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The monitoring data of key areas of non-uniform surface observed by satellite remote sensing are usually complicated and uncertain, and are easily affected by various factors such as weather and equipment failure, which makes it difficult to accurately determine key monitoring areas and obtain useful information, resulting in limited monitoring scope and large errors in monitoring results. Therefore, in order to provide data support for the treatment of non-uniform surface, the wireless sensor network is used to optimize the design of satellite remote sensing observation of non-uniform surface monitoring system. Add satellite remote sensing observation image sensors, adjust the wireless sensor network module, modify the monitoring data processor, use the adjusted system circuit to connect the hardware components, complete the optimization of the hardware system, and avoid data loss or error caused by equipment failure or weather and other factors. Through the construction and logical connection of database table, the results of database construction of monitoring system are obtained. With the support of hardware and database, the wireless sensor network is constructed from the aspects of topology and transmission protocol. To realize the deep integration of high altitude remote sensing and wireless sensor network, the wireless sensor network is used to collect surface satellite remote sensing observation images, obtain more comprehensive and accurate surface information, expand the monitoring range, effectively overcome the complexity and uncertainty of satellite remote sensing data, and improve the accuracy of information acquisition. Through filtering, geometric correction and other steps, the initial image is preprocessed to improve the quality of the image, and the image features are extracted. According to the matching results of the feature images, the key areas of the non-uniform surface are determined. Finally, according to the obtained information and data, the key areas of non-uniform land surface are monitored by satellite remote sensing according to the indexes such as surface tilt Angle and surface non-uniformity degree. The results show that compared with the traditional monitoring system, the monitoring errors of the output surface inclination Angle and surface deformation are reduced by 0.28° and 0.73m3 respectively, and the monitoring range of the system is obviously expanded.