Land-Use Degree and Spatial Autocorrelation Analysis in Kunming City Based on Big Data

This paper applies the theory of spatial correlation, basing on big data of ENVI remote sensing image interpretation and the land use data of 14 counties in Kunming, to analyze the spatial autocorrelation of land use structure and land use degree in Kunming in 2005, 2011 and 2015 with Moran Index I. The research shows: (1) The share of cultivated land and vegetation coverage in the land use structure of Kunming are large, but the area of cultivated land is decreasing while the area of construction land is increasing. (2)There is a global spatial autocorrelation of land use in Kunming, but the correlation is weakening. (3)There is local spatial autocorrelation clustering in land use degree in Kunming, including four types: high - high agglomerations(HH), high - low agglomerations(LL), low - low agglomerations, and low - high agglomerations(LH). But the agglomerations are weakening.