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Based on "Production-Living-Ecological" space theory, the productive, living and ecological spaces in Wuyuan county were classified based on the 30 m spatial resolution Landsat time-series images. The spatial and temporal characteristics of the three types of spaces were further analyzed. The kernel density estimation method was applied to explore the spatial features for the conversions among three types of spaces. In addition, to further identify the causes of these changes, Redundancy Analysis (RDA) method was applied to attribute the spatiotemporal changes to different socioeconomic factors. Results showed that the two indices, namely, mean area of patches and aggregation index, decreased in both living space and ecological space, while they increased in production space during 2002-2018. We revealed that the fragmentation and dispersion of production space and ecological space was enhanced due to increasing urban area and living spaces, which facilitated the splitting of the continuity of production space and ecological space. From the perspective of changing function, 56% and 44% of the increased living space area was from production space (mainly cropland) and ecological space (mainly forest or grassland), respectively. The living space area showed a significant (P<0.05) increasing trend, the ecological space area showed a non-significant increasing trend; while the production space area showed a significant decreasing trend. All this revealed that the urbanization rate was accelerated by the rapid growth of tourism economy, and the ecological environment improved in Wuyuan county during 2002-2018.

Urban expansion has been changing the urban thermal environment. Understanding the spatial distribution and temporal trends in the urban thermal environment is important in guiding sustainable urbanization. In this study, we focused on the land use/land cover (LULC) changes and urban expansion in Nanchang city, Jiangxi province, China. The four elements in the remote sensing-based ecological index (RSEI) are heat, greenness, dryness, and wetness, which correspond to the land surface temperature (LST), NDVI, NDBSI, and WET, respectively. According to the synthetic images of the average indices, we conducted temporal trend analysis together with statistical significance test for these images. We conducted partial correlation analyses between LST and NDVI, NDVSI, as well as WET. In addition, we used the LULC maps to analyze the multi-year trends in urban expansion. Then, we superimposed the trends in daytime and nighttime LST in summer on urban expansion area to extract the LST trends at sample locations. The results showed that LULC in Nanchang has substantially changed during the study period. The areas with statistically significant trends in LST coincided with the urban expansion areas. Land cover change was the main reason for LST change in Nanchang. In particular, artificial surfaces showed the greatest increase in LST; for per 100 km2 expansion in artificial surfaces, the daytime and nighttime LST increased by 0.8 °C and 0.7 °C, respectively. Among all the study land cover types, water bodies showed the greatest differences in LST change between the daytime and nighttime. There were statistically significant correlations between increases in LST and increases in NDBSI as well as decreases in NDVI and WET. In view of the considerable impact of urban expansion on the urban thermal environment, we urge local authorities to emphasize on urban greening when carrying out urban planning and construction.

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