Crop type classification using a combination of optical and radar remote sensing data: a review

Reliable and accurate crop classification maps are an important data source for agricultural monitoring and food security assessment studies. For many years, crop type classification and monitoring were focused on single-source optical satellite data classification. With advancements in sensor technologies and processing capabilities, the potential of multi-source satellite imagery has gained increasing attention. The combination of optical and radar data is particularly promising in the context of crop type classification as it allows explaining the advantages of both sensor types with respect to e.g. vegetation structure and biochemical properties. This review article gives a comprehensive overview of studies on crop type classification using optical and radar data fusion approaches. A structured review of fusion approaches, classification strategies and potential for mapping specific crop types is provided. Finally, the partially untapped potential of radar-optical fusion approaches, research gaps and challenges for upcoming future studies are highlighted and discussed.

搜集汇总

背景与挑战

背景概述

该数据集是一篇综述文章，全面回顾了结合光学和雷达遥感数据用于作物类型分类的研究。它总结了数据融合方法、分类策略，并探讨了该领域的潜力和挑战，旨在为农业监测和粮食安全评估提供支持。