Geo-ForPy - Forest Structure Information for the Paraguayan Chaco - Sentinel-1/2/GEDI, 2019

The dataset is based on an analysis combining Sentinel-1 (SAR), -2 (Multispectral) and GEDI (Global Ecosystem Dynamics Investigation, LiDAR) data to model vegetation structure information.

The derived products show high-spatial resolution maps (10 m) of total canopy cover (cover density in %), Foliage height diversity (Fhd) index in meter, Plant area index (Pai) in meter and canopy height (rh95) in meter.

Citation proposal
German Aerospace Center (DLR). Geo-ForPy - Forest Structure Information for the Paraguayan Chaco - Sentinel-1/2/GEDI, 2019. https://gdk.gdi-de.org/geonetwork/srv/api/records/1ef2d116-ee75-4a22-a83c-572fc0238821

Simple

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

Edition

Identifier: https://geoservice.dlr.de/catalogue/srv/metadata/1ef2d116-ee75-4a22-a83c-572fc0238821

Presentation form: Digital map

Other citation details

Purpose: This data set provides a quantitative overview of vegetation structure characteristics of the Paraguayan Chaco comprising various attributes on horizontal and vertical properties.

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
DLR
EOC
GeoForPy
Forest
Forest Structure
Sentinel-1
Sentinel-2
GEDI
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: Grid

Denominator: 20000

Metadata language: English English

Character set: UTF8

Topic category

Biota

Number of dimensions: 2

Dimension name: Column

Dimension size: 57879

Resolution: 10 m

Dimension name: Row

Dimension size: 68333

Resolution: 10 m

Cell geometry: Area

Transformation parameter availability: false

Distribution format

GeoTIFF ()

OnLine resource: FOREST_COVER_S2_PRY
WMS Access: Forest Cover Structures in the Paraguayan Chaco: Total Canopy Cover

OnLine resource: FOREST_FHD_S2_PRY
WMS Access: Forest Cover Structures in the Paraguayan Chaco: Foliage Height Diversity Index

OnLine resource: FOREST_PAI_S2_PRY
WMS Access: Forest Cover Structures in the Paraguayan Chaco: Plant Area Index

OnLine resource: FOREST_RH95_S2_PRY
WMS Access: Forest Cover Structures in the Paraguayan Chaco: Canopy Height (95th percentile)

OnLine resource: HTTP download Geo-ForPy - Paraguayan Chaco, 2019
HTTP download Geo-ForPy - Paraguayan Chaco, 2019

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

OnLine resource: Fusing Sentinel-1 and -2 to Model GEDI-Derived Vegetation Structure Characteristics in GEE for the Paraguayan Chaco
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 dataset provides large-scale information on vegetation structure information (canopy height, total canopy cover, plant area index, foliage height diversity index), that allows for a complete understanding of spatial characteristics for the complete Paraguayan Chaco, when combined with the other modelled data sets.

Description

Geo-ForPy - Forest Structure Information for the Paraguayan Chaco - Processing

Data:

The data basis for modelling comprises data from Synthetic-Aperture-Radar (SAR) from Sentinel-1, multispectral Information from Sentinel-2 and LiDAR (Light detection and ranging) data from GEDI. All data has been filtered to the period of the dry season 2019 (April to September).

Processing:

GEDI data has been preprocessed (quality and temporal filtering) on a local machine (16 GB RAM). Sentinel preprocessing (Sentinel-1: radiometric terrain normalization and speckle filtering; Sentinel-2 cloud masking, vegetation indices, temporal-spectral metrics) and modelling has been fully conducted in Google Earth Engine using the Python API.

Quality Assurance:

Cover: Modeling accuracy for total canopy cover amounts to: 61.4 % in R² (coefficient of determination) and 9.1 % in RMSE (root mean square error).

Fhdi: Modeling accuracy for Foliage height diversity index amounts to: 48,0 % in R² (coefficient of determination) and 0,3 in RMSE (root mean square error).

Pai: Modeling accuracy for Plant area index amounts to: 50,6 % in R² (coefficient of determination) and 0,3 in RMSE (root mean square error).

rh95 Modeling accuracy for canopy height amounts to: 64,0 % in R² (coefficient of determination) and 1,6 m in RMSE (root mean square error).