The present paper aims to introduce a remote sensing analysis of the seasonal dynamic variations of the urban thermal environmentof Lanzhou city. As is known, with the fast advancing pace of urbanization, theurban heat island (UHI) effect has become a conspicuous influential factor in deteriorating the urban eco-environment. As a typical valley city, Lanzhou has its own particular thermal environment since its evolution into a modern metropolis with its own specific characteristic urban landscape. As a result, the fast urbanization of the city has made its UHI ever more intensified. To study the UHIeffect of the city, it seems more realistic and instructive to quote four scenarios of the thermal infrared remote sensing data (Landsat TM images), collected in January, March, June and September in 2009, respectively, so as to analyze thespatial pattern of UHI in different seasons. And, for our purpose, we would like first of all to quote the 6S model to rectify atmosphere, and then apply the mono-window algorithm to illustrate the land surface temperature (LST) fluctuations, and, finally, a normalized method has been adopted to divide the temperature rating categories so as to obtain the LST maps and the LST rating maps. Trying to obtain the urban heat island ratio index, it is necessary to extract theurban heat field elements by using the image segmentation algorithms of the target-oriented fractal net evolution approach (FNEA), with the heat island seasonal pattern distinguished by G_i~* index spatial aggregation analysis. The landscape metrics were used to quantify the variations of the urban thermal landscape pattern. The following facts should be clarified via the appraisal system of temperature landscape: the UHI in the city can help to show the remarkable differences in a seasonal pattern. Generally speaking, the UHI of the city is likely to be most intensive in spring; it is getting moderate in summer and autumn, and becomes weakest in winter. So far as the landscape level is concerned, the most conspicuous landscape fragmentation of the urban thermal field appears in spring, whereas the second comes in summer, and, then, followed by autumn and winter. Thus, the thermal landscape pattern indicates significant diversity in their characteristic features with seasonal alteration. On the other hand,the dominant index of the urban thermal field has been found increasing from spring to winter, whereas the Shannon diversity index goes up from winter to spring. From the point of view of classification, it can be thought that the fragmentation of UHI tends to reach the maximal limit in summer, followed by winter and spring. Therefore, the fragmentation changing trend of cold islands turns out tobe consistent with its heat islands, however, the degree of fragmentation on thewhole proves less than the heat island. The second heat island tends to be continuous in winter and interrupted in spring. What is more, we have analyzed the correlation between NDVI and the land surface temperature. As a result, we have come to the conclusion that the heat island strength may imply a negative linearcorrelation with the urban vegetation coverage both in summer and autumn. Thus,it can be thought that the climate change and human activities should account for the seasonal changes of surface heat regime, to which the increase of urban green land may contribute to the reduction of the urban heat island effects.