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Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
Published on: February 9, 2024
Comprehensive uncrewed aerial system data for Amazon rainforest at Tiputini Biodiversity Station, Ecuador
Minyoung Jung1, Anjin Chang2, Charles H Cannon3
1Lyles School of Civil and Construction Engineering, Purdue University, West Lafayette, IN, 47907, USA.
None:
The Amazon rainforest, the most biodiverse biome on Earth, represents a critical natural laboratory for studying species interactions, ecosystem functioning, and vulnerability to climate change. High-quality datasets are crucial for advancing a detailed understanding of this complex biome; however, open-access uncrewed aerial system (UAS) datasets for this region remain notably scarce. Here, we present UAS-derived high-resolution products that seamlessly cover over 700 hectares of the upper and hyperdiverse Amazon. To the best of our knowledge, this is the first large-scale, comprehensive, open, and seamless UAS dataset of the Amazon, integrating multispectral imagery and lidar (light detection and ranging) data collected during a single mission, ensuring temporal consistency. The dataset provides complementary spectral and structural information from the Tiputini Biodiversity Station, one of the regions with the highest tree species richness per unit area on Earth. This resource supports diverse applications such as biodiversity and forest-structure analyses and establishes a methodological reference for future large-scale UAS research in the Amazon.
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