Artificial intelligence and machine learning applications in forest management and biodiversity conservation

Abstract

The recent progress in data science, along with the transformation in digital and satellite technology, has enhanced the capacity for artificial intelligence (AI) applications in the forestry and wildlife domains. Nevertheless, the swift proliferation of developmental projects, agricultural, and urban areas pose a significant threat to biodiversity on a global scale. Hence, the integration of emerging technologies such as AI in the fields of forests and biodiversity might facilitate the efficient surveillance, administration, and preservation of biodiversity and forest resources. The objective of this paper is to present a comprehensive review of how AI and machine learning (ML) algorithms are utilized in the forestry sector and biodiversity conservation worldwide. Furthermore, this research examines the difficulties encountered while implementing AI technology in the fields of forestry and biodiversity. Enhancing the availability of extensive data pertaining to forests and biodiversity, along with the utilization of cloud computing and digital and satellite technology, can facilitate the wider acceptance and implementation of AI technology. The findings of this study would inspire forest officials, scientists, researchers, and conservationists to investigate the potential of AI technology for the purposes of forest management and biodiversity conservation.