610 / 2019-04-29 03:18:19

The spatiotemporal non-stationarity of the relationship between land cover and land surface temperature in multiple time series

LST;Multi-timescale;Temporal dynamic;GWR;Urban

全体主题 > Remote Sensing

The method of geographic weighted regression is widely used to explore the relationship between surface thermal environment and surface ele-ment coverage due to the consideration of spatial heterogeneity. Howev-er, most of the current researches only focus on a single image This paper selected satellite image data and land cover data of five time nodes in wuhan from 2004 to 2016, and used the GWR method to explore the re-lationship between surface thermal environment and land cover. The ex-perimental results show that because of the evolution of cities, the influ-ence of surface land use on urban surface temperature presents obvious spatial and temporal non-stationarity. At the same time, this experiment compared the results of GWR and GTWR. The results showed that alt-hough the time non-stationarity of GTWR was taken into account, the fitting effect of GTWR at the present stage was not significantly im-proved compared with the geographical weighted regression when it was applied to the geographical factors with large temporal and spatial hetero-geneity, such as the surface thermal environment. The spatial and tem-poral heterogeneity of the contribution rate of geographical factors to ur-ban thermal environment is significant, but the experimental results also show that the method to study the spatial and temporal heterogeneity by means of Geographic Weighted Regression and Geographically and Tem-porally Weighted Regression has poor stability and robustness.