Results 261 to 270 of about 232,366 (358)

Assessing group size and the demographic composition of a canopy‐dwelling primate, the northern muriqui (Brachyteles hypoxanthus), using arboreal camera trapping and genetic tagging

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
We combined arboreal camera trapping and non‐invasive genetic tagging to estimate group size in the critically endangered northern muriqui (Brachyteles hypoxanthus) in Brazil's Atlantic Forest. Both methods provided complementary insights into group size and demographic structure, while differing in their cost‐effectiveness and sampling constraints ...
Mariane C. Kaizer   +7 more
wiley   +1 more source

Stunted canopy: Marine forests under the thermal effluent of a nuclear power plant [PDF]

open access: hybrid
Ivan Monclaro Carneiro   +3 more
openalex   +1 more source

Robotics‐assisted acoustic surveys could deliver reliable, landscape‐level biodiversity insights

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
Deploying and maintaining sensors is often a major bottleneck in collecting rapid biodiversity data. We tested whether autonomous hopping drones equipped with acoustic recorders could collect reliable biodiversity data in Costa Rica. Using 26,000+ hours of existing audio from 341 sites, with machine learning detections of 19 bird species and spider ...
Peggy A. Bevan   +5 more
wiley   +1 more source

Wall‐to‐wall Amazon forest height mapping with Planet NICFI, Aerial LiDAR, and a U‐Net regression model

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
Tree canopy height is a key indicator of forest biomass and structure, yet accurate mapping across the Amazon remains challenging. Here, we generated a canopy height map of the Amazon forest at ~4.8 m resolution using Planet NICFI imagery and a deep learning U‐Net model trained with airborne LiDAR data.
Fabien H. Wagner   +21 more
wiley   +1 more source

Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
Accurately estimating forest age is key to understanding how forests recover and evaluating restoration success. We developed a two‐step deep learning approach using historical greyscale aerial photographs to map forest age at fine spatial scales. By combining a pre‐trained model with localized fine‐tuning, our U‐Net + ResNet50 architecture achieved ...
Ying Ki Law   +10 more
wiley   +1 more source

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