Monitoring low-intensity management by selective logging in an Amazon forest using deep learning and Planet NICFI imagery

Name: Monitoring low-intensity management by selective logging in an Amazon forest using deep learning and Planet NICFI imagery
Keywords: Sustainable forest management, Forest management

Braga, Daniel; Dalagnol, Ricardo; Aragão, Luiz

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ZENODO

Dataset . 2025

License: CC BY

Data sources: Datacite

ZENODO

Dataset . 2025

License: CC BY

Data sources: Datacite

ZENODO

Dataset . 2025

License: CC BY

Data sources: Datacite

Monitoring low-intensity management by selective logging in an Amazon forest using deep learning and Planet NICFI imagery

Research datakeyboard_double_arrow_right Dataset 01 Jan 2025 English Publisher:Zenodo

Authors: Braga, Daniel; Dalagnol, Ricardo; Aragão, Luiz;

doi: 10.5281/zenodo.14783442 , 10.5281/zenodo.14780147 , 10.5281/zenodo.14780148

Monitoring low-intensity management by selective logging in an Amazon forest using deep learning and Planet NICFI imagery

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Abstract

(1) REDD+AI, TMF, GFC and DETER-B raster and vetorial data clipped to Jamari (2) Brazilian Forest Service reference data shapefiles (forest management) (3) Collect Earth Online Jamari logging samples data and related files Data used in the paper Monitoring low-intensity management by selective logging in an Amazon forest using deep learning and Planet NICFI imagery.

Related Organizations

National Aeronautics and Space Administration
United States
National Institute for Space Research
Brazil
Jet Propulsion Lab
United States

Keywords

Sustainable forest management, Forest management

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