Research on image capture technology of intelligent terminal and multi exposure fusion to improve the resilience of agriculture production systems

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. In order to analyze agriculture sustainability, this study covers the most recent developments in artificial intelligence methodologies and satellite remote sensing techniques, with a particular emphasis on how they might be used to assess the resiliency of agricultural production systems. We propose a new strategy that combines artificial intelligence with remote sensing that may be applied to increase the sustainability of agricultural 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.