The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/c9e33027-2376-4b34-9187-db9141b672cf

Tagle Casapia, Maria Ximena; Falen, Lourdes; Harm Bartholomeus; Cardenas, Rodolfo; Flores, Gerardo et. al. (2025): Data underlying the publication: Identifying and Quantifying the Abundance of Economically Important Palms in Tropical Moist Forest Using UAV Imagery. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/c9e33027-2376-4b34-9187-db9141b672cf.v1

Dataset

• Forestry
• Plant Production and Plant Primary Products

DJI, forest, palm swamp, tropical, UAV

view on openstreetmap

2017

CC BY-NC-SA 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Maria Ximena Tagle Casapia , Lourdes Falen , Harm Bartholomeus , Rodolfo Cardenas , Gerardo Flores , Martin Herold , Euridice N Honorio Coronado , Tim Baker

Ten UAV RGB mosaics were generated from DJI Phantom 4 surveys conducted between October and December 2017 in palm swamp areas across various locations in the Loreto region of Peru. For access to the labeled data, please feel free to reach out via email.

• 2025-01-15 first online, published, posted

4TU.ResearchData

tif

Identifying and Quantifying the Abundance of Economically Important Palms in Tropical Moist Forest Using UAV Imagery

• Monitoring Protected Areas in Peru to Increase Forest Resilience to Climate Change’ (MonANPeru) (grant code 5349 ) Gordon and Betty Moore Foundation
• 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)

Research Institute of the Peruvian Amazon - IIAP
Laboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research - WUR