多云雾山丘地区遥感定量化理论及应用进展

在分析光学与微波遥感各自的应用现状及面临的挑战的基础上，从数据层、数据预处理和定量化理论与方法3个层面详细分析和总结了适用于多云雾山丘地区复杂环境的遥感定量化应用理论与方法，包括面向对象的反演策略、主被动遥感协同、时间序列建模、前向模型地形效应修正、弱敏感参数反演等。同时，结合研究团队近年在多云雾山丘地区遥感定量应用的研究实践，给出西南地区的土地连续变化监测、森林火灾风险评估、干旱监测、植被覆盖条件下的土壤水分主被动遥感反演等方面的应用实例。

Theory and Application Status of Quantitative Remote Sensing in Cloudy and Hilly Regions

With the rapid development of the Earth observation technologies, remote sensing plays an increasingly important role in the applications of global change, ecological environment, territorial resources, natural disasters, national defense, smart city, and other applications. Accompanied by the development and improvement for the theories and applications of the quantitative remote sensing, there are still many unprecedented challenges. Because of the Earth complexity of the surface and the limitation of the remote sensing information, the quantitative applications of remote sensing generally are hampered by ill-posed inversion, scale effect, and other problems. Especially for cloudy and hilly regions, sufficiently influenced by the cloud, topography, and spatial heterogeneity, the quantitative applications of remote sensing becomes more difficult. Based on the analysis of the application status and the challenges faced by optical and microwave remote sensing, this paper reviews the theory and approaches applied for cloudy and hilly regions from the perspective of remote sensing data, preprocessing, and the quantitative theory and approaches, which include object-oriented inversion strategy, synergy of active and passive remote sensing, time series modeling, topographic correction of the forward model, and inversion of weak sensitive parameters. In addition, specific application examples are presented based on the recent research and practice achieved by the team of the authors, including continuous change detection of land cover, forest fire risk assessment, drought monitoring, and soil moisture retrieval under vegetation cover from active and passive remote sensing in the southwest China.