Group 1: AI Technology in Natural Resource Monitoring - The introduction of AI technology in natural resource monitoring significantly enhances the precision of identifying various tree species, which is crucial for detailed investigations of forests, grasslands, wetlands, and desertification [1][14] - AI can assist in the classification of land types, such as distinguishing between different vegetation types and improving the accuracy of land use assessments, thereby reducing manual workload [2][14] - The application of AI in data extraction, field verification, result validation, and analysis stages is expected to optimize the entire monitoring process, leading to increased efficiency and accuracy [2][14] Group 2: Evolution of Monitoring Techniques - The transition from traditional paper-based surveys to digital methods using tablets, and now to smartphone-based comprehensive monitoring, reflects the industry's adaptation to technological advancements [3][16] - Future expectations include the seamless integration of more advanced technologies into natural resource monitoring to continuously improve efficiency and expand operational boundaries [3][16] Group 3: Importance of Data and Technology Integration - The integration of high-resolution imagery and AI for automatic monitoring and data extraction is a key development in enhancing the capabilities of natural resource departments [2][14] - The establishment of automated models for result verification and the creation of local knowledge bases using big data analytics are essential for intelligent natural resource management [2][14]