Abstract: As an important approach to supporting national ecosystem governance and resource management, remote sensing-based ecosystem monitoring is facing multiple challenges such as rapid growth of data volume, diversified business demands, and a demand for higher interpretation accuracy. To enhance the intelligence level of remote sensing interpretation, this study designed an intelligent framework of remote sensing image interpretation oriented to ecosystem monitoring services by integrating several algorithm modules, including image recognition, intelligent interpretation, and change detection. This framework enables automated processing of remote sensing images throughout the whole process from sample construction to multi-task interpretation. The proposed framework was verified by applying it to the extraction of patches with changes from multitemporal images of a pilot area in Guangdong Province. The results reveal that the recognition rate of patches with true changes reached 60.99%, with an area coverage rate of up to 78.94%. This finding suggests that the intelligent framework exhibits a strong capability of change recognition and a high efficiency of intelligent interpretation under complex ecological backgrounds, confirming its practicality and stability in actual applications.