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Forest loss year (2000-2018)

Dataset Creator: Matthew Hansen
Publication Year: 2019

Forest loss during the period 2000–2018, defined as a stand-replacement disturbance, or a change from a forest to non-forest state. Data in this layer were generated using multi-spectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+) sensor. The clear surface observations from over 600,000 images were analysed using Google Earth ...

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Forest lossGoogleGlobal

Title:

Forest loss year (2000-2018)

Publication Year:

2019

Description:
Associated Publications: https://doi.org/10.1126/science.1244693
External links to the project: https://earthenginepartners.appspot.com
https://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.7.html
License:

CC BY 4.0

Creator

Name:

Matthew Hansen

E-mail: mhansen@umd.edu
Organisation:

University of Maryland

Contact

Name:

Matthew Hansen

E-mail: mhansen@umd.edu
Organisation:

University of Maryland

Essential Biodiversity Variables (EBVs)

EBV class

Ecosystem structure

EBV name

Ecosystem distribution

Spatial domain

Spatial extent:

Global

W: -180.0 S: -90.0 E: 180.0 N: 90.0
Spatial resolution:

1000 meter

Spatial accuracy:

1000 meter

Temporal domain

Temporal resolution:

Yearly

Temporal extent:

From 2000-01-01 to 2018-01-01

Biological entity

Entity type:

Ecosystem Types

Classification System Name:

Forests

Environmental domain

Realm:

Terrestrial

Metric

Name:

Forest loss

Description:

Encoded as either 0 (no loss) or else a value in the range 1–18, representing loss detected primarily in the year 2001–2018, respectively.

Unit:

Year of gross forest cover loss event


Scenario

No scenario provided

Description of resources:

Methodology available from https://science.sciencemag.org/content/sci/suppl/2013/11/14/342.6160.850.DC1/Hansen.SM.pdf

Resources used to generate the data

Resource 1
Name and version:

High-Resolution Global Maps of 21st-Century Forest Cover Change

Type:

Description of protocol


Access:

Open


Link:

https://doi.org/10.1126/science.1244693


Reference:


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