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Date of publication: December 15, 2022

Version 1

Date of publication: December 15, 2022

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Forest loss from 2000 to 2020

by Miguel Fernandez

This EBV dataset is based entirely on the time series analysis developed by Prof. Matthew Hansen and colleagues (2013) in version 1.8, which examines the global Landsat archive at a special resolution of 30 meters to characterize global forest extent and change from 2000 through 2020. In this EBV dataset we focus on "Forest Cover loss" defined as a stand-replacement disturbance, or a change from a forest to non-forest state. The original data fro ...(continue reading)

DOI 10.25829/a4pw92
Citation
Fernandez, M. (2022). Forest loss from 2000 to 2020 (Version 1) [Dataset]. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. https://doi.org/10.25829/a4pw92

Forest loss

2
The title of the dataset. Forest loss from 2000 to 2020
The date on which this version of the data was created in YYYY-MM-DD format.
A paragraph describing the dataset.
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This EBV dataset is based entirely on the time series analysis developed by Prof. Matthew Hansen and colleagues (2013) in version 1.8, which examines the global Landsat archive at a special resolution of 30 meters to characterize global forest extent and change from 2000 through 2020. In this EBV dataset we focus on "Forest Cover loss" defined as a stand-replacement disturbance, or a change from a forest to non-forest state. The original data from Hansen et al., (2013), was processed using a factor of 15 to aggregate to a new spatial resolution of 450 x 450 meters and are structured in the multidimensional and standard format proposed by the GEO BON community for the Essential Biodiversity Variables.
Provide the DOI number of associated publications. Click Plus to add DOIs.
https://doi.org/
10.1126/science.1244693
The method of production of the original data.
Hover to see a suggestion for a minimum description. To produce this dataset, we build on the process, results, and data outputs from time-series analysis of Landsat images in characterizing global forest extent and change from 2000 through 2020 (Hansen et al., Science 2013; version 1.8). Here forest loss during the period 2000–2020, is defined as a stand-replacement disturbance, or a change from a forest to non-forest state; encoded as either 0 (no loss) or else a value in the range 1–20, representing loss detected primarily in the year 2001–2020, respectively. We aggregate the original data at 30x30 meter spatial resolution using a factor of 15 that resulted in a new dataset at a resolution of 450x450 meters. All calculations and processing were made using ArcGIS Pro tools. The value of each 450x450 meter pixel in this aggregated dataset represents the number of pixels at the original resolution (30x30 meters) that experienced this transition from forest to non-forest state in a particular year.
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The name of the Project.
The URL from the project website. https://e-shape.eu
The name of the person or other creator type principally responsible for creating this data.
The email of the person or other creator type principally responsible for creating this data. miguel.fernandez@idiv.de

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miguel.fernandez@idiv.de

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Essential Biodiversity Variables

Select the EBV class and the EBV name for the dataset. For cross-cutting use the comment at the bottom of the page for further information.
Genetic composition
Intraspecific genetic diversity
Genetic differentiation
Effective population size
Inbreeding
Other
Species populations
Species distributions
Species abundances
Other
Species traits
Morphology
Physiology
Phenology
Movement
Other
Community composition
Community abundance
Taxonomic and phylogenetic diversity
Trait diversity
Interaction diversity
Other
Ecosystem functioning
Primary productivity
Ecosystem phenology
Ecosystem disturbances
Other
Ecosystem structure
Live cover fraction
Ecosystem distribution
Ecosystem Vertical Profile
Other
Ecosystem services
Pollination
Other
Cross-cutting

Entity

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Species
Communities
Ecosystems
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None
A description of the range of taxa or ecosystem types addressed in the dataset. E.g. "300 species of mammals”, “Forests”, etc.
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Metric

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Scenario

Spatial domain

Global
Continental/Regional
National
Sub-national/Local
degree
southWest lat: -60, lon: -180
northEast lat: 80, lon: 180

Temporal domain

The targeted time period between each value in the dataset.
decadal
annually
monthly
weekly
daily
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__

Environmental domain *

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Freshwater
Miscellaneous information about the data, not captured elsewhere. N/A
Entities
Forest