value: Environment

Palau

iso2Code: PW

capitalCity: Koror

country_code: PLW

country_name: Palau

value: Land area where elevation is below 5 meters (% of total land area)

value: Environment: Land use


name: Land area where elevation is below 5 meters (% of total land area)

value: World Development Indicators

sourceNone: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.

value: Climate Change

Papua New Guinea

iso2Code: PG

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XN

value: Lower middle income

iso2code: XH

value: Blend

capitalCity: Port Moresby

country_code: PNG

country_name: Papua New Guinea

value: Weighted average

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Annual

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.

schema: wb


Poland

iso2Code: PL

value: Europe & Central Asia

iso2code: XD

value: High income

iso2code: XF

value: IBRD

capitalCity: Warsaw

country_code: POL

country_name: Poland

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


value: World Development Indicators

value: Environment

Pre-demographic dividend

value: Aggregates

country_code: PRE

country_name: Pre-demographic dividend

value: Land area where elevation is below 5 meters (% of total land area)

value: Environment: Land use


value: Climate Change

Puerto Rico

iso2Code: PR

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XX

value: Not classified

capitalCity: San Juan

country_code: PRI

country_name: Puerto Rico


Korea, Dem. People's Rep.

iso2Code: KP

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XM

value: Low income

capitalCity: Pyongyang

country_code: PRK

country_name: Korea, Dem. People's Rep.

value: Weighted average

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.


Portugal

iso2Code: PT

value: Europe & Central Asia

value: High income

capitalCity: Lisbon

country_code: PRT

country_name: Portugal

value: Annual

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


value: World Development Indicators

value: Environment

Paraguay

iso2Code: PY

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

iso2code: XT

value: Upper middle income

value: IBRD

capitalCity: Asuncion

country_code: PRY

country_name: Paraguay

value: Land area where elevation is below 5 meters (% of total land area)

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


value: Climate Change

West Bank and Gaza

iso2Code: PS

iso2code: ZQ

value: Middle East & North Africa

iso2code: XQ

value: Middle East & North Africa (excluding high income)

value: Not classified

country_code: PSE

country_name: West Bank and Gaza

value: Environment: Land use


Pacific island small states

value: Aggregates

country_code: PSS

country_name: Pacific island small states

value: Weighted average

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.


country_code: PST

country_name: Post-demographic dividend

value: Annual

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


value: World Development Indicators

value: Environment

French Polynesia

iso2Code: PF

value: East Asia & Pacific

value: High income

capitalCity: Papeete

country_code: PYF

country_name: French Polynesia


value: Climate Change

Qatar

iso2Code: QA

capitalCity: Doha

country_code: QAT

country_name: Qatar

value: Land area where elevation is below 5 meters (% of total land area)

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


Romania

iso2Code: RO

value: Europe & Central Asia

value: IBRD

capitalCity: Bucharest

country_code: ROU

country_name: Romania


Russian Federation

iso2Code: RU

value: Europe & Central Asia (excluding high income)

value: Upper middle income

capitalCity: Moscow

country_code: RUS

country_name: Russian Federation

value: Environment: Land use


Rwanda

iso2Code: RW

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

value: Low income

iso2code: XI

value: IDA

capitalCity: Kigali

country_code: RWA

country_name: Rwanda

value: Weighted average

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.


value: World Development Indicators

value: Environment

South Asia

value: Aggregates

country_code: SAS

country_name: South Asia

value: Annual

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


value: Climate Change

Saudi Arabia

iso2Code: SA

value: Middle East & North Africa

iso2code: XD

value: High income

iso2code: XX

value: Not classified

capitalCity: Riyadh

country_code: SAU

country_name: Saudi Arabia

value: Land area where elevation is below 5 meters (% of total land area)

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


Sudan

iso2Code: SD

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

iso2code: XM

value: Low income

value: IDA

capitalCity: Khartoum

country_code: SDN

country_name: Sudan

value: Environment: Land use


value: World Development Indicators

value: Environment

Senegal

iso2Code: SN

iso2code: XN

value: Lower middle income

capitalCity: Dakar

country_code: SEN

country_name: Senegal

value: Weighted average

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.


value: Climate Change

Singapore

iso2Code: SG

value: East Asia & Pacific

capitalCity: Singapore

country_code: SGP

country_name: Singapore

value: Annual

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


Solomon Islands

iso2Code: SB

value: East Asia & Pacific (excluding high income)

capitalCity: Honiara

country_code: SLB

country_name: Solomon Islands

value: Land area where elevation is below 5 meters (% of total land area)

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


Sierra Leone

iso2Code: SL

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

value: Low income

value: IDA

capitalCity: Freetown

country_code: SLE

country_name: Sierra Leone


value: World Development Indicators

value: Environment

El Salvador

iso2Code: SV

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

iso2code: XT

value: Upper middle income

iso2code: XF

value: IBRD

capitalCity: San Salvador

country_code: SLV

country_name: El Salvador

value: Environment: Land use


value: Climate Change

San Marino

iso2Code: SM

value: Europe & Central Asia

value: High income

value: Not classified

capitalCity: San Marino

country_code: SMR

country_name: San Marino

value: Weighted average

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Annual

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).


Somalia

iso2Code: SO

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

value: Low income

iso2code: XI

value: IDA

capitalCity: Mogadishu

country_code: SOM

country_name: Somalia

value: Land area where elevation is below 5 meters (% of total land area)

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


value: World Development Indicators

value: Climate Change

value: Environment

Serbia

iso2Code: RS

value: Europe & Central Asia (excluding high income)

value: Upper middle income

value: IBRD

capitalCity: Belgrade

country_code: SRB

country_name: Serbia

value: Environment: Land use


name: Sub-Saharan Africa (excluding high income)

value: Aggregates

country_code: SSA

value: Weighted average

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Annual


South Sudan

iso2Code: SS

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

iso2code: XM

value: Low income

value: IDA

capitalCity: Juba

country_code: SSD

country_name: South Sudan

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).


value: World Development Indicators

country_code: SSF

country_name: Sub-Saharan Africa

value: Land area where elevation is below 5 meters (% of total land area)

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


value: Climate Change

value: Environment

country_code: SST

country_name: Small states


Sao Tome and Principe

iso2Code: ST

iso2code: XN

value: Lower middle income

capitalCity: Sao Tome

country_code: STP

country_name: São Tomé and Principe

value: Environment: Land use


Suriname

iso2Code: SR

value: Latin America & Caribbean

value: Latin America & Caribbean (excluding high income)

value: Upper middle income

value: IBRD

capitalCity: Paramaribo

country_code: SUR

country_name: Suriname

value: Weighted average

value: CC BY-4.0


Slovak Republic

iso2Code: SK

value: Europe & Central Asia

iso2code: XD

value: High income

iso2code: XX

value: Not classified

capitalCity: Bratislava

country_code: SVK

country_name: Slovak Republic

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Annual


value: World Development Indicators

Slovenia

iso2Code: SI

capitalCity: Ljubljana

country_code: SVN

country_name: Slovenia

value: Land area where elevation is below 5 meters (% of total land area)

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).


value: Climate Change

value: Environment

Sweden

iso2Code: SE

capitalCity: Stockholm

country_code: SWE

country_name: Sweden

value: Environment: Land use

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


Eswatini

iso2Code: SZ

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

value: Lower middle income

iso2code: XF

value: IBRD

capitalCity: Mbabane

country_code: SWZ

country_name: Eswatini


Sint Maarten (Dutch part)

iso2Code: SX

iso2code: ZJ

value: Latin America & Caribbean

value: High income

capitalCity: Philipsburg

country_code: SXM

country_name: Sint Maarten (Dutch part)

value: Weighted average

value: CC BY-4.0


value: World Development Indicators

Seychelles

iso2Code: SC

iso2code: ZG

capitalCity: Victoria

country_code: SYC

country_name: Seychelles

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Annual


Syrian Arab Republic

iso2Code: SY

iso2code: ZQ

value: Middle East & North Africa

iso2code: XQ

value: Middle East & North Africa (excluding high income)

value: Low income

iso2code: XI

value: IDA

capitalCity: Damascus

country_code: SYR

country_name: Syrian Arab Republic

value: Land area where elevation is below 5 meters (% of total land area)

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).


value: Climate Change

value: Environment

Turks and Caicos Islands

iso2Code: TC

value: Not classified

capitalCity: Grand Turk

country_code: TCA

country_name: Turks and Caicos Islands

value: Environment: Land use

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


Chad

iso2Code: TD

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

iso2code: XM

capitalCity: N'Djamena

country_code: TCD

country_name: Chad

value: Weighted average

value: CC BY-4.0


value: World Development Indicators

name: East Asia & Pacific (IDA & IBRD countries)

value: Aggregates

country_code: TEA

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Annual


name: Europe & Central Asia (IDA & IBRD countries)

country_code: TEC

value: Land area where elevation is below 5 meters (% of total land area)


Togo

iso2Code: TG

value: Low income

value: IDA

capitalCity: Lome

country_code: TGO

country_name: Togo

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


value: Climate Change

value: Environment

Thailand

iso2Code: TH

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XT

value: Upper middle income

value: IBRD

capitalCity: Bangkok

country_code: THA

country_name: Thailand

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).


Tajikistan

iso2Code: TJ

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

iso2code: XN

value: Lower middle income

capitalCity: Dushanbe

country_code: TJK

country_name: Tajikistan

value: Weighted average

value: Environment: Land use

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


value: World Development Indicators

Turkmenistan

iso2Code: TM

iso2code: XF

capitalCity: Ashgabat

country_code: TKM

country_name: Turkmenistan

value: Land area where elevation is below 5 meters (% of total land area)

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Annual


value: Climate Change

value: Environment

name: Latin America & the Caribbean (IDA & IBRD countries)

value: Aggregates

country_code: TLA

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


Timor-Leste

iso2Code: TL

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XH

value: Blend

capitalCity: Dili

country_code: TLS

country_name: Timor-Leste

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).


name: Middle East & North Africa (IDA & IBRD countries)

country_code: TMN

value: Weighted average


Tonga

iso2Code: TO

value: Upper middle income

value: IDA

capitalCity: Nuku'alofa

country_code: TON

country_name: Tonga

value: Environment: Land use


value: World Development Indicators

country_code: TSA

country_name: South Asia (IDA & IBRD)

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


name: Sub-Saharan Africa (IDA & IBRD countries)

country_code: TSS

value: Land area where elevation is below 5 meters (% of total land area)

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.


value: Climate Change

value: Environment

Trinidad and Tobago

iso2Code: TT

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XD

value: High income

value: IBRD

capitalCity: Port-of-Spain

country_code: TTO

country_name: Trinidad and Tobago

value: Annual


Tunisia

iso2Code: TN

iso2code: ZQ

value: Middle East & North Africa

iso2code: XQ

value: Middle East & North Africa (excluding high income)

value: Lower middle income

capitalCity: Tunis

country_code: TUN

country_name: Tunisia

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).


value: World Development Indicators

Turkiye

iso2Code: TR

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

value: Upper middle income

capitalCity: Ankara

country_code: TUR

country_name: Turkey

value: Weighted average

value: Environment: Land use


value: Climate Change

Tuvalu

iso2Code: TV

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XI

value: IDA

capitalCity: Funafuti

country_code: TUV

country_name: Tuvalu

value: Land area where elevation is below 5 meters (% of total land area)

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


value: Environment

Tanzania

iso2Code: TZ

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

value: Lower middle income

capitalCity: Dodoma

country_code: TZA

country_name: Tanzania

value: Annual

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


value: World Development Indicators

Uganda

iso2Code: UG

iso2code: XM

value: Low income

capitalCity: Kampala

country_code: UGA

country_name: Uganda

value: Weighted average

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).


value: Climate Change

Ukraine

iso2Code: UA

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

iso2code: XN

iso2code: XF

value: IBRD

capitalCity: Kiev

country_code: UKR

country_name: Ukraine

value: Environment: Land use


Upper middle income

iso2Code: XT

value: Aggregates

country_code: UMC

country_name: Upper middle income

value: Land area where elevation is below 5 meters (% of total land area)

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).


value: Environment

Uruguay

iso2Code: UY

iso2code: ZJ

value: Latin America & Caribbean

value: High income

capitalCity: Montevideo

country_code: URY

country_name: Uruguay

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


value: World Development Indicators

United States

iso2Code: US

iso2code: XU

value: North America

iso2code: XD

iso2code: XX

value: Not classified

capitalCity: Washington D.C.

country_code: USA

country_name: United States

value: Annual

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


value: Climate Change

Uzbekistan

iso2Code: UZ

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

value: Lower middle income

iso2code: XH

value: Blend

capitalCity: Tashkent

country_code: UZB

country_name: Uzbekistan

value: Weighted average

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).


St. Vincent and the Grenadines

iso2Code: VC

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

value: Upper middle income

capitalCity: Kingstown

country_code: VCT

country_name: St. Vincent and the Grenadines

value: Land area where elevation is below 5 meters (% of total land area)

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Environment: Land use

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).


value: World Development Indicators

value: Environment

Venezuela, RB

iso2Code: VE

value: Latin America & Caribbean

iso2code: XY

value: Not classified

value: IBRD

capitalCity: Caracas

country_code: VEN

country_name: Venezuela, RB

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


value: Climate Change

British Virgin Islands

iso2Code: VG

value: High income

capitalCity: Road Town

country_code: VGB

country_name: British Virgin Islands

value: Annual

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


Virgin Islands (U.S.)

iso2Code: VI

capitalCity: Charlotte Amalie

country_code: VIR

country_name: Virgin Islands (U.S.)

value: Weighted average

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).


Viet Nam

iso2Code: VN

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XN

value: Lower middle income

capitalCity: Hanoi

country_code: VNM

country_name: Vietnam

value: Land area where elevation is below 5 meters (% of total land area)


Vanuatu

iso2Code: VU

iso2code: XI

value: IDA

capitalCity: Port-Vila

country_code: VUT

country_name: Vanuatu

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Environment: Land use

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).


value: World Development Indicators

value: Environment

World

value: Aggregates

country_code: WLD

country_name: World


value: Climate Change

Samoa

iso2Code: WS

capitalCity: Apia

country_code: WSM

country_name: Samoa

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


Kosovo

iso2Code: XK

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

iso2code: XT

value: Upper middle income

capitalCity: Pristina

country_code: XKX

country_name: Kosovo

value: Annual

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


Yemen, Rep.

iso2Code: YE

iso2code: ZQ

value: Middle East & North Africa

iso2code: XQ

value: Middle East & North Africa (excluding high income)

iso2code: XM

value: Low income

capitalCity: Sana'a

country_code: YEM

country_name: Yemen, Rep.

value: Weighted average

value: The 2007 Intergovernmental Panel on Climate Change's (IPCC) assessment report concluded that global warming is “unequivocal” and gave the strongest warning yet about the role of human activities. The report estimated that sea levels would rise approximately 49 centimeters over the next 100 years, with a range of uncertainty of 20–86 centimeters. That will lead to increased coastal flooding through direct inundation and a higher base for storm surges, allowing flooding of larger areas and higher elevations. Climate model simulations predict an increase in average surface air temperature of about 2.5°C by 2100 (Kattenberg and others 1996) and increase of “killer” heat waves during the warm season (Karl and others 1997).


South Africa

iso2Code: ZA

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

iso2code: XF

value: IBRD

capitalCity: Pretoria

country_code: ZAF

country_name: South Africa

value: Land area where elevation is below 5 meters (% of total land area)

value: CC BY-4.0

value: Scientists use the terms climate change and global warming to refer to the gradual increase in the Earth's surface temperature that has accelerated since the industrial revolution and especially over the past two decades. Most global warming has been caused by human activities that have changed the chemical composition of the atmosphere through a buildup of greenhouse gases - primarily carbon dioxide, methane, and nitrous oxide. Rising global temperatures will cause sea level rise and alter local climate conditions, affecting forests, crop yields, and water supplies, and may affect human health, animals, and many types of ecosystems.

value: Environment: Land use


value: World Development Indicators

value: Climate Change

value: Environment

Zambia

iso2Code: ZM

value: Lower middle income

value: IDA

capitalCity: Lusaka

country_code: ZMB

country_name: Zambia

value: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).

value: Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.


Zimbabwe

iso2Code: ZW

iso2code: XH

value: Blend

capitalCity: Harare

country_code: ZWE

country_name: Zimbabwe

value: Annual

value: Land area below 5m is the percentage of total land where the elevation is 5 meters or less.


Land under fonio production (hectares)

value: Africa Development Indicators

sourceNone: Land under fonio production refers to harvested area, although some countries report only sown or cultivated area. Production data on relate to crop harvested for dry grain only. Crop harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.

Africa

value: Aggregates

country_code: AFR

country_name: Africa

value: Sum

value: Land under fonio production (hectares)

value: Food and Agriculture Organization, electronic files and web site.

value: Environment: Agricultural production


Angola

iso2Code: AO

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

iso2code: XN

value: IBRD

capitalCity: Luanda

country_code: AGO

country_name: Angola

value: Land under fonio production refers to harvested area, although some countries report only sown or cultivated area. Production data on relate to crop harvested for dry grain only. Crop harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.


Land under fonio production (hectares)

Burundi

iso2Code: BI

value: Low income

iso2code: XI

capitalCity: Bujumbura

country_code: BDI

country_name: Burundi


Benin

iso2Code: BJ

value: Lower middle income

value: IDA

capitalCity: Porto-Novo

country_code: BEN

country_name: Benin


Land under fonio production (hectares)

Burkina Faso

iso2Code: BF

capitalCity: Ouagadougou

country_code: BFA

country_name: Burkina Faso


Botswana

iso2Code: BW

iso2code: XT

value: Upper middle income

capitalCity: Gaborone

country_code: BWA

country_name: Botswana


Land under fonio production (hectares)

Central African Republic

iso2Code: CF

capitalCity: Bangui

country_code: CAF

country_name: Central African Republic


Cote d'Ivoire

iso2Code: CI

capitalCity: Yamoussoukro

country_code: CIV

country_name: Côte d'Ivoire


Land under fonio production (hectares)

Cameroon

iso2Code: CM

value: Blend

capitalCity: Yaounde

country_code: CMR

country_name: Cameroon


Congo, Dem. Rep.

iso2Code: CD

iso2code: ZG

iso2code: XM

capitalCity: Kinshasa

country_code: COD

country_name: Congo, Dem. Rep.

value: Annual


Land under fonio production (hectares)

Congo, Rep.

iso2Code: CG

iso2code: ZF

capitalCity: Brazzaville

country_code: COG

country_name: Congo, Rep.


Comoros

iso2Code: KM

capitalCity: Moroni

country_code: COM

country_name: Comoros


Land under fonio production (hectares)

Cabo Verde

iso2Code: CV

iso2code: XH

capitalCity: Praia

country_code: CPV

country_name: Cabo Verde


Djibouti

iso2Code: DJ

iso2code: ZQ

value: Middle East & North Africa

iso2code: XQ

value: Middle East & North Africa (excluding high income)

iso2code: XN

capitalCity: Djibouti

country_code: DJI

country_name: Djibouti


Land under fonio production (hectares)

value: Africa Development Indicators

Algeria

iso2Code: DZ

iso2code: XF

capitalCity: Algiers

country_code: DZA

country_name: Algeria


Egypt, Arab Rep.

iso2Code: EG

capitalCity: Cairo

country_code: EGY

country_name: Egypt, Arab Rep.

value: Sum


Land under fonio production (hectares)

Eritrea

iso2Code: ER

iso2code: XI

capitalCity: Asmara

country_code: ERI

country_name: Eritrea

value: Land under fonio production (hectares)


Ethiopia

iso2Code: ET

capitalCity: Addis Ababa

country_code: ETH

country_name: Ethiopia

value: Food and Agriculture Organization, electronic files and web site.


Land under fonio production (hectares)

Gabon

iso2Code: GA

iso2code: ZG

iso2code: XT

capitalCity: Libreville

country_code: GAB

country_name: Gabon

value: Environment: Agricultural production


Ghana

iso2Code: GH

value: Sub-Saharan Africa

iso2code: ZF

capitalCity: Accra

country_code: GHA

country_name: Ghana


Land under fonio production (hectares)

Guinea

iso2Code: GN

value: Sub-Saharan Africa (excluding high income)

capitalCity: Conakry

country_code: GIN

country_name: Guinea


Gambia, The

iso2Code: GM

iso2code: XM

capitalCity: Banjul

country_code: GMB

country_name: Gambia, The


Land under fonio production (hectares)

Guinea-Bissau

iso2Code: GW

capitalCity: Bissau

country_code: GNB

country_name: Guinea-Bissau


Equatorial Guinea

iso2Code: GQ

value: IBRD

capitalCity: Malabo

country_code: GNQ

country_name: Equatorial Guinea


Land under fonio production (hectares)

Kenya

iso2Code: KE

iso2code: XN

iso2code: XH

capitalCity: Nairobi

country_code: KEN

country_name: Kenya

value: Land under fonio production refers to harvested area, although some countries report only sown or cultivated area. Production data on relate to crop harvested for dry grain only. Crop harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.


Liberia

iso2Code: LR

value: Low income

capitalCity: Monrovia

country_code: LBR

country_name: Liberia


Land under fonio production (hectares)

Libya

iso2Code: LY

iso2code: ZQ

iso2code: XQ

iso2code: XF

capitalCity: Tripoli

country_code: LBY

country_name: Libya


Lesotho

iso2Code: LS

iso2code: ZG

value: Lower middle income

iso2code: XI

capitalCity: Maseru

country_code: LSO

country_name: Lesotho


Land under fonio production (hectares)

Morocco

iso2Code: MA

capitalCity: Rabat

country_code: MAR

country_name: Morocco


Madagascar

iso2Code: MG

iso2code: ZF

value: IDA

capitalCity: Antananarivo

country_code: MDG

country_name: Madagascar


Land under fonio production (hectares)

Mali

iso2Code: ML

iso2code: XM

capitalCity: Bamako

country_code: MLI

country_name: Mali


Mozambique

iso2Code: MZ

capitalCity: Maputo

country_code: MOZ

country_name: Mozambique


Land under fonio production (hectares)

Mauritania

iso2Code: MR

capitalCity: Nouakchott

country_code: MRT

country_name: Mauritania


Mauritius

iso2Code: MU

iso2code: XT

value: Upper middle income

capitalCity: Port Louis

country_code: MUS

country_name: Mauritius


Land under fonio production (hectares)

Malawi

iso2Code: MW

capitalCity: Lilongwe

country_code: MWI

country_name: Malawi


North Africa

value: Aggregates

country_code: NAF

country_name: North Africa


Land under fonio production (hectares)

Namibia

capitalCity: Windhoek

country_code: NAM

country_name: Namibia

value: Annual


Niger

iso2Code: NE

capitalCity: Niamey

country_code: NER

country_name: Niger


Land under fonio production (hectares)

Nigeria

iso2Code: NG

iso2code: XN

iso2code: XH

value: Blend

capitalCity: Abuja

country_code: NGA

country_name: Nigeria


Rwanda

iso2Code: RW

capitalCity: Kigali

country_code: RWA

country_name: Rwanda


Land under fonio production (hectares)

Sudan

iso2Code: SD

iso2code: ZG

capitalCity: Khartoum

country_code: SDN

country_name: Sudan


Senegal

iso2Code: SN

iso2code: XI

capitalCity: Dakar

country_code: SEN

country_name: Senegal


Land under fonio production (hectares)

Sierra Leone

iso2Code: SL

iso2code: ZF

capitalCity: Freetown

country_code: SLE

country_name: Sierra Leone


Somalia

iso2Code: SO

iso2code: XM

capitalCity: Mogadishu

country_code: SOM

country_name: Somalia


Land under fonio production (hectares)

country_code: SSA

country_name: Sub-Saharan Africa (excluding high income)


South Sudan

iso2Code: SS

capitalCity: Juba

country_code: SSD

country_name: South Sudan


Land under fonio production (hectares)

country_code: SSF

country_name: Sub-Saharan Africa


Sao Tome and Principe

iso2Code: ST

capitalCity: Sao Tome

country_code: STP

country_name: São Tomé and Principe


Land under fonio production (hectares)

Eswatini

iso2Code: SZ

iso2code: XF

capitalCity: Mbabane

country_code: SWZ

country_name: Eswatini


name: Sub-Saharan Africa excluding South Africa

country_code: SXZ


Seychelles

iso2Code: SC

iso2code: XD

value: High income

capitalCity: Victoria

country_code: SYC

country_name: Seychelles


Land under fonio production (hectares)

value: Africa Development Indicators

Chad

iso2Code: TD

capitalCity: N'Djamena

country_code: TCD

country_name: Chad


Togo

iso2Code: TG

capitalCity: Lome

country_code: TGO

country_name: Togo

value: Sum


Land under fonio production (hectares)

Tunisia

iso2Code: TN

iso2code: ZQ

value: Middle East & North Africa

iso2code: XQ

value: Middle East & North Africa (excluding high income)

iso2code: XN

capitalCity: Tunis

country_code: TUN

country_name: Tunisia

value: Land under fonio production (hectares)


Tanzania

iso2Code: TZ

iso2code: ZG

value: Sub-Saharan Africa

iso2code: XI

capitalCity: Dodoma

country_code: TZA

country_name: Tanzania

value: Food and Agriculture Organization, electronic files and web site.

value: Environment: Agricultural production


Land under fonio production (hectares)

Uganda

iso2Code: UG

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

capitalCity: Kampala

country_code: UGA

country_name: Uganda

value: Land under fonio production refers to harvested area, although some countries report only sown or cultivated area. Production data on relate to crop harvested for dry grain only. Crop harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.


name: Sub-Saharan Africa excluding South Africa and Nigeria

country_code: XZN


South Africa

iso2Code: ZA

iso2code: XT

value: IBRD

capitalCity: Pretoria

country_code: ZAF

country_name: South Africa


Land under fonio production (hectares)

Zambia

iso2Code: ZM

value: Lower middle income

value: IDA

capitalCity: Lusaka

country_code: ZMB

country_name: Zambia


Zimbabwe

iso2Code: ZW

iso2code: XH

capitalCity: Harare

country_code: ZWE

country_name: Zimbabwe


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

sourceNone: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.

Afghanistan

iso2Code: AF

value: South Asia

iso2code: XM

value: Low income

capitalCity: Kabul

country_code: AFG

country_name: Afghanistan

value: Weighted average

value: Tree Cover Loss

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.

value: CC BY-4.0

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Hectares

value: Identifies areas of gross tree cover loss.

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).

value: Environment: Natural capital endowment and management


Angola

iso2Code: AO

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

iso2code: XF

capitalCity: Luanda

country_code: AGO

country_name: Angola

value: Annual

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.


Tree Cover Loss (hectares)

Albania

iso2Code: AL

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

value: Upper middle income

value: IBRD

capitalCity: Tirane

country_code: ALB

country_name: Albania


value: Environment, Social and Governance (ESG) Data

Andorra

iso2Code: AD

iso2code: XD

value: High income

iso2code: XX

value: Not classified

capitalCity: Andorra la Vella

country_code: AND

country_name: Andorra

value: Weighted average


Tree Cover Loss (hectares)

Arab World

value: Aggregates

country_code: ARB

country_name: Arab World

value: Tree Cover Loss

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.

value: CC BY-4.0

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.


United Arab Emirates

iso2Code: AE

iso2code: ZQ

value: Middle East & North Africa

capitalCity: Abu Dhabi

country_code: ARE

country_name: United Arab Emirates

value: Hectares

value: Identifies areas of gross tree cover loss.

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

Argentina

iso2Code: AR

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

capitalCity: Buenos Aires

country_code: ARG

country_name: Argentina

value: Annual

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.


value: Environment, Social and Governance (ESG) Data

Armenia

iso2Code: AM

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

iso2code: XT

value: Upper middle income

value: IBRD

capitalCity: Yerevan

country_code: ARM

country_name: Armenia


Tree Cover Loss (hectares)

Antigua and Barbuda

iso2Code: AG

value: High income

capitalCity: Saint John's

country_code: ATG

country_name: Antigua and Barbuda

value: Weighted average

value: Tree Cover Loss

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.


Australia

iso2Code: AU

value: East Asia & Pacific

value: Not classified

capitalCity: Canberra

country_code: AUS

country_name: Australia

value: CC BY-4.0

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Hectares


Tree Cover Loss (hectares)

Austria

iso2Code: AT

capitalCity: Vienna

country_code: AUT

country_name: Austria

value: Identifies areas of gross tree cover loss.

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).

value: Environment: Natural capital endowment and management


value: Environment, Social and Governance (ESG) Data

Azerbaijan

iso2Code: AZ

capitalCity: Baku

country_code: AZE

country_name: Azerbaijan

value: Annual

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.


Tree Cover Loss (hectares)

Burundi

iso2Code: BI

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

iso2code: XM

value: Low income

iso2code: XI

value: IDA

capitalCity: Bujumbura

country_code: BDI

country_name: Burundi


Belgium

iso2Code: BE

value: Europe & Central Asia

iso2code: XD

value: High income

iso2code: XX

capitalCity: Brussels

country_code: BEL

country_name: Belgium

value: Weighted average

value: Tree Cover Loss


Tree Cover Loss (hectares)

Benin

iso2Code: BJ

iso2code: XN

value: Lower middle income

capitalCity: Porto-Novo

country_code: BEN

country_name: Benin

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.

value: CC BY-4.0


Burkina Faso

iso2Code: BF

capitalCity: Ouagadougou

country_code: BFA

country_name: Burkina Faso

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Hectares

value: Identifies areas of gross tree cover loss.


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Bangladesh

iso2Code: BD

value: South Asia

capitalCity: Dhaka

country_code: BGD

country_name: Bangladesh

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).

value: Environment: Natural capital endowment and management


Bulgaria

iso2Code: BG

value: Europe & Central Asia (excluding high income)

iso2code: XT

value: Upper middle income

iso2code: XF

value: IBRD

capitalCity: Sofia

country_code: BGR

country_name: Bulgaria

value: Annual

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.


Tree Cover Loss (hectares)

Bahrain

iso2Code: BH

iso2code: ZQ

value: Middle East & North Africa

value: High income

value: Not classified

capitalCity: Manama

country_code: BHR

country_name: Bahrain

value: Weighted average


Bahamas, The

iso2Code: BS

iso2code: ZJ

value: Latin America & Caribbean

capitalCity: Nassau

country_code: BHS

country_name: Bahamas, The

value: Tree Cover Loss

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.

value: CC BY-4.0


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Bosnia and Herzegovina

iso2Code: BA

value: Europe & Central Asia

capitalCity: Sarajevo

country_code: BIH

country_name: Bosnia and Herzegovina

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Hectares

value: Identifies areas of gross tree cover loss.


Belarus

iso2Code: BY

value: Europe & Central Asia (excluding high income)

value: Upper middle income

capitalCity: Minsk

country_code: BLR

country_name: Belarus

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

Belize

iso2Code: BZ

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

value: IBRD

capitalCity: Belmopan

country_code: BLZ

country_name: Belize

value: Annual

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.


Bolivia

iso2Code: BO

value: Latin America & Caribbean

value: Lower middle income

capitalCity: La Paz

country_code: BOL

country_name: Bolivia

value: Weighted average


Tree Cover Loss (hectares)

Brazil

iso2Code: BR

capitalCity: Brasilia

country_code: BRA

country_name: Brazil

value: Tree Cover Loss

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.

value: CC BY-4.0


value: Environment, Social and Governance (ESG) Data

Barbados

iso2Code: BB

iso2code: XD

value: High income

iso2code: XX

value: Not classified

capitalCity: Bridgetown

country_code: BRB

country_name: Barbados

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.


Tree Cover Loss (hectares)

Brunei Darussalam

iso2Code: BN

value: East Asia & Pacific

capitalCity: Bandar Seri Begawan

country_code: BRN

country_name: Brunei Darussalam

value: Hectares

value: Identifies areas of gross tree cover loss.


Bhutan

iso2Code: BT

value: South Asia

iso2code: XN

iso2code: XI

value: IDA

capitalCity: Thimphu

country_code: BTN

country_name: Bhutan

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

Botswana

iso2Code: BW

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

iso2code: XT

value: Upper middle income

iso2code: XF

value: IBRD

capitalCity: Gaborone

country_code: BWA

country_name: Botswana

value: Annual

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.


value: Environment, Social and Governance (ESG) Data

Central African Republic

iso2Code: CF

iso2code: XM

value: Low income

capitalCity: Bangui

country_code: CAF

country_name: Central African Republic

value: Weighted average

value: Tree Cover Loss

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.

value: CC BY-4.0


Tree Cover Loss (hectares)

Canada

iso2Code: CA

iso2code: XU

value: North America

value: High income

value: Not classified

capitalCity: Ottawa

country_code: CAN

country_name: Canada

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Hectares

value: Identifies areas of gross tree cover loss.


Central Europe and the Baltics

value: Aggregates

country_code: CEB

country_name: Central Europe and the Baltics

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

Switzerland

iso2Code: CH

value: Europe & Central Asia

capitalCity: Bern

country_code: CHE

country_name: Switzerland

value: Annual


value: Environment, Social and Governance (ESG) Data

Chile

iso2Code: CL

iso2code: ZJ

value: Latin America & Caribbean

value: IBRD

capitalCity: Santiago

country_code: CHL

country_name: Chile

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.


Tree Cover Loss (hectares)

China

iso2Code: CN

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

value: Upper middle income

capitalCity: Beijing

country_code: CHN

country_name: China

value: Weighted average

value: Tree Cover Loss

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.


Cote d'Ivoire

iso2Code: CI

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

value: Lower middle income

value: IDA

capitalCity: Yamoussoukro

country_code: CIV

country_name: Côte d'Ivoire

value: CC BY-4.0

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Hectares


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Cameroon

iso2Code: CM

iso2code: XH

value: Blend

capitalCity: Yaounde

country_code: CMR

country_name: Cameroon

value: Annual

value: Identifies areas of gross tree cover loss.

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).

value: Environment: Natural capital endowment and management


Congo, Dem. Rep.

iso2Code: CD

value: Low income

iso2code: XI

capitalCity: Kinshasa

country_code: COD

country_name: Congo, Dem. Rep.

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.


Tree Cover Loss (hectares)

Congo, Rep.

iso2Code: CG

iso2code: ZG

iso2code: XN

capitalCity: Brazzaville

country_code: COG

country_name: Congo, Rep.

value: Weighted average

value: Tree Cover Loss


Colombia

iso2Code: CO

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

iso2code: XT

value: Upper middle income

iso2code: XF

value: IBRD

capitalCity: Bogota

country_code: COL

country_name: Colombia

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.


Tree Cover Loss (hectares)

Comoros

iso2Code: KM

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

value: Lower middle income

value: IDA

capitalCity: Moroni

country_code: COM

country_name: Comoros

value: CC BY-4.0

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.


value: Environment, Social and Governance (ESG) Data

Cabo Verde

iso2Code: CV

value: Blend

capitalCity: Praia

country_code: CPV

country_name: Cabo Verde

value: Annual

value: Hectares

value: Identifies areas of gross tree cover loss.

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).


Tree Cover Loss (hectares)

Costa Rica

iso2Code: CR

iso2code: ZJ

value: Latin America & Caribbean

capitalCity: San Jose

country_code: CRI

country_name: Costa Rica

value: Weighted average

value: Tree Cover Loss

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.

value: Environment: Natural capital endowment and management


Caribbean small states

value: Aggregates

country_code: CSS

country_name: Caribbean small states

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.


Tree Cover Loss (hectares)

Cuba

iso2Code: CU

value: Latin America & Caribbean (excluding high income)

value: Upper middle income

iso2code: XX

value: Not classified

capitalCity: Havana

country_code: CUB

country_name: Cuba


Cyprus

iso2Code: CY

value: Europe & Central Asia

iso2code: XD

value: High income

capitalCity: Nicosia

country_code: CYP

country_name: Cyprus

value: CC BY-4.0

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Czechia

iso2Code: CZ

capitalCity: Prague

country_code: CZE

country_name: Czech Republic

value: Annual

value: Hectares


Germany

iso2Code: DE

capitalCity: Berlin

country_code: DEU

country_name: Germany

value: Identifies areas of gross tree cover loss.

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).


Tree Cover Loss (hectares)

Djibouti

iso2Code: DJ

iso2code: ZQ

value: Middle East & North Africa

iso2code: XQ

value: Middle East & North Africa (excluding high income)

value: Lower middle income

iso2code: XI

value: IDA

capitalCity: Djibouti

country_code: DJI

country_name: Djibouti

value: Weighted average

value: Tree Cover Loss


Dominica

iso2Code: DM

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

iso2code: XT

value: Upper middle income

iso2code: XH

value: Blend

capitalCity: Roseau

country_code: DMA

country_name: Dominica

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Denmark

iso2Code: DK

value: Europe & Central Asia

value: High income

value: Not classified

capitalCity: Copenhagen

country_code: DNK

country_name: Denmark

value: CC BY-4.0

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Annual


Dominican Republic

iso2Code: DO

iso2code: XF

value: IBRD

capitalCity: Santo Domingo

country_code: DOM

country_name: Dominican Republic

value: Hectares

value: Identifies areas of gross tree cover loss.

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).


Tree Cover Loss (hectares)

Algeria

iso2Code: DZ

value: Middle East & North Africa

value: Middle East & North Africa (excluding high income)

iso2code: XN

value: Lower middle income

capitalCity: Algiers

country_code: DZA

country_name: Algeria

value: Weighted average

value: Tree Cover Loss


name: East Asia & Pacific (excluding high income)

value: Aggregates

country_code: EAP

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.

value: Environment: Natural capital endowment and management


value: Environment, Social and Governance (ESG) Data

country_code: EAR

country_name: Early-demographic dividend


country_code: EAS

country_name: East Asia & Pacific

value: CC BY-4.0


name: Europe & Central Asia (excluding high income)

country_code: ECA

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.


country_code: ECS

country_name: Europe & Central Asia

value: Annual


Ecuador

iso2Code: EC

iso2code: ZJ

value: Latin America & Caribbean

value: Latin America & Caribbean (excluding high income)

value: Upper middle income

value: IBRD

capitalCity: Quito

country_code: ECU

country_name: Ecuador


Tree Cover Loss (hectares)

Egypt, Arab Rep.

iso2Code: EG

value: Middle East & North Africa

capitalCity: Cairo

country_code: EGY

country_name: Egypt, Arab Rep.

value: Hectares

value: Identifies areas of gross tree cover loss.

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).


Euro area

iso2Code: XC

country_code: EMU

country_name: Euro area

value: Weighted average

value: Tree Cover Loss


Tree Cover Loss (hectares)

Eritrea

iso2Code: ER

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

iso2code: XM

value: Low income

value: IDA

capitalCity: Asmara

country_code: ERI

country_name: Eritrea

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.


value: Environment, Social and Governance (ESG) Data

Spain

iso2Code: ES

value: Europe & Central Asia

iso2code: XD

value: High income

iso2code: XX

value: Not classified

capitalCity: Madrid

country_code: ESP

country_name: Spain

value: CC BY-4.0

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

Estonia

iso2Code: EE

capitalCity: Tallinn

country_code: EST

country_name: Estonia

value: Annual

value: Hectares

value: Identifies areas of gross tree cover loss.


Ethiopia

iso2Code: ET

iso2code: XI

capitalCity: Addis Ababa

country_code: ETH

country_name: Ethiopia

value: Weighted average

value: Tree Cover Loss

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).


Tree Cover Loss (hectares)

European Union

iso2Code: EU

value: Aggregates

country_code: EUU

country_name: European Union


name: Fragile and conflict affected situations

country_code: FCS


Finland

iso2Code: FI

capitalCity: Helsinki

country_code: FIN

country_name: Finland


Tree Cover Loss (hectares)

Fiji

iso2Code: FJ

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XT

value: Upper middle income

iso2code: XH

value: Blend

capitalCity: Suva

country_code: FJI

country_name: Fiji


value: Environment, Social and Governance (ESG) Data

France

iso2Code: FR

value: Europe & Central Asia

value: High income

capitalCity: Paris

country_code: FRA

country_name: France

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.


Tree Cover Loss (hectares)

Micronesia, Fed. Sts.

iso2Code: FM

iso2code: XN

value: Lower middle income

value: IDA

capitalCity: Palikir

country_code: FSM

country_name: Micronesia, Fed. Sts.

value: CC BY-4.0

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.


Gabon

iso2Code: GA

iso2code: ZG

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

iso2code: XF

value: IBRD

capitalCity: Libreville

country_code: GAB

country_name: Gabon

value: Weighted average

value: Annual

value: Hectares

value: Identifies areas of gross tree cover loss.

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

United Kingdom

iso2Code: GB

value: Not classified

capitalCity: London

country_code: GBR

country_name: United Kingdom

value: Tree Cover Loss

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).


Georgia

iso2Code: GE

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

value: Upper middle income

capitalCity: Tbilisi

country_code: GEO

country_name: Georgia

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.


Tree Cover Loss (hectares)

Ghana

iso2Code: GH

iso2code: ZF

value: Lower middle income

value: IDA

capitalCity: Accra

country_code: GHA

country_name: Ghana

value: CC BY-4.0

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.


Guinea

iso2Code: GN

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

capitalCity: Conakry

country_code: GIN

country_name: Guinea

value: Weighted average

value: Annual


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Gambia, The

iso2Code: GM

iso2code: XM

value: Low income

iso2code: XI

capitalCity: Banjul

country_code: GMB

country_name: Gambia, The

value: Hectares

value: Identifies areas of gross tree cover loss.

value: Environment: Natural capital endowment and management


Guinea-Bissau

iso2Code: GW

capitalCity: Bissau

country_code: GNB

country_name: Guinea-Bissau

value: Tree Cover Loss

value: Global Forest Watch. Tree Cover Loss (Hansen/UMD/Google/USGS/NASA).


Tree Cover Loss (hectares)

Equatorial Guinea

iso2Code: GQ

iso2code: XT

value: Upper middle income

value: IBRD

capitalCity: Malabo

country_code: GNQ

country_name: Equatorial Guinea

value: In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height. It includes natural forests, but may also include plantations. Tree cover loss includes deforestation (the conversion of natural forest to other land uses) but also timber harvesting, fire, disease, or storm damage. Tree cover loss does not equate to deforestation.


Greece

iso2Code: GR

value: Europe & Central Asia

iso2code: XD

value: High income

iso2code: XX

value: Not classified

capitalCity: Athens

country_code: GRC

country_name: Greece

value: CC BY-4.0


Tree Cover Loss (hectares)

Grenada

iso2Code: GD

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

iso2code: XH

value: Blend

capitalCity: Saint George's

country_code: GRD

country_name: Grenada

value: Administrative boundaries: Global Administrative Areas database (GADM), version 3.6.

value: Shows year-by-year tree cover loss, defined as stand level replacement of vegetation greater than 5 meters, within the selected area. The tree cover loss data set is a collaboration of the University of Maryland, Google, USGS, and NASA, and uses Landsat satellite images to map annual tree cover loss at a 30 × 30 meter resolution. Note that “tree cover loss” is not the same as “deforestation” – tree cover loss includes change in both natural and planted forest, and does not need to be human caused. The data from 2011 onward were produced with an updated methodology that may capture additional loss. Comparisons between the original 2001-2010 data and future years should be performed with caution.