内蒙古湿地资源丰富，居全国第三位，但是当前都存在不同程度的退化问题。本项目的研究目标是构建旨在服务于湿地退化过程监测的湿地退化指示种识别技术，为此将综合利用湿地退化指示种的高分光学和高分极化SAR特征，并考虑湿地退化指示种的季节和物候特性，建立自适应的湿地退化指示种识别策略。围绕该目标，本项目将研究：（1）湿地退化指示种高分光学识别能力分析；（2）湿地退化指示种高分极化SAR响应特征及识别能力分析；（3）基于高分光学和高分极化SAR联合的湿地退化指示种识别模型研究；（4）基于多时相高分光学和高分极化SAR退化指示种识别策略；（5）面向达里诺尔湿地保护区退化指示种的识别模型验证与应用示范。本项目的研究成果将为内蒙古湿地退化监测提供强有力的技术支撑，对内蒙古湿地保护具有重要意义。

Inner Mongolia is rich in wetland resources, ranking third in China. While most of them face the threat of degradation in different degrees. This proposal aims to develop a technology to recognize wetland degradation indicator species, which could serve for wetland degradation process monitoring. To achieve such goal, we propose to utilize comprehensively the features extracted from both high-resolution optical images and high-resolution pol-SAR data of wetland degradation indicators species, and the seasonal and phonological characteristics of wetland degradation indicator species, to establish an adaptive wetland degradation indicator identification strategy. The main research topics include: (1) the recognition ability of high-resolution optical images to wetland degradation indicator species. (2) the recognition ability of high-resolution pol-SAR images to wetland degradation indicator species. (3) the joint recognition ability of high-resolution pol-SAR images and high-resolution pol-SAR images to wetland degradation indicator species. (4) the recognition strategy to wetland degradation indicator species based on multi-temporal phase high-resolution pol-SAR images and high-resolution pol-SAR images. (5) the validation to recognition model and operational application in Dalinor wetland reserve area. The research results of this proposal will provide a strong technical support for the monitor of wetland degradation in Inner Mongolia, which is of great significance to the protection of Inner Mongolia wetland.