An Unexpectedly Large Count of Trees in the West African Sahara and Sahel - Bassin Arachidier au Sénégal

This dataset provides georeferenced polygon vectors of individual tree canopy geometries for dryland areas in West African Sahara and Sahel that were derived using deep learning applied to 50 cm resolution satellite imagery. More than 1.8 billion non-forest trees (i.e., woody plants with a crown size over 3 m2) over about 1.3 million km2 were identified from panchromatic and pansharpened normalized difference vegetation index (NVDI) images at 0.5 m spatial resolution using an automatic tree detection framework based on supervised deep-learning techniques. Combined with existing and future fieldwork, these data lay the foundation for a comprehensive database that contains information on all individual trees outside of forests and could provide accurate estimates of woody carbon in arid and semi-arid areas throughout the Earth for the first time.
 
Citation proposal
. An Unexpectedly Large Count of Trees in the West African Sahara and Sahel - Bassin Arachidier au Sénégal. https://idg-tetis.teledetection.fr/geonetwork/srv/api/records/51c7c1a1-33e9-4f5f-8da8-f5b7c9ebb75c
 

INSPIRE

Identification

File identifier
51c7c1a1-33e9-4f5f-8da8-f5b7c9ebb75c   XML
Hierarchy level
Dataset
Online resource
Protocol
file for download
Protocol
file for download
Protocol
file for download
Protocol
OGC:WMS
Protocol
OGC:WMS
Resource identifier
code
https://doi.org/10.3334/ORNLDAAC/1832
Metadata language
English
Spatial representation type
Vector
Encoding
Format
GeoPackage, ESRI Shapefile
Version
1.0
Projection
code
32628
 

Classification of data and services

Topic category
  • Environment
  • Imagery base maps earth cover
  • Biota
 

Classification of data and services

Coupled resource
Coupled resource
 
 

Classification of data and services

Coupled resource
Coupled resource
 
 

Keywords

General ( Theme )
  • remote sensing
  • vegetation map
  • deep learning
  • Very High spatial resolution optical imagery
GEMET - INSPIRE themes, version 1.0 ( Theme )
GEMET - Concepts ( Theme )
GCMD Keywords viewer ( Theme )
TETIS Thesaurus, version 1.0 21112019 ( Theme )
Other keywords
 
 

Geographic coverage

N
S
E
W


 

Temporal reference

Temporal extent
Begin
2005-11-01T00:00:00Z
End
2018-03-31T00:00:00Z
Temporal extent
Date ( Revision )
2022-05-17T19:08:39
 

Quality and validity

Lineage
The mapping of woody plants at the level of single trees was achieved by the use of satellite data at very high spatial resolution (0.5 m) from DigitalGlobe satellites, combined with modern machine-learning techniques. More than 50,000 DigitalGlobe multispectral images from the QuickBird-2, GeoEye-1, WorldView-2 and WorldView-3 satellites, were collected from 2005–2018 (in November to March) from 12° to 24° N latitude within Universal Transverse Mercator zones 28 and 29 (provided under the NextView license from the National Geospatial Intelligence). Normalized difference vegetation index (NDVI) images were used to distinguish tree crowns from the non-vegetated background because the images were taken from a period during which only woody plants are photosynthetically active in the study area. A set of decision rules was applied to select images for the mosaic, consisting of 25 × 25 km tiles. This resulted in 11,128 images that were used for the study. The neural network model (UNet; publicly available at https://doi.org/10.5281/zenodo.3978185 ) was used to automatically segment the tree crowns—that is, to detect tree crowns in the input images. The segmented areas were then converted to polygons for counting the trees and measuring their crown size. Using machine learning coupled to training data of 89,899 manually delineated and annotated trees, the location of individual trees over 1,300,000 km2 and their crown area were determined from the input images. Every tree with a crown area >3 m2 was enumerated resulting in 1,837,565,501 trees.
Distance
50  cm
 

Conformity

Conformity
Conformity
 

Conformity

Conformity
Conformity
Explanation
some explanation about the conformance
Explanation
See the referenced specification
Explanation
See the referenced specification
 

Restrictions on access and use

 

Restrictions on access and use

 

Responsible organization (s)

Contact for the resource
Organisation name
NASA ORNL DAAC
Email
uso@daac.ornl.gov
 

Responsible organization (s)

Contact for the resource
Organisation name
NASA ORNL DAAC
Email
uso@daac.ornl.gov
 

Metadata information

Contact for the metadata
Organisation name
CNRS UMR TETIS
Email
claudia.lavalley@cnrs.fr
Organisation name
NASA ORNL DAAC
Email
uso@daac.ornl.gov
Organisation name
NASA ORNL DAAC
Email
uso@daac.ornl.gov
Date stamp
2022-05-17T19:20:40
Metadata language
English
Character set
UTF8
 
 

SDS

Conformance class 1: invocable

Access Point URL
Endpoint URL
Technical specification
 

Conformance class 2: interoperable

Coordinate reference system
 
Quality of Service
 
Access constraints
Limitation
 
Use constraints
Limitation
 
Responsible custodian
Contact for the resource
 
 

Conformance class 3: harmonized

 
 

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