Geo-ForPy - Fragmentation of Forest Cover in the Paraguayan Chaco - Landsat-5/7/8, 2000/2010/2020

This product is a shape file of all detected forest patches in the Paraguayan Chaco that are larger than 10 hectars fort he years 2000, 2010, and 2020. Every forest patch contains information on its perimeter, size, shape, and core area. By looking at all forest patches together, an impression can be gained of the fragmentation of the forest in the Paraguayan Chaco.

Proximity is a measure of fragmentation. Areas of large and close by forest patches show high proximity values while isolated patches or patchest hat are only surrounded by small forest patches, have a small proximity.

The Core area index quantifies the share of core area in the entire forest patch area. Thereby, corea area is the area of a forest patch with at least 500m distance to the edge of the forest.

The Shape index is calculated from perimeter and area of a patch. The fragementation of a forest often has the effect that the ratio between area and perimeter is affected. The edge lengths become longer while the surface area becomes smaller.

Citation proposal
German Aerospace Center (DLR). Geo-ForPy - Fragmentation of Forest Cover in the Paraguayan Chaco - Landsat-5/7/8, 2000/2010/2020. https://gdk.gdi-de.org/geonetwork/srv/api/records/2F5ca620b7-1b15-47e5-af23-fc7ae77db345

Simple

Date ( Creation ): 2022-09-01T00:00:00

Edition

Identifier: https://geoservice.dlr.de/catalogue/srv/metadata/2F5ca620b7-1b15-47e5-af23-fc7ae77db345

Presentation form: Digital map

Other citation details

Purpose: This data set shows how the fragmentation of the forest in the Paraguayan Chaco proceeded over the last two decades (2000 – 2020).

Status: Completed

Author

German Aerospace Center (DLR) -

Point of contact

German Aerospace Center (DLR)

Maintenance and update frequency: As needed

GEMET - INSPIRE themes, version 1.0 ( Theme )

Land cover

Spatial scope

National

Keywords

opendata
forest
forest cover
random forest
fragmentation
Landsat-5
Landsat-7
Landsat-8
Paraguay

Use limitation: Nutzungseinschränkungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Use Limitations: DLR not liable for damage resulting from use.

Access constraints: Other restrictions

Use constraints: Other restrictions

Other constraints: Nutzungsbedingungen: Lizenz, https://creativecommons.org/licenses/by/4.0/ Terms of use: License, https://creativecommons.org/licenses/by/4.0/

Other constraints

{"id": "cc-by-4.0",

"name": "Creative-Commons - Attribution 4.0 International (CC BY 4.0)",

"url": "http://dcat-ap.de/def/licenses/cc-by/4.0",

"quelle": "Copyright DLR (2022)"}

Spatial representation type: Vector

Denominator: 60000

Metadata language: English English

Character set: UTF8

Topic category

Biota

Distribution format

Geopackage ()

OnLine resource: FOREST_FRAGMENTATION_PRY_2000
WMS Access: Forest Fragmentation Paraguay for 2000

OnLine resource: FOREST_FRAGMENTATION_PRY_2010
WMS Access: Forest Fragmentation Paraguay for 2010

OnLine resource: FOREST_FRAGMENTATION_PRY_2020
WMS Access: Forest Fragmentation Paraguay for 2020

OnLine resource: HTTP download Geo-ForPy - Paraguayan Chaco, 200/2010/2020
HTTP download Geo-ForPy - Paraguayan Chaco, 200/2010/2020

OnLine resource: Geo-ForPy - Deforestration in Latin America and the Paraguayan Chaco
Geo-ForPy - project Webpage

OnLine resource: Understanding 34 Years of Forest Cover Dynamics across the Paraguayan Chaco: Characterizing Annual Changes and Forest Fragmentation Levels between 1987 and 2020
Article

Hierarchy level: Dataset

Domain consistency

Measure identification: INSPIRE / Conformity_001

Conformance result

Date ( Publication ): 2010-12-08

Explanation: See the referenced specification.

Pass: true

Statement: This data set provides information on the forest of the Paraguayan Chaco on a patch level, for the years 2000, 2010, and 2020.

Description

Fragmentation of forest cover in the Paraguayan Chaco 2000, 2010, 2020 - Processing

Data:

The forest cover shape file for the years 2000, 2010, and 2020 was derived from the forest masks of the respective years, which are a product of the Geo-ForPy project. More information on this data set can be found under the following link.

Processing:

The forest masks were transformed from a raster to a vector format using a 4 neighborhood and all forest patches less than 10 hectars were deleted. Next, patch level metrics (area, perimeter, perimeter-area-ratio, shape index, fractal dimension, proximity, core area, core area index) were calculated.

Quality Assurance:

The underlying forest masks have overall accuracies between 85% and 97%. Missclassifications directly affect the calculated forest area.