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Data · dataset · 2025

Soil Organic Carbon estimation using Sentinel-2 optical remote sensing time series data

Listed in International Potato Center

This R implementation models and predicts Soil Organic Carbon (SOC) content using machine learning techniques.

Description

It analyzes the influence of soil physicochemical properties, historical climate data, and multi-year cropland frequencies on SOC levels.

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Geochemistry 73% · Satellite remote sensing 65%
Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
International Potato Centerdoi:10.21223/P3/8FVH0K10 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:group:3703enrichment · data cipotato orgtaxonomy-embedding@1.1.0title+keywords+description (73%)
concepts[field].dataverse_subject:computer-and-information-sciencesource · data cipotato orgconnector:data_cipotato_org@1.0.0/subjects
concepts[field].local:field:earth-environmentalmapping · data cipotato orgconnector:data_cipotato_org@1.0.0/subjects
concepts[modality].local:modality:remote-sensingenrichment · data cipotato orgkeyword-concept-rules@1.0.0title+description (65%)
created_datesource · data cipotato orgconnector:data_cipotato_org@1.0.0
descriptionsource · data cipotato orgconnector:data_cipotato_org@1.0.0/description
publication_datesource · data cipotato orgconnector:data_cipotato_org@1.0.0
titlesource · data cipotato orgconnector:data_cipotato_org@1.0.0/name
updated_datesource · data cipotato orgconnector:data_cipotato_org@1.0.0
version_labelsource · data cipotato orgconnector:data_cipotato_org@1.0.0