摘要 : The research on the impact of land cover changes on the thermal environment is crucial to environmental monitoring. Land surface temperature (LST) is often used as the main parameter to analyze the thermal environment. As the prim... 展开 The research on the impact of land cover changes on the thermal environment is crucial to environmental monitoring. Land surface temperature (LST) is often used as the main parameter to analyze the thermal environment. As the primary land cover type, "cropland" is the main factor affecting the LST. Previous studies investigated the effects of cropland with other land cover types on the LST but ignored the changes within cropland. Furthermore, inter-annual changes of crop types in the cropland often occur. With the growth of the crops, their impact on LST also change. Therefore, it is necessary to understand how cropland changes affect the LST. The traditional comparison method based on a single time image is not suitable for evaluating the impact of the different crops during the whole growth period because single-phase information cannot reflect the changing process of crop influence. To address this issue, this paper proposes a cumulative land surface temperature index (cLST) based on multi-temporal images to evaluate the yearly impact of cropland changes. Results indicate that different crops have different effects on the thermal environment, and the annual cLST of cotton extracted from MODIS is higher than that of corn, sorghum, and winter wheat cropland. Also, the changing amplitude of the annual cLST is mainly related to the inter-annual cropland area ratio change (R = 0.85 for winter wheat to cotton, R = 0.75 for corn to cotton) in the study area, indicating that the overall change from corn and winter wheat to cotton cropland increases the annual cLST. The effect of cotton-sorghum and winter wheat-corn change is not significant. By comparing the contribution rate, it is found that the annual cLST is more affected by the cotton-winter wheat change (35%) than air temperature (26%). The method proposed in this paper helps to reveal the impact of cropland changes on LST, and the prediction of regional climate changes. 收起