value: Environment, Social and Governance (ESG) Data

Guatemala

iso2Code: GT

iso2code: XF

capitalCity: Guatemala City

country_code: GTM

country_name: Guatemala

value: Weighted average

value: Annual

value: Hectares


Tree Cover Loss (hectares)

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.

Guyana

iso2Code: GY

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XD

value: High income

iso2code: XI

value: IDA

capitalCity: Georgetown

country_code: GUY

country_name: Guyana

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: 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

schema: wb


High income

value: Aggregates

country_code: HIC

country_name: High income

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)

Honduras

iso2Code: HN

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

iso2code: XN

value: Lower middle income

capitalCity: Tegucigalpa

country_code: HND

country_name: Honduras


value: Environment, Social and Governance (ESG) Data

Heavily indebted poor countries (HIPC)

iso2Code: XE

country_code: HPC

country_name: Heavily indebted poor countries (HIPC)

value: Weighted average


Tree Cover Loss (hectares)

Croatia

iso2Code: HR

value: Europe & Central Asia

value: IBRD

capitalCity: Zagreb

country_code: HRV

country_name: Croatia

value: Annual

value: Hectares


Haiti

iso2Code: HT

value: Latin America & Caribbean

value: IDA

capitalCity: Port-au-Prince

country_code: HTI

country_name: Haiti

value: Tree Cover Loss


Tree Cover Loss (hectares)

Hungary

iso2Code: HU

value: High income

iso2code: XX

value: Not classified

capitalCity: Budapest

country_code: HUN

country_name: Hungary

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.


IBRD only

value: Aggregates

country_code: IBD

country_name: IBRD only

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: 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)

value: Environment, Social and Governance (ESG) Data

IDA & IBRD total

iso2Code: ZT

country_code: IBT

country_name: IDA & IBRD total

value: Weighted average


IDA total

iso2Code: XG

country_code: IDA

country_name: IDA total

value: Annual


Tree Cover Loss (hectares)

IDA blend

iso2Code: XH

country_code: IDB

country_name: IDA blend

value: Hectares


Indonesia

iso2Code: ID

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XT

value: Upper middle income

value: IBRD

capitalCity: Jakarta

country_code: IDN

country_name: Indonesia


Tree Cover Loss (hectares)

country_code: IDX

country_name: IDA only

value: Tree Cover Loss


India

iso2Code: IN

value: South Asia

value: Lower middle income

iso2code: XF

capitalCity: New Delhi

country_code: IND

country_name: India

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)

Ireland

iso2Code: IE

value: Europe & Central Asia

iso2code: XD

value: High income

value: Not classified

capitalCity: Dublin

country_code: IRL

country_name: Ireland

value: CC BY-4.0

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


value: Environment, Social and Governance (ESG) Data

Iran, Islamic Rep.

iso2Code: IR

iso2code: ZQ

value: Middle East & North Africa

iso2code: XQ

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

capitalCity: Tehran

country_code: IRN

country_name: Iran, Islamic 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.

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)

Iraq

iso2Code: IQ

value: Upper middle income

value: IBRD

capitalCity: Baghdad

country_code: IRQ

country_name: Iraq

value: Weighted average

value: Annual

value: Hectares


Iceland

iso2Code: IS

value: Europe & Central Asia

capitalCity: Reykjavik

country_code: ISL

country_name: Iceland

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.


Tree Cover Loss (hectares)

Israel

iso2Code: IL

value: High income

value: Not classified

country_code: ISR

country_name: Israel

value: CC BY-4.0


value: Environment, Social and Governance (ESG) Data

Italy

iso2Code: IT

capitalCity: Rome

country_code: ITA

country_name: Italy

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


Tree Cover Loss (hectares)

Jamaica

iso2Code: JM

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

capitalCity: Kingston

country_code: JAM

country_name: Jamaica

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.


Jordan

iso2Code: JO

value: Middle East & North Africa

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

iso2code: XN

value: Lower middle income

capitalCity: Amman

country_code: JOR

country_name: Jordan

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)

Japan

iso2Code: JP

value: East Asia & Pacific

iso2code: XX

capitalCity: Tokyo

country_code: JPN

country_name: Japan

value: Weighted average

value: Annual

value: Hectares


Kazakhstan

iso2Code: KZ

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

iso2code: XT

value: Upper middle income

iso2code: XF

value: IBRD

capitalCity: Astana

country_code: KAZ

country_name: Kazakhstan

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.


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Kenya

iso2Code: KE

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

iso2code: XH

value: Blend

capitalCity: Nairobi

country_code: KEN

country_name: Kenya

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.


Kyrgyz Republic

iso2Code: KG

value: Lower middle income

iso2code: XI

value: IDA

capitalCity: Bishkek

country_code: KGZ

country_name: Kyrgyz Republic

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)

Cambodia

iso2Code: KH

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

capitalCity: Phnom Penh

country_code: KHM

country_name: Cambodia

value: Weighted average

value: Annual

value: Hectares


value: Environment, Social and Governance (ESG) Data

Kiribati

iso2Code: KI

capitalCity: Tarawa

country_code: KIR

country_name: Kiribati

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.


Tree Cover Loss (hectares)

St. Kitts and Nevis

iso2Code: KN

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XD

value: High income

value: IBRD

capitalCity: Basseterre

country_code: KNA

country_name: St. Kitts and Nevis


Korea, Rep.

iso2Code: KR

value: Not classified

capitalCity: Seoul

country_code: KOR

country_name: Korea, Rep.

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.


Tree Cover Loss (hectares)

Kuwait

iso2Code: KW

iso2code: ZQ

value: Middle East & North Africa

capitalCity: Kuwait City

country_code: KWT

country_name: Kuwait

value: Identifies areas of gross tree cover loss.

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


iso2Code: XJ

name: Latin America & Caribbean (excluding high income)

value: Aggregates

country_code: LAC

value: Environment: Natural capital endowment and management


Lao PDR

iso2Code: LA

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XN

value: Lower middle income

value: IDA

capitalCity: Vientiane

country_code: LAO

country_name: Lao PDR

value: Weighted average

value: Annual


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Lebanon

iso2Code: LB

iso2code: XQ

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

iso2code: XF

capitalCity: Beirut

country_code: LBN

country_name: Lebanon

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: Hectares


Liberia

iso2Code: LR

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

iso2code: XM

value: Low income

capitalCity: Monrovia

country_code: LBR

country_name: Liberia

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.


Tree Cover Loss (hectares)

Libya

iso2Code: LY

value: Middle East & North Africa

iso2code: XT

value: Upper middle income

value: IBRD

capitalCity: Tripoli

country_code: LBY

country_name: Libya

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

St. Lucia

iso2Code: LC

iso2code: ZJ

value: Latin America & Caribbean

value: Latin America & Caribbean (excluding high income)

iso2code: XH

value: Blend

capitalCity: Castries

country_code: LCA

country_name: St. Lucia

value: Weighted average

value: Annual


Tree Cover Loss (hectares)

Latin America & Caribbean

value: Aggregates

country_code: LCN

country_name: Latin America & Caribbean

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: Hectares


iso2Code: XL

name: Least developed countries: UN classification

country_code: LDC

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.


country_code: LIC

country_name: Low income


Liechtenstein

iso2Code: LI

value: Europe & Central Asia

iso2code: XD

value: High income

iso2code: XX

value: Not classified

capitalCity: Vaduz

country_code: LIE

country_name: Liechtenstein


Tree Cover Loss (hectares)

Sri Lanka

iso2Code: LK

value: South Asia

iso2code: XN

value: Lower middle income

iso2code: XI

value: IDA

capitalCity: Colombo

country_code: LKA

country_name: Sri Lanka

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

country_code: LMC

country_name: Lower middle income

value: Weighted average

value: Annual


Low & middle income

iso2Code: XO

value: Aggregates

country_code: LMY

country_name: Low & middle income

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.


Tree Cover Loss (hectares)

Lesotho

iso2Code: LS

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

capitalCity: Maseru

country_code: LSO

country_name: Lesotho

value: CC BY-4.0

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

value: Hectares


country_code: LTE

country_name: Late-demographic dividend

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.


Lithuania

iso2Code: LT

value: Europe & Central Asia

value: High income

value: Not classified

capitalCity: Vilnius

country_code: LTU

country_name: Lithuania


Tree Cover Loss (hectares)

Luxembourg

iso2Code: LU

capitalCity: Luxembourg

country_code: LUX

country_name: Luxembourg

value: Identifies areas of gross tree cover loss.

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


value: Environment, Social and Governance (ESG) Data

Latvia

iso2Code: LV

capitalCity: Riga

country_code: LVA

country_name: Latvia

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

Morocco

iso2Code: MA

iso2code: ZQ

value: Middle East & North Africa

iso2code: XQ

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

value: Lower middle income

iso2code: XF

value: IBRD

capitalCity: Rabat

country_code: MAR

country_name: Morocco

value: Weighted average

value: Annual


Monaco

iso2Code: MC

capitalCity: Monaco

country_code: MCO

country_name: Monaco

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)

Moldova

iso2Code: MD

value: Europe & Central Asia (excluding high income)

iso2code: XT

value: Upper middle income

capitalCity: Chisinau

country_code: MDA

country_name: Moldova

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

value: Hectares

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.


Madagascar

iso2Code: MG

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

iso2code: XM

value: Low income

value: IDA

capitalCity: Antananarivo

country_code: MDG

country_name: Madagascar

value: Identifies areas of gross tree cover loss.

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


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Maldives

iso2Code: MV

value: South Asia

iso2code: XI

capitalCity: Male

country_code: MDV

country_name: Maldives

value: Environment: Natural capital endowment and management


Middle East & North Africa

value: Aggregates

country_code: MEA

country_name: Middle East & North Africa

value: Weighted average

value: Tree Cover Loss

value: Annual


Tree Cover Loss (hectares)

Mexico

iso2Code: MX

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

value: Upper middle income

value: IBRD

capitalCity: Mexico City

country_code: MEX

country_name: Mexico

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


Marshall Islands

iso2Code: MH

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

capitalCity: Majuro

country_code: MHL

country_name: Marshall Islands

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

value: Hectares

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)

value: Environment, Social and Governance (ESG) Data

Middle income

iso2Code: XP

country_code: MIC

country_name: Middle income

value: Identifies areas of gross tree cover loss.

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


North Macedonia

iso2Code: MK

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

capitalCity: Skopje

country_code: MKD

country_name: North Macedonia

value: Weighted average

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

Mali

iso2Code: ML

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

value: Low income

value: IDA

capitalCity: Bamako

country_code: MLI

country_name: Mali

value: Tree Cover Loss

value: Annual


Malta

iso2Code: MT

iso2code: ZQ

value: Middle East & North Africa

iso2code: XD

value: High income

iso2code: XX

value: Not classified

capitalCity: Valletta

country_code: MLT

country_name: Malta

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

Myanmar

iso2Code: MM

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XN

value: Lower middle income

capitalCity: Naypyidaw

country_code: MMR

country_name: Myanmar

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

value: Hectares

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: Identifies areas of gross tree cover loss.


iso2Code: XQ

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

value: Aggregates

country_code: MNA

value: Weighted average

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

value: Environment: Natural capital endowment and management


Montenegro

iso2Code: ME

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

iso2code: XT

value: Upper middle income

iso2code: XF

value: IBRD

capitalCity: Podgorica

country_code: MNE

country_name: Montenegro

value: Tree Cover Loss

value: Annual


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Mongolia

iso2Code: MN

value: East Asia & Pacific

capitalCity: Ulaanbaatar

country_code: MNG

country_name: Mongolia

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


Mozambique

iso2Code: MZ

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: Maputo

country_code: MOZ

country_name: Mozambique

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

value: Hectares


Tree Cover Loss (hectares)

Mauritania

iso2Code: MR

value: Lower middle income

capitalCity: Nouakchott

country_code: MRT

country_name: Mauritania

value: Weighted average

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: 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


Mauritius

iso2Code: MU

value: Upper middle income

value: IBRD

capitalCity: Port Louis

country_code: MUS

country_name: Mauritius

value: Tree Cover Loss

value: Annual


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Malawi

iso2Code: MW

capitalCity: Lilongwe

country_code: MWI

country_name: Malawi

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


Malaysia

iso2Code: MY

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

capitalCity: Kuala Lumpur

country_code: MYS

country_name: Malaysia


Tree Cover Loss (hectares)

North America

iso2Code: XU

value: Aggregates

country_code: NAC

country_name: North America

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


Namibia

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

capitalCity: Windhoek

country_code: NAM

country_name: Namibia

value: Hectares


Tree Cover Loss (hectares)

Niger

iso2Code: NE

value: Low income

value: IDA

capitalCity: Niamey

country_code: NER

country_name: Niger

value: Weighted average

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: Identifies areas of gross tree cover loss.


Nigeria

iso2Code: NG

iso2code: XN

value: Lower middle income

iso2code: XH

value: Blend

capitalCity: Abuja

country_code: NGA

country_name: Nigeria

value: 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)

value: Environment, Social and Governance (ESG) Data

Nicaragua

iso2Code: NI

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

capitalCity: Managua

country_code: NIC

country_name: Nicaragua

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: Annual


Netherlands

iso2Code: NL

value: Europe & Central Asia

iso2code: XD

value: High income

iso2code: XX

value: Not classified

capitalCity: Amsterdam

country_code: NLD

country_name: Netherlands

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

value: Hectares


Tree Cover Loss (hectares)

Norway

iso2Code: NO

capitalCity: Oslo

country_code: NOR

country_name: Norway

value: Weighted average

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: Identifies areas of gross tree cover loss.


Nepal

iso2Code: NP

value: South Asia

value: Lower middle income

iso2code: XI

value: IDA

capitalCity: Kathmandu

country_code: NPL

country_name: Nepal

value: Tree Cover Loss


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Nauru

iso2Code: NR

value: East Asia & Pacific

iso2code: XF

value: IBRD

capitalCity: Yaren District

country_code: NRU

country_name: Nauru

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

value: Environment: Natural capital endowment and management


New Zealand

iso2Code: NZ

capitalCity: Wellington

country_code: NZL

country_name: New Zealand

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: Annual


Tree Cover Loss (hectares)

OECD members

iso2Code: OE

value: Aggregates

country_code: OED

country_name: OECD members

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


Oman

iso2Code: OM

iso2code: ZQ

value: Middle East & North Africa

value: High income

value: Not classified

capitalCity: Muscat

country_code: OMN

country_name: Oman

value: Weighted average

value: Hectares


Tree Cover Loss (hectares)

country_code: OSS

country_name: Other small states

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: Identifies areas of gross tree cover loss.


value: Environment, Social and Governance (ESG) Data

Pakistan

iso2Code: PK

value: South Asia

iso2code: XN

value: Lower middle income

value: Blend

capitalCity: Islamabad

country_code: PAK

country_name: Pakistan

value: Tree Cover Loss


Tree Cover Loss (hectares)

Panama

iso2Code: PA

value: Latin America & Caribbean

value: IBRD

capitalCity: Panama City

country_code: PAN

country_name: Panama

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

value: Environment: Natural capital endowment and management


Peru

iso2Code: PE

iso2code: ZJ

value: Latin America & Caribbean (excluding high income)

iso2code: XT

value: Upper middle income

capitalCity: Lima

country_code: PER

country_name: Peru

value: CC BY-4.0

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

value: Annual


Tree Cover Loss (hectares)

Philippines

iso2Code: PH

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

capitalCity: Manila

country_code: PHL

country_name: Philippines

value: Weighted average

value: Hectares

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

Palau

iso2Code: PW

capitalCity: Koror

country_code: PLW

country_name: Palau

value: Identifies areas of gross tree cover loss.


Tree Cover Loss (hectares)

Papua New Guinea

iso2Code: PG

value: Lower middle income

iso2code: XH

value: Blend

capitalCity: Port Moresby

country_code: PNG

country_name: Papua New Guinea

value: Tree Cover Loss


Poland

iso2Code: PL

value: Europe & Central Asia

iso2code: XD

value: High income

value: IBRD

capitalCity: Warsaw

country_code: POL

country_name: Poland

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


Tree Cover Loss (hectares)

Pre-demographic dividend

value: Aggregates

country_code: PRE

country_name: Pre-demographic dividend

value: CC BY-4.0

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

value: Environment: Natural capital endowment and management


Korea, Dem. People's Rep.

iso2Code: KP

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

iso2code: XM

value: Low income

iso2code: XX

value: Not classified

capitalCity: Pyongyang

country_code: PRK

country_name: Korea, Dem. People's Rep.

value: Weighted average

value: Annual


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Portugal

iso2Code: PT

capitalCity: Lisbon

country_code: PRT

country_name: Portugal

value: Hectares

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: Identifies areas of gross tree cover loss.


Paraguay

iso2Code: PY

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

value: Upper middle income

iso2code: XF

value: IBRD

capitalCity: Asuncion

country_code: PRY

country_name: Paraguay

value: Tree Cover Loss


Tree Cover Loss (hectares)

Pacific island small states

value: Aggregates

country_code: PSS

country_name: Pacific island 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.

value: CC BY-4.0

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

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


country_code: PST

country_name: Post-demographic dividend

value: Environment: Natural capital endowment and management


Qatar

iso2Code: QA

iso2code: ZQ

value: Middle East & North Africa

value: High income

value: Not classified

capitalCity: Doha

country_code: QAT

country_name: Qatar

value: Weighted average


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Romania

iso2Code: RO

value: Europe & Central Asia

capitalCity: Bucharest

country_code: ROU

country_name: Romania

value: Annual

value: Hectares

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.


Russian Federation

iso2Code: RU

value: Europe & Central Asia (excluding high income)

iso2code: XT

value: Upper middle income

value: IBRD

capitalCity: Moscow

country_code: RUS

country_name: Russian Federation

value: Identifies areas of gross tree cover loss.


Tree Cover Loss (hectares)

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: 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


South Asia

value: Aggregates

country_code: SAS

country_name: South Asia

value: Weighted average

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

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

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Saudi Arabia

iso2Code: SA

value: Middle East & North Africa

iso2code: XD

value: High income

value: Not classified

capitalCity: Riyadh

country_code: SAU

country_name: Saudi Arabia

value: Annual

value: Hectares

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.


Sudan

iso2Code: SD

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

iso2code: XM

value: Low income

capitalCity: Khartoum

country_code: SDN

country_name: Sudan

value: Identifies areas of gross tree cover loss.


Tree Cover Loss (hectares)

Senegal

iso2Code: SN

iso2code: XN

value: Lower middle income

value: IDA

capitalCity: Dakar

country_code: SEN

country_name: Senegal

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


Singapore

iso2Code: SG

value: East Asia & Pacific

iso2code: XX

capitalCity: Singapore

country_code: SGP

country_name: Singapore

value: Weighted average

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

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

value: Environment: Natural capital endowment and management


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Solomon Islands

iso2Code: SB

value: East Asia & Pacific (excluding high income)

capitalCity: Honiara

country_code: SLB

country_name: Solomon Islands

value: Annual


Sierra Leone

iso2Code: SL

value: Sub-Saharan Africa

capitalCity: Freetown

country_code: SLE

country_name: Sierra Leone

value: Hectares

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)

El Salvador

iso2Code: SV

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

value: Upper middle income

iso2code: XF

value: IBRD

capitalCity: San Salvador

country_code: SLV

country_name: El Salvador

value: Identifies areas of gross tree cover loss.


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: 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

Somalia

iso2Code: SO

iso2code: ZG

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

value: Low income

value: IDA

capitalCity: Mogadishu

country_code: SOM

country_name: Somalia

value: Weighted average

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

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

value: Environment: Natural capital endowment and management


Serbia

iso2Code: RS

value: Europe & Central Asia (excluding high income)

iso2code: XT

value: Upper middle income

capitalCity: Belgrade

country_code: SRB

country_name: Serbia

value: Annual

value: Hectares

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)

name: Sub-Saharan Africa (excluding high income)

value: Aggregates

country_code: SSA

value: Identifies areas of gross tree cover loss.


South Sudan

iso2Code: SS

value: Sub-Saharan Africa

iso2code: XM

iso2code: XI

capitalCity: Juba

country_code: SSD

country_name: South Sudan

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.


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

country_code: SSF

country_name: Sub-Saharan Africa

value: CC BY-4.0


country_code: SST

country_name: Small states


Sao Tome and Principe

iso2Code: ST

value: Sub-Saharan Africa (excluding high income)

iso2code: XN

value: Lower middle income

value: IDA

capitalCity: Sao Tome

country_code: STP

country_name: São Tomé and Principe


Tree Cover Loss (hectares)

Suriname

iso2Code: SR

value: Latin America & Caribbean

value: Latin America & Caribbean (excluding high income)

value: IBRD

capitalCity: Paramaribo

country_code: SUR

country_name: Suriname

value: Weighted average

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

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


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: Annual

value: Hectares

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

Slovenia

iso2Code: SI

capitalCity: Ljubljana

country_code: SVN

country_name: Slovenia

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: Identifies areas of gross tree cover loss.


Sweden

iso2Code: SE

capitalCity: Stockholm

country_code: SWE

country_name: Sweden


Tree Cover Loss (hectares)

Eswatini

iso2Code: SZ

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

value: Lower middle income

iso2code: XF

capitalCity: Mbabane

country_code: SWZ

country_name: Eswatini


Seychelles

iso2Code: SC

iso2code: ZG

value: IBRD

capitalCity: Victoria

country_code: SYC

country_name: Seychelles

value: Weighted average

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


Tree Cover Loss (hectares)

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

value: IDA

capitalCity: Damascus

country_code: SYR

country_name: Syrian Arab Republic

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


Chad

iso2Code: TD

iso2code: ZF

iso2code: XM

capitalCity: N'Djamena

country_code: TCD

country_name: Chad

value: Annual

value: Hectares

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

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

value: Aggregates

country_code: TEA

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


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

country_code: TEC

value: Identifies areas of gross tree cover loss.


Togo

iso2Code: TG

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

iso2code: XI

capitalCity: Lome

country_code: TGO

country_name: Togo

value: Weighted average


Tree Cover Loss (hectares)

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


Tajikistan

iso2Code: TJ

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

iso2code: XN

value: Lower middle income

value: IDA

capitalCity: Dushanbe

country_code: TJK

country_name: Tajikistan

value: Annual

value: Hectares

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


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Turkmenistan

iso2Code: TM

capitalCity: Ashgabat

country_code: TKM

country_name: Turkmenistan

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: 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


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

value: Aggregates

country_code: TLA

value: Weighted average

value: Identifies areas of gross tree cover loss.


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


Tree Cover Loss (hectares)

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

country_code: TMN


Tonga

iso2Code: TO

value: Upper middle income

value: IDA

capitalCity: Nuku'alofa

country_code: TON

country_name: Tonga


Tree Cover Loss (hectares)

country_code: TSA

country_name: South Asia (IDA & IBRD)

value: Annual

value: Hectares


value: Environment, Social and Governance (ESG) Data

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

country_code: TSS

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


Trinidad and Tobago

iso2Code: TT

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XD

value: High income

iso2code: XF

value: IBRD

capitalCity: Port-of-Spain

country_code: TTO

country_name: Trinidad and Tobago

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.


Tree Cover Loss (hectares)

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: Weighted average

value: CC BY-4.0

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


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

value: Identifies areas of gross tree cover loss.


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

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: Annual

value: Hectares

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


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: 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.


Tree Cover Loss (hectares)

Uganda

iso2Code: UG

iso2code: XM

value: Low income

capitalCity: Kampala

country_code: UGA

country_name: Uganda

value: Weighted average

value: CC BY-4.0

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

Ukraine

iso2Code: UA

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

iso2code: XN

value: IBRD

capitalCity: Kiev

country_code: UKR

country_name: Ukraine

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

value: Identifies areas of gross tree cover loss.


Tree Cover Loss (hectares)

Upper middle income

iso2Code: XT

value: Aggregates

country_code: UMC

country_name: Upper middle income

value: Annual

value: Hectares

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


Uruguay

iso2Code: UY

iso2code: ZJ

value: Latin America & Caribbean

value: High income

capitalCity: Montevideo

country_code: URY

country_name: Uruguay

value: Tree Cover Loss


Tree Cover Loss (hectares)

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: Weighted average

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

Uzbekistan

iso2Code: UZ

value: Lower middle income

iso2code: XH

value: Blend

capitalCity: Tashkent

country_code: UZB

country_name: Uzbekistan

value: CC BY-4.0

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)

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

value: Identifies areas of gross tree cover loss.


Venezuela, RB

iso2Code: VE

value: Latin America & Caribbean

iso2code: XY

iso2code: XF

value: IBRD

capitalCity: Caracas

country_code: VEN

country_name: Venezuela, RB

value: Annual

value: Hectares

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


Tree Cover Loss (hectares)

Viet Nam

iso2Code: VN

value: East Asia & Pacific

value: East Asia & Pacific (excluding high income)

capitalCity: Hanoi

country_code: VNM

country_name: Vietnam

value: Weighted average

value: Tree Cover Loss


value: Environment, Social and Governance (ESG) Data

Vanuatu

iso2Code: VU

value: Lower middle income

iso2code: XI

value: IDA

capitalCity: Port-Vila

country_code: VUT

country_name: Vanuatu

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)

World

value: Aggregates

country_code: WLD

country_name: World

value: CC BY-4.0

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


Samoa

iso2Code: WS

iso2code: XN

capitalCity: Apia

country_code: WSM

country_name: Samoa

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

value: Identifies areas of gross tree cover loss.


Tree Cover Loss (hectares)

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: Annual


South Africa

iso2Code: ZA

iso2code: ZG

value: Sub-Saharan Africa

iso2code: ZF

value: Sub-Saharan Africa (excluding high income)

iso2code: XT

value: Upper middle income

value: IBRD

capitalCity: Pretoria

country_code: ZAF

country_name: South Africa

value: Hectares

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


Tree Cover Loss (hectares)

value: Environment, Social and Governance (ESG) Data

Zambia

iso2Code: ZM

value: Lower middle income

value: IDA

capitalCity: Lusaka

country_code: ZMB

country_name: Zambia

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.


Zimbabwe

iso2Code: ZW

iso2code: XH

value: Blend

capitalCity: Harare

country_code: ZWE

country_name: Zimbabwe

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: Identifies areas of gross tree cover loss.

value: Environment: Natural capital endowment and management


Forest area (hectares)

value: Africa Development Indicators

sourceNone: Forest area is land under natural or planted stands of trees of at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural production systems (for example, in fruit plantations and agroforestry systems) and trees in urban parks and gardens.

Africa

value: Aggregates

country_code: AFR

country_name: Africa

value: Sum

value: Forest area (ha)

value: Annual

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

value: Environment: Land use


Angola

iso2Code: AO

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

value: Lower middle income

iso2code: XF

value: IBRD

capitalCity: Luanda

country_code: AGO

country_name: Angola

value: Forest area is land under natural or planted stands of trees of at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural production systems (for example, in fruit plantations and agroforestry systems) and trees in urban parks and gardens.


Forest area (hectares)

Burundi

iso2Code: BI

value: Low income

value: IDA

capitalCity: Bujumbura

country_code: BDI

country_name: Burundi


Benin

iso2Code: BJ

iso2code: XI

capitalCity: Porto-Novo

country_code: BEN

country_name: Benin


Forest area (hectares)

Burkina Faso

iso2Code: BF

capitalCity: Ouagadougou

country_code: BFA

country_name: Burkina Faso


Botswana

iso2Code: BW

value: Upper middle income

capitalCity: Gaborone

country_code: BWA

country_name: Botswana


Forest area (hectares)

Central African Republic

iso2Code: CF

capitalCity: Bangui

country_code: CAF

country_name: Central African Republic


Cote d'Ivoire

iso2Code: CI

iso2code: XN

capitalCity: Yamoussoukro

country_code: CIV

country_name: Côte d'Ivoire


Forest area (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.


Forest area (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


Forest area (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)

capitalCity: Djibouti

country_code: DJI

country_name: Djibouti


Forest area (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


Forest area (hectares)

Eritrea

iso2Code: ER

iso2code: XI

capitalCity: Asmara

country_code: ERI

country_name: Eritrea

value: Forest area (ha)


Ethiopia

iso2Code: ET

capitalCity: Addis Ababa

country_code: ETH

country_name: Ethiopia

value: Annual


Forest area (hectares)

Gabon

iso2Code: GA

iso2code: XT

capitalCity: Libreville

country_code: GAB

country_name: Gabon

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


Ghana

iso2Code: GH

iso2code: ZG

iso2code: XN

capitalCity: Accra

country_code: GHA

country_name: Ghana

value: Environment: Land use


Forest area (hectares)

Guinea

iso2Code: GN

value: Sub-Saharan Africa

iso2code: ZF

capitalCity: Conakry

country_code: GIN

country_name: Guinea


Gambia, The

iso2Code: GM

value: Sub-Saharan Africa (excluding high income)

iso2code: XM

capitalCity: Banjul

country_code: GMB

country_name: Gambia, The


Forest area (hectares)

Guinea-Bissau

iso2Code: GW

capitalCity: Bissau

country_code: GNB

country_name: Guinea-Bissau


Equatorial Guinea

iso2Code: GQ

capitalCity: Malabo

country_code: GNQ

country_name: Equatorial Guinea


Forest area (hectares)

Kenya

iso2Code: KE

value: Lower middle income

iso2code: XH

capitalCity: Nairobi

country_code: KEN

country_name: Kenya


Liberia

iso2Code: LR

capitalCity: Monrovia

country_code: LBR

country_name: Liberia


Forest area (hectares)

Libya

iso2Code: LY

iso2code: ZQ

iso2code: XQ

iso2code: XF

value: IBRD

capitalCity: Tripoli

country_code: LBY

country_name: Libya


Lesotho

iso2Code: LS

iso2code: XI

capitalCity: Maseru

country_code: LSO

country_name: Lesotho

value: Forest area is land under natural or planted stands of trees of at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural production systems (for example, in fruit plantations and agroforestry systems) and trees in urban parks and gardens.


Forest area (hectares)

Morocco

iso2Code: MA

capitalCity: Rabat

country_code: MAR

country_name: Morocco


Madagascar

iso2Code: MG

iso2code: ZG

value: Low income

capitalCity: Antananarivo

country_code: MDG

country_name: Madagascar


Forest area (hectares)

Mali

iso2Code: ML

iso2code: ZF

value: IDA

capitalCity: Bamako

country_code: MLI

country_name: Mali


Mozambique

iso2Code: MZ

iso2code: XM

capitalCity: Maputo

country_code: MOZ

country_name: Mozambique


Forest area (hectares)

Mauritania

iso2Code: MR

iso2code: XN

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


Forest area (hectares)

Malawi

iso2Code: MW

capitalCity: Lilongwe

country_code: MWI

country_name: Malawi


North Africa

value: Aggregates

country_code: NAF

country_name: North Africa


Forest area (hectares)

Namibia

capitalCity: Windhoek

country_code: NAM

country_name: Namibia


Niger

iso2Code: NE

capitalCity: Niamey

country_code: NER

country_name: Niger


Forest area (hectares)

Nigeria

iso2Code: NG

iso2code: XH

value: Blend

capitalCity: Abuja

country_code: NGA

country_name: Nigeria


Rwanda

iso2Code: RW

capitalCity: Kigali

country_code: RWA

country_name: Rwanda


Forest area (hectares)

Sudan

iso2Code: SD

iso2code: XI

capitalCity: Khartoum

country_code: SDN

country_name: Sudan


Senegal

iso2Code: SN

capitalCity: Dakar

country_code: SEN

country_name: Senegal


Forest area (hectares)

Sierra Leone

iso2Code: SL

iso2code: ZG

capitalCity: Freetown

country_code: SLE

country_name: Sierra Leone


Somalia

iso2Code: SO

iso2code: ZF

capitalCity: Mogadishu

country_code: SOM

country_name: Somalia


Forest area (hectares)

country_code: SSA

country_name: Sub-Saharan Africa (excluding high income)


South Sudan

iso2Code: SS

iso2code: XM

capitalCity: Juba

country_code: SSD

country_name: South Sudan


Forest area (hectares)

country_code: SSF

country_name: Sub-Saharan Africa


Sao Tome and Principe

iso2Code: ST

iso2code: XN

capitalCity: Sao Tome

country_code: STP

country_name: São Tomé and Principe


Forest area (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


Forest area (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


Forest area (hectares)

Tunisia

iso2Code: TN

iso2code: ZQ

value: Middle East & North Africa

iso2code: XQ

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

capitalCity: Tunis

country_code: TUN

country_name: Tunisia

value: Forest area (ha)


Tanzania

iso2Code: TZ

iso2code: XI

capitalCity: Dodoma

country_code: TZA

country_name: Tanzania

value: Annual

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

value: Environment: Land use


Forest area (hectares)

Uganda

iso2Code: UG

iso2code: ZG

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

capitalCity: Kampala

country_code: UGA

country_name: Uganda


name: Sub-Saharan Africa excluding South Africa and Nigeria

country_code: XZN

value: Forest area is land under natural or planted stands of trees of at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural production systems (for example, in fruit plantations and agroforestry systems) and trees in urban parks and gardens.


South Africa

iso2Code: ZA

iso2code: ZF

iso2code: XT

value: IBRD

capitalCity: Pretoria

country_code: ZAF

country_name: South Africa


Forest area (hectares)

Zambia

iso2Code: ZM

iso2code: XN

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


Forest area (sq. km)

value: World Development Indicators

value: Agriculture & Rural Development

value: Climate Change

value: Environment

Aruba

iso2Code: AW

iso2code: ZJ

value: Latin America & Caribbean

iso2code: XD

iso2code: XX

value: Not classified

capitalCity: Oranjestad

country_code: ABW

country_name: Aruba

value: Forest area (sq. km)

value: CC BY-4.0

value:
As threats to biodiversity mount, the international community is increasingly focusing on conserving diversity. Deforestation is a major cause of loss of biodiversity, and habitat conservation is vital for stemming this loss. Conservation efforts have focused on protecting areas of high biodiversity.

On a global average, more than one-third of all forest is primary forest, i.e. forest of native species where there are no clearly visible indications of human activities and the ecological processes have not been significantly disturbed. Primary forests, in particular tropical moist forests, include the most species-rich, diverse terrestrial ecosystems. The decrease of primary forest area, 0.4 percent over a ten-year period, is largely due to reclassification of primary forest to "other naturally regenerated forest" because of selective logging and other human interventions.

National parks, game reserves, wilderness areas and other legally established protected areas cover more than 10 percent of the total forest area in most countries and regions. FAO estimates that around 10 million people are employed in forest management and conservation - but many more are directly dependent on forests for their livelihoods. Also, 80 about percent of the world's forests are publicly owned, but ownership and management of forests by communities, individuals and private companies is on the rise.

Close to 1.2 billion hectares of forest are managed primarily for the production of wood and non-wood forest products. An additional 25 percent of forest area is designated for multiple uses - in most cases including the production of wood and non-wood forest products. The area designated primarily for productive purposes has decreased by more than 50 million hectares since 1990 as forests have been designated for other purposes.

value: The world and regional aggregate series do not include data from countries that no longer exist.

value:
The Food and Agricultural Organization (FAO) has been collecting and analyzing data on forest area since 1946. This is done at intervals of 5-10 years as part of the Global Forest Resources Assessment (FRA). FAO reports data for 229 countries and territories; for the remaining 56 small island states and territories where no information is provided, a report is prepared by FAO using existing information and a literature search. The data are aggregated at sub-regional, regional and global levels by the FRA team at FAO, and estimates are produced by straight summation.

The lag between the reference year and the actual production of data series as well as the frequency of data production varies between countries. Deforested areas do not include areas logged but intended for regeneration or areas degraded by fuelwood gathering, acid precipitation, or forest fires. Negative numbers indicate an increase in forest area.

Data includes areas with bamboo and palms; forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific scientific, historical, cultural or spiritual interest; windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters; plantations primarily used for forestry or protective purposes, such as rubber-wood plantations and cork oak stands. Data excludes tree stands in agricultural production systems, such as fruit plantations and agroforestry systems. Forest area also excludes trees in urban parks and gardens. The proportion of forest area to total land area is calculated and changes in the proportion are computed to identify trends.

value:
Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should reach a minimum height of 5 meters in situ. Areas under reforestation that have not yet reached but are expected to reach a canopy cover of 10 percent and a tree height of 5 meters are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, which are expected to regenerate.

FAO provides detail information on forest cover, and adjusted estimates of forest cover. The current survey uses a uniform definition of forest. Although FAO provides a breakdown of forest cover between natural forest and plantation for developing countries, this indictor data does not reflect that breakdown. Thus the deforestation data may underestimate the rate at which natural forest is disappearing in some countries.


Africa Eastern and Southern

iso2Code: ZH

value: Aggregates

country_code: AFE

country_name: Africa Eastern and Southern

value: Sum

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

value: Annual

value: Environment: Land use


Forest area (sq. km)

value: World Development Indicators

Afghanistan

iso2Code: AF

value: South Asia

iso2code: XM

value: Low income

value: IDA

capitalCity: Kabul

country_code: AFG

country_name: Afghanistan

value: Forest area is land under natural or planted stands of trees of at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural production systems (for example, in fruit plantations and agroforestry systems) and trees in urban parks and gardens.


value: Agriculture & Rural Development

value: Climate Change

value: Environment

Africa Western and Central

iso2Code: ZI

country_code: AFW

country_name: Africa Western and Central


Forest area (sq. km)

Angola

iso2Code: AO

value: Sub-Saharan Africa

value: Sub-Saharan Africa (excluding high income)

value: Lower middle income

iso2code: XF

value: IBRD

capitalCity: Luanda

country_code: AGO

country_name: Angola

value: Forest area (sq. km)

value: CC BY-4.0

value:
As threats to biodiversity mount, the international community is increasingly focusing on conserving diversity. Deforestation is a major cause of loss of biodiversity, and habitat conservation is vital for stemming this loss. Conservation efforts have focused on protecting areas of high biodiversity.

On a global average, more than one-third of all forest is primary forest, i.e. forest of native species where there are no clearly visible indications of human activities and the ecological processes have not been significantly disturbed. Primary forests, in particular tropical moist forests, include the most species-rich, diverse terrestrial ecosystems. The decrease of primary forest area, 0.4 percent over a ten-year period, is largely due to reclassification of primary forest to "other naturally regenerated forest" because of selective logging and other human interventions.

National parks, game reserves, wilderness areas and other legally established protected areas cover more than 10 percent of the total forest area in most countries and regions. FAO estimates that around 10 million people are employed in forest management and conservation - but many more are directly dependent on forests for their livelihoods. Also, 80 about percent of the world's forests are publicly owned, but ownership and management of forests by communities, individuals and private companies is on the rise.

Close to 1.2 billion hectares of forest are managed primarily for the production of wood and non-wood forest products. An additional 25 percent of forest area is designated for multiple uses - in most cases including the production of wood and non-wood forest products. The area designated primarily for productive purposes has decreased by more than 50 million hectares since 1990 as forests have been designated for other purposes.


Albania

iso2Code: AL

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

value: Upper middle income

capitalCity: Tirane

country_code: ALB

country_name: Albania

value: Sum

value: The world and regional aggregate series do not include data from countries that no longer exist.

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

value: Annual

value:
The Food and Agricultural Organization (FAO) has been collecting and analyzing data on forest area since 1946. This is done at intervals of 5-10 years as part of the Global Forest Resources Assessment (FRA). FAO reports data for 229 countries and territories; for the remaining 56 small island states and territories where no information is provided, a report is prepared by FAO using existing information and a literature search. The data are aggregated at sub-regional, regional and global levels by the FRA team at FAO, and estimates are produced by straight summation.

The lag between the reference year and the actual production of data series as well as the frequency of data production varies between countries. Deforested areas do not include areas logged but intended for regeneration or areas degraded by fuelwood gathering, acid precipitation, or forest fires. Negative numbers indicate an increase in forest area.

Data includes areas with bamboo and palms; forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific scientific, historical, cultural or spiritual interest; windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters; plantations primarily used for forestry or protective purposes, such as rubber-wood plantations and cork oak stands. Data excludes tree stands in agricultural production systems, such as fruit plantations and agroforestry systems. Forest area also excludes trees in urban parks and gardens. The proportion of forest area to total land area is calculated and changes in the proportion are computed to identify trends.

value:
Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should reach a minimum height of 5 meters in situ. Areas under reforestation that have not yet reached but are expected to reach a canopy cover of 10 percent and a tree height of 5 meters are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, which are expected to regenerate.

FAO provides detail information on forest cover, and adjusted estimates of forest cover. The current survey uses a uniform definition of forest. Although FAO provides a breakdown of forest cover between natural forest and plantation for developing countries, this indictor data does not reflect that breakdown. Thus the deforestation data may underestimate the rate at which natural forest is disappearing in some countries.


Forest area (sq. km)

value: World Development Indicators

value: Agriculture & Rural Development

value: Climate Change

value: Environment

Andorra

iso2Code: AD

value: High income

value: Not classified

capitalCity: Andorra la Vella

country_code: AND

country_name: Andorra

value: Forest area is land under natural or planted stands of trees of at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural production systems (for example, in fruit plantations and agroforestry systems) and trees in urban parks and gardens.

value: Environment: Land use


Arab World

value: Aggregates

country_code: ARB

country_name: Arab World

value: Forest area (sq. km)

value: CC BY-4.0

value:
As threats to biodiversity mount, the international community is increasingly focusing on conserving diversity. Deforestation is a major cause of loss of biodiversity, and habitat conservation is vital for stemming this loss. Conservation efforts have focused on protecting areas of high biodiversity.

On a global average, more than one-third of all forest is primary forest, i.e. forest of native species where there are no clearly visible indications of human activities and the ecological processes have not been significantly disturbed. Primary forests, in particular tropical moist forests, include the most species-rich, diverse terrestrial ecosystems. The decrease of primary forest area, 0.4 percent over a ten-year period, is largely due to reclassification of primary forest to "other naturally regenerated forest" because of selective logging and other human interventions.

National parks, game reserves, wilderness areas and other legally established protected areas cover more than 10 percent of the total forest area in most countries and regions. FAO estimates that around 10 million people are employed in forest management and conservation - but many more are directly dependent on forests for their livelihoods. Also, 80 about percent of the world's forests are publicly owned, but ownership and management of forests by communities, individuals and private companies is on the rise.

Close to 1.2 billion hectares of forest are managed primarily for the production of wood and non-wood forest products. An additional 25 percent of forest area is designated for multiple uses - in most cases including the production of wood and non-wood forest products. The area designated primarily for productive purposes has decreased by more than 50 million hectares since 1990 as forests have been designated for other purposes.


Forest area (sq. km)

United Arab Emirates

iso2Code: AE

iso2code: ZQ

value: Middle East & North Africa

capitalCity: Abu Dhabi

country_code: ARE

country_name: United Arab Emirates

value: Sum

value: The world and regional aggregate series do not include data from countries that no longer exist.


Argentina

iso2Code: AR

value: Latin America & Caribbean

iso2code: XJ

value: Latin America & Caribbean (excluding high income)

iso2code: XT

value: Upper middle income

value: IBRD

capitalCity: Buenos Aires

country_code: ARG

country_name: Argentina

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

value: Annual

value:
The Food and Agricultural Organization (FAO) has been collecting and analyzing data on forest area since 1946. This is done at intervals of 5-10 years as part of the Global Forest Resources Assessment (FRA). FAO reports data for 229 countries and territories; for the remaining 56 small island states and territories where no information is provided, a report is prepared by FAO using existing information and a literature search. The data are aggregated at sub-regional, regional and global levels by the FRA team at FAO, and estimates are produced by straight summation.

The lag between the reference year and the actual production of data series as well as the frequency of data production varies between countries. Deforested areas do not include areas logged but intended for regeneration or areas degraded by fuelwood gathering, acid precipitation, or forest fires. Negative numbers indicate an increase in forest area.

Data includes areas with bamboo and palms; forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific scientific, historical, cultural or spiritual interest; windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters; plantations primarily used for forestry or protective purposes, such as rubber-wood plantations and cork oak stands. Data excludes tree stands in agricultural production systems, such as fruit plantations and agroforestry systems. Forest area also excludes trees in urban parks and gardens. The proportion of forest area to total land area is calculated and changes in the proportion are computed to identify trends.


Forest area (sq. km)

value: World Development Indicators

value: Agriculture & Rural Development

value: Climate Change

value: Environment

Armenia

iso2Code: AM

value: Europe & Central Asia

value: Europe & Central Asia (excluding high income)

capitalCity: Yerevan

country_code: ARM

country_name: Armenia

value:
Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should reach a minimum height of 5 meters in situ. Areas under reforestation that have not yet reached but are expected to reach a canopy cover of 10 percent and a tree height of 5 meters are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, which are expected to regenerate.

FAO provides detail information on forest cover, and adjusted estimates of forest cover. The current survey uses a uniform definition of forest. Although FAO provides a breakdown of forest cover between natural forest and plantation for developing countries, this indictor data does not reflect that breakdown. Thus the deforestation data may underestimate the rate at which natural forest is disappearing in some countries.