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With the rapid development of information technologies such as the Internet, the Internet of Things and cloud computing, network big data is widely used in various fields of society, and making good use of network big data is great significance to the sustainable development of cities. Based on the network big data as the data source, this paper analyzes the spatial distribution and spatial-temporal pattern of house prices in the main city zone of Kunming through the Getis-Ord Gi* index and Kriging method, and quantifies the spatial-temporal changes of house prices through statistical analysis and spatial overlay analysis. The result shows that in hot and cold spot analysis, hot spot (high house price agglomeration area) is surrounded by cold spot (low house price agglomeration area), and Chenggong District is the cold spot dominant area. The house price in the main city zone of Kunming forms two high-value areas in the spatial distribution, and presents a pile-shaped ring structure with a central high price and low price in circumference. During the study period, the overall house price fluctuations were small, showing a pattern of north high and south low. The results of statistical analysis and spatial overlay analysis show that there is a significant difference in house prices among various administrative districts. The high-value clusters and low-value clusters in house prices are randomly distributed in various administrative regions. The price changes in Chenggong District are the most significant, and Panlong District has the smallest change.

To explore temporal and spatial evolution of NDVI and its response relation with Climate in Kunming, Yunnan Province, it is is of great significance to the ecological environmental protection and ecological safety construction. Based on the Landsat data of Kunming City from 2010 to 2018 and the meteorological data of Kunming City during the same period, this paper uses the method of pixel dichotomy, correlation analysis and other methods to analyze the temporal and spatial evolution of vegetation coverage and its response to climate change in the past 9 years. The results show that: (1) From 2010 to 2018, Kunming's average annual NDVI showed an upward trend, with an increase of 0.017/year. In 2018, the area covered by high vegetation was as high as 54%, and the ecological environment of Kunming City was significantly improved. (2) The change of NDVI in Kunming is insignificantly positively correlated with annual precipitation and insignificantly negatively correlated with annual average temperature, but has a higher correlation with annual average temperature and is more sensitive to temperature factors. (3) The correlation between NDVI change and elevation differentiation is significant within the elevation zone of 619 ~ 2642m in Kunming city, NDVI increases with the increase of elevation.