Evaluation of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems
Wei Wang, Yan Wang
Abstract
In recent decades, based on new developments in data acquisition, processing, and analysis of satellite remote sensing images, various innovations have been proposed to monitor regional or global agricultural production systems’ resilience. This paper reviews the latest advances in satellite remote sensing techniques and artificial intelligence methods for agriculture sustainability assessment, with a special focus on their application to check the resilience of agriculture production systems. We propose a new approach that combines remote sensing and artificial intelligence, which can be used to improve the resilience of agriculture production systems. This approach is based on classifying the vulnerability of an agricultural sector’s production system into one of three categories—high vulnerability, moderate vulnerability, and low vulnerability. A possible application is presented.