Remote Sensing Applications for Monitoring Habitat Degradation and Conservation Prioritization in Biodiversity Hotspots

Abstract

Abstract: However habitat degradation is one of the biggest causes of biodiversity loss and is threatening the stability of ecosystems and the ability to implement effective conservation efforts in global biodiversity hotspots. This study proposes an integrated multi-source geospatial data framework for habitat degradation monitoring and conservation prioritization using remote sensing information. The proposed methodology is based on the integration of optical satellite data, Synthetic Aperture Radar (SAR), LiDAR observations, and high-resolution Unmanned Aerial Vehicle (UAV) data, for the purposes of producing accurate land use and land cover maps, condition assessments of vegetation, habitat suitability models, and ecological connectivity analyses. These advanced preprocessing, computing of the spectral index and multi-source data fusion increase the confidence of habitat characterization under various environmental conditions. Forest cover loss detection, vegetation health monitoring and wetland change assessment are used to quantify habitat degradation, and indicators of species richness, habitat suitability and landscape connectivity are used to identify conservation priority zones. The experimental assessment shows high land cover classification accuracy, robust habitat degradation detection and reliable identification of the biodiversity hotspots that facilitates timely ecological decision-making. The proposed framework will improve planning for conservation by offering a scalable, cost-effective and repeatable monitoring process for protected areas and ecologically sensitive landscapes. In general, the use of remote sensing technologies is a useful decision support tool for sustainable biodiversity management, restoration of habitats and long-term conservation and protection of ecosystems in the context of growing anthropogenic and climate influences.