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Imaging · collection · 2020

An Unexpectedly Large Count of Trees in the West African Sahara and Sahel

Listed in NASA Earthdata CMR and NASA Data Portal — shown once because both records carry DOI 10.3334/ornldaac/1832

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.

Description

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 (NDVI) 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.

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Catalogue records · 3

Topics

Inferred from text
Geoinformatics 74% · Image 65% · Satellite remote sensing 65%
Provenance · 2 source records, 20 field assertions
SourceKeyLast seenRaw
NASA Earthdata CMRC2761798565-ORNL_CLOUD14 d agoJSON v1
NASA Data Portal2aa61ccb-dfa6-4336-9520-4c4a925fec9c11 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · NASA CMRconnector:nasa_cmr@1.0.0
concepts[field].anzsrc:group:3704enrichment · NASA CMRtaxonomy-embedding@1.1.0title+keywords+description (74%)
concepts[instrument].gcmd_instrument:computersource · NASA CMRconnector:nasa_cmr@1.0.0
concepts[measured_variable].gcmd:earth-science/biosphere/ecosystems/terrestrial-ecosystems/savannassource · NASA CMRconnector:nasa_cmr@1.0.0
concepts[measured_variable].gcmd:earth-science/biosphere/ecosystems/terrestrial-ecosystems/shrubland-scrubsource · NASA CMRconnector:nasa_cmr@1.0.0
concepts[measured_variable].gcmd:earth-science/biosphere/vegetation/canopy-characteristicssource · NASA CMRconnector:nasa_cmr@1.0.0
concepts[measured_variable].gcmd:earth-science/biosphere/vegetation/forest-composition-vegetation-structuresource · NASA CMRconnector:nasa_cmr@1.0.0
concepts[measured_variable].gcmd:earth-science/biosphere/vegetation/vegetation-coversource · NASA CMRconnector:nasa_cmr@1.0.0
concepts[modality].local:modality:imageenrichment · NASA CMRkeyword-concept-rules@1.0.0title+description (65%)
concepts[modality].local:modality:remote-sensingenrichment · NASA CMRkeyword-concept-rules@1.0.0title+description (65%)
concepts[platform].gcmd_platform:modelssource · NASA CMRconnector:nasa_cmr@1.0.0
created_datesource · NASA CMRconnector:nasa_cmr@1.0.0
descriptionsource · NASA CMRconnector:nasa_cmr@1.0.0/umm/Abstract
license_textsource · data nasa govconnector:data_nasa_gov@1.0.0
publication_datesource · NASA CMRconnector:nasa_cmr@1.0.0
spatialsource · NASA CMRconnector:nasa_cmr@1.0.0/umm/SpatialExtent
temporalsource · NASA CMRconnector:nasa_cmr@1.0.0/umm/TemporalExtents
titlesource · NASA CMRconnector:nasa_cmr@1.0.0/umm/EntryTitle
updated_datesource · NASA CMRconnector:nasa_cmr@1.0.0
version_labelsource · NASA CMRconnector:nasa_cmr@1.0.0