Data underlying the publication: Effective integration of drone technology for mapping and managing palm species in the Peruvian Amazon, Loreto region (2018-2019)
DOI:10.4121/e57f8b3e-20e4-45bc-8581-26a52e2170df.v1
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DOI: 10.4121/e57f8b3e-20e4-45bc-8581-26a52e2170df
DOI: 10.4121/e57f8b3e-20e4-45bc-8581-26a52e2170df
Datacite citation style:
Tagle Casapia, Maria Ximena; Di Liberto, Silvana; Davila, Ander; Cardenas, Rodolfo; Draper, Frederick et. al. (2025): Data underlying the publication: Effective integration of drone technology for mapping and managing palm species in the Peruvian Amazon, Loreto region (2018-2019). Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/e57f8b3e-20e4-45bc-8581-26a52e2170df.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
UAV RGB mosaic clips generated from DJI Phantom 4 and DJI Phantom 4 RTK surveys conducted between January 2018 and October 2019, primarily over palm swamp regions across multiple locations in the Loreto region, Peru. Full-resolution mosaics (some covering areas up to 200 hectares) and labeled data (available only for the clips) are accessible upon request. For further information please get in touch with us via email.
History
- 2025-03-06 first online, published, posted
Publisher
4TU.ResearchDataFormat
tifFunding
- Novel approaches to understand the state of biodiversity and support livelihoods: the distribution and degradation levels of Mauritia flexuosa stands in Amazonia (grant code 41469429) Newton Fund - CONCYTEC Peru
- Integration of high resolution imagery from UAVs for Mapping of Provisioning Ecosystem Services in the tropics (grant code #RF67) [more info...] WWF Russel E. Train Education for Nature Program (EFN)
- Monitoring Protected Areas in Peru to Increase Forest Resilience to Climate Change’ (MonANPeru) (grant code 5349 ) Gordon and Betty Moore Foundation
Organizations
Research Institute of the Peruvian Amazon - IIAPProtected Areas Authority of Peru - SERNANP
School of Geography, University of Leeds
Laboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research
DATA
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ReadMe_Loreto.pdf - 6,519,493,464 bytesMD5:
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Mosaics.7z -
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