Optimizing biodiversity conservation in Sunderland through advanced geospatial techniques and remote sensing technologies - Usman Gabi, Alhassan; Mohamad Abdullah, Nazirah (2023)
Sundaland ecosystems are under threat from human activity and climate change such as logging, agricultural practices, overexploitation of wildlife and climatic change that have led to frequent forest fires and a decline in indigenous plant and animal species. This study investigates the risks to Sundaland's biodiversity as well as the management possibilities using GIS, RS, and AI. The goal was to find out how artificial intelligence (AI) can be applied to effectively manage biodiversity and expand on the body of knowledge already available about the useful roles that GIS and RS play in the area. In this systematic method, seven databases were used to gather data from 110 research publications, of which 101 were screened for scope and subject variable. 80% (81articles) of the examined studies collected data using GIS and RS. It is found that. AI in biodiversity management is poised to grow, offering new opportunities to address the intricate challenges facing our planet's diverse ecosystems. In conclusion, for efficient monitoring, well-informed policy creation, and decision-making to guarantee the long-term preservation of Sundaland's biodiversity, integration of GIS, RS, and AI is essential