Extracting Diurnal Activity Patterns of Birds in Communal Roosts From Polarimetric Weather Radar Data

作者：Zhuoran Sun, Cheng Hu, Kai Cui, Rui Wang, Mingming Ding, Zujing Yan, Dongli Wu · 发表于：IEEE Transactions on Geoscience and Remote Sensing · 年份：2024 · DOI：10.1109/tgrs.2024.3513294 · 被引用次数：92 · 研究领域：Avian ecology and behavior、Remote Sensing in Agriculture

Communal roosts are essential stopover sites for migratory birds. Monitoring the diurnal activity patterns of birds in communal roosts (DAPBCRs) is crucial for understanding their migratory behavior and ecological needs. This information is crucial for guiding habitat conservation and management strategies and assessing the impact of environmental changes on bird populations. Traditional methods for extracting DAPBCR often rely on detecting high reflectivity factor arc features generated by birds collectively leaving or returning to communal roosts using weather radar data and deep learning target detection algorithms. However, many bird echoes do not produce these high reflectivity factor arc features, making pixel-level extraction of DAPBCR challenging. To address this, we propose a method for DAPBCR extraction based on the differences in the probability distribution function (pdf) of differential backscattering phase between birds and insects. This method first removes nonbiological echoes from polarimetric weather radar data, retaining only biological echoes. By calculating the differential backscattering phase using the differential phase and system differential phase, we obtain the pdf of the differential backscattering phase for biological echoes. We fit this pdf to a mixed von Mises distribution to obtain the PDFs for birds and insects. Using posterior probabilities for birds and insects, we estimate the bird-insect mixing ratio and further estimate the number of bird...