Combining the travel modes of human activities, fully mining multi-source data, and analyzing the relationship between the urban ecological environment and human activities are important topics in urban ecological environment planning. Human activity indicators were constructed based on the data of POI points, OSM road network, and residential areas. Machine learning models such as support vector regression machine, extreme gradient boosting regression, polynomial regression, and random forest regression were combined with remote sensing images to construct an urban ecological environment indicator system. These models were used to conduct regression analysis of urban ecological environment indicators and human activity indicators in Chengdu, China. The research shows that the three indicators of human activities all show a trend of increasing in the center and gradually decreasing in the surrounding areas, while the sustainable urban ecological environment indicators show the opposite trend. On the relationship between urban ecological environment and human activities, XGB has the best effect; the correlation between the street vitality index and the urban function mixing index and the sustainable urban ecological environment is stronger, and the correlation between the walkability measure index of the residential area and the sustainable urban ecological environment is even worse.

Water resource is an important foundation to support industrial and agricultural production, in the maintenance of national energy security role is irreplaceable. Water conservation and the effective use of water resources are essential for achieving sustainable development in China. The construction of water-saving society is a prerequisite for realizing efficient utilization of water resources and an important strategic development for moving towards environment-friendly society. This study established an index system to evaluate the implementation of water-saving measures in Xiangtan, Hunan province, China. The index system incorporated five aspects: (1) comprehensiveness; (2) agricultural water; (3) industrial water; (4) domestic water, and; (5) aquatic ecology and environmental management. Analytic hierarchy (AH) was used to determine the weights of indices, and AH was integrated with grey relative analysis to establish a comprehensive system for the evaluation of the water-saving measures in Xiangtan. The results showed that the implementation of water-saving measures in Xiangtan is generally progressing well. However, industrial added value water consumption per 10,000-yuan remains at the primary stage and wastewater reuse remains limited. In addition, water use per 10,000-yuan gross domestic product, the coverage of water-saving irrigation projects, industrial wastewater reuse, and the leakage rate of urban water supply network remain at an intermediate stage. The result of this study can scientifically reflect the level of the water-saving measures in place in Xiangtan and could guide future implementation of water saving measures in Xiangtan and in other cities.