Since its establishment as the capital of the Ningxia Hui Autonomous Region, the city of Yinchuan has been facing an increasingly serious urban-heat-island effect due to rapid urbanization. To provide insight into the city’s changes, thermal environment variation, and the response relationship of urban built-up area expansion and the thermal environment in Yinchuan during the past 28 years, this study used Landsat 5 TM and Landsat 8 OLI im? age data for 1989, 1999, 2010, and 2017 to extract urban built-up area using the index-based built-up index, and the expansion intensity, speed, compactness index, fractal dimension, and center of gravity from urban morphology evolution indices such as AGR, AGA, BCI for the same period. The study also used land surface temperature (LST) values retrieved through the thermal infrared bands based on a radiative transfer equation, and calculated the ur? ban-heat-island ratio index (URI) for these four years through normalized LST. Lastly, the space-time evolution of urban built-up area expansion and thermal environment variation were studied and their response relationship was discussed. The results showed the following: (1) During 1989-2017, urban built-up area expanded rapidly, increas? ing by nearly 506.13 km2. The expansion intensity and speed of different periods varied greatly; however, they pre? sented periodical characteristics with slow-rapid-steady expansion phases. The compactness index showed an up? ward trend while the fractal dimension showed a downward trend overall, which demonstrated that the urban spatial form tended to be compact and stable. The city expanded to the east and north and the city’s center of gravity shift? ed nearly 5.54 km to the northeast. (2) The heat island area gradually increased with urban expansion, with areas of higher temperature, high temperature, and extremely high temperature increasing by factors of approximately 9, 10, and 4 over the past 28 years, respectively. However, the heat intensity transferred from the region of high tempera? ture and extremely high temperature to the higher temperature region, thus relieving the heat island effect. The heat island’s spatial distribution showed that it spread from the old town area of Xingqing district to Helan County and Xixia district. Meanwhile, the Xingqing district heat island gradually evolved into an independent small secondary island, alleviating the intense overall heat island effect of Yinchuan, and URI showed an increasing trend first and then a decreasing trend but an overall increase. (3) The spatial distribution and expansion direction of the high tem? perature region of the LST is highly consistent with urban expansion. In addition, urban land, buildings, and bare land could increase LST, whereas grass land and water could decrease it, meaning that urban green spaces and wa? ter were able to effectively alleviate the heat island effect, with water demonstrating greater LST decreases than ur? ban green spaces.
[1] Department of Economic and Social Affairs (UN DESA), United Nations. World urbanization prospects: The 2014 revision high⁃ lights[R]. New York: United Nations, Department of Economic and Social Affairs: 2014, 20. [2] 鲍超, 邹建军. 中国西北地区城镇化质量的时空变化分析[J]. 干 旱 区 地 理, 2019, 42(5): 1141- 1152. [BAO Chao, ZOU Jianjun. Spatiotemporal variations of urbanization quality in northwest Chi⁃ na[J]. Arid Land Geography, 2019, 42(5): 1141-1152. ] [3] 姚 远, 陈 曦, 钱 静. 城 市 地 表 热 环 境 研 究 进 展 [J]. 生 态 学 报, 2018, 38(3): 1134-1147. [YAO Yuan, CHEN Xi, QIAN Jing. Re⁃ search progress on the thermal environment of the urban surfaces [J]. Acta Ecologica Sinica, 2018, 38(3): 1134-1147. ] [4] 李瑶, 潘竟虎. 基于 Landsat 8 劈窗算法与混合光谱分解的城市 热岛空间格局分析——以兰州市中心城区为例[J]. 干旱区地 理, 2015, 38(1): 111- 119. [LI Yao, PAN Jinghu. Spatial pattern on urban heat environment using split window algorithm and spec⁃ tral mixture analysis based on Landsat 8 images: A case of Lan⁃ zhou City[J]. Arid Land Geography, 2015, 38(1): 111-119. ] [5] 祝新明, 王旭红, 周永芳, 等. 建成区扩张下的西安市热环境空 间分异性[J]. 生态学杂志, 2017, 36(12): 3574-3583. [ZHU Xin⁃ ming, WANG Xuhong, ZHOU Yongfang et al. Spatial variability of thermal environment in Xi’an under the build-up area expansion [J]. Chinese Journal of Ecology, 2017,3 6(12): 3574-3583. ] [6] MADANIAN M, SOFFIANIAN A R, KOUPAI S S, et al. Analyz⁃ ing the effects of urban expansion on land surface temperature pat⁃ terns by landscape metrics: A case study of Isfahan City, Iran[J]. Environmental Monitoring & Assessment, 2018, 190(4): 189. [7] BOYAN L, WEI W, LIANG B, et al. Effects of spatio- temporal landscape patterns on land surface temperature: A case study of Xi’an City, China[J]. Environmental Monitoring and Assessment, 2018, 190(7): 419. [8] 李乐, 徐涵秋. 杭州市城市空间扩展及其热环境变化[J]. 遥感技 术与应用, 2014, 29(2): 264-272. [LI Le, XU Hanqiu. Urban ex⁃ pansion and thermal environment changes in Hangzhou City of east of China[J]. Remote Sensing Technology and Application, 2014, 29(2): 264-272. ] [9] 庄元, 薛东前, 王剑. 半干旱区典型工业城市热岛时空分布及演 变特征——以包头市为例[J]. 干旱区地理, 2017, 40(2): 276- 283. [ZHUANG Yuan, XUE Dongqian, WANG Jian. Spatial- tem⁃ poral evolution of urban heat island in semiarid typical industrial city: A case of Baotou City[J]. Arid Land Geography, 2017, 40(2): 276-283. ] [10] 吕荣芳, 王浩, 王鹏龙, 等. 近 25 a 银川市城市化进程中热力景 观 格 局 演 变 分 析 [J]. 干 旱 区 研 究, 2016, 33(4): 860- 868. [LV Rongfang, WANG Hao, WANG Penglong, et al. Evolution of ther⁃ mal landscape pattern in urbanization of Yinchuan City in recent 25 years[J]. Arid Zone Research, 2016, 33(4): 860-868. ] [11] 孙鹏, 韩沐汶, 白林波, 等. 基于 Landsat TM/ETM 的银川市热岛 效 应 时 空 变 化 研 究 [J]. 水 土 保 持 研 究, 2014, 21(1): 290- 293. [SUN Peng, HAN Muwen, BAI Linbo, et al. Study on spatiotempo⁃ ral variation of heat island effect based on Landsat TM/ETM in Yinchuan City[J]. Research of Soil and Water Conservation, 2014, 21(1): 290-293. ] [12] 杨存建, 周成虎. TM 影像的居民地信息提取方法研究[J]. 遥感 学报, 2000, 4(2): 146-150. [YANG Cunjian, ZHOU Chenghu. Ex⁃ tracting residential areas on the TM imagery[J]. Journal of Remote Sensing, 2000, 4(2): 146-150. ] [13] ZHA Y, GAO J, NI S. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery[J]. Interna⁃ tional Journal of Remote Sensing, 2003, 24(3): 583-594. [14] XU Hanqiu. A new index for delineating built-up land features in satellite imagery[J]. International Journal of Remote Sensing, 2008, 29(14): 4269-4276. [15] 徐涵秋. 利用改进的归一化差异水体指数(MNDWI)提取水体信 息 的 研 究 [J]. 遥 感 学 报, 2005, 9(5): 589- 595. [XU Hanqiu. A study on information extraction of water body with the modified normalized difference water index (MNDWI)[J]. Journal of Remote Sensing, 2005, 9(5): 589-595. ] [16] HUETE A R. A soil- adjusted vegetation index (SAVI) [J]. Remote Sensing of Environment, 1988, 25(3): 295-309. [17] 杨立国, 周国华. 怀化城市形态演变特征及影响因素[J]. 地理科 学 进 展, 2010, 29(5): 627- 632. [YANG Liguo, ZHOU Guohua. Evolution characteristics of the urban morphology and its forming mechanism in Huaihua[J]. Progress in Geography, 2010, 29(5): 627-632.] [18] 潘竟虎, 韩文超. 兰州中心城区用地扩展及其热岛响应的遥感 分 析 [J]. 生 态 学 杂 志, 2011, 30(11): 2597- 2603. [PAN Jinghu, HAN Wenchao. Urban expansion and its heat island response in Lanzhou City based on remote sensing analysis [J]. Chinese Jour⁃ nal of Ecology, 2011, 30(11): 2597-2603. ] [19] BATTY M. Exploring isovist fields: space and shape in architectur⁃ al and urban morphology[J]. Environment and Planning B: Plan⁃ ning and Design, 2001, 28(1): 123-150. [20] SOBRINO J A, JIMÉNEZ-MUÑOZ J C, PAOLINI L. Land surface temperature retrieval from LANDSAT TM 5 [J]. Remote Sensing of Environment, 2004, 90(4): 434-440. [21] ARTIS D A, CARNAHAN W H. Survey of emissivity variability in thermograph of urban areas [J]. Remote Sensing of Environment, 1982, 12(4): 313-329. [22] JIMÉNEZ-MUÑOZ J C, SOBRINO J A. A generalized single chan⁃ nel method for retrieving land surface temperature from remote sensing data [J]. Journal of Geophysical Research, 2003, 108 (D22): 1-9. [23] QIN Z H, KARNIELI A, BERLINER P. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel- Egypt border region [J]. International Journal of Remote Sensing, 2001, 22(18): 3719-3746. [24] NICHOL J. Remote sensing of urban heat islands by day and night [J]. Photogrammetric Engineering and Remote Sensing, 2005, 71 (6): 613-621. [25] BARSI J A, SCHOTT J R, HOOK S J, et al. Landsat-8 thermal in⁃ frared sensor (TIRS) vicarious radiometric calibration[J]. Remote Sensing, 2014, 6(11): 11607-11626. [26] YU X, GUO X, WU Z. Land surface temperature retrieval from Landsat 8 TIRS: Comparison between radiative transfer equation- based method, split window algorithm and single channel method [J]. Remote Sensing,2014, 6(10): 9829-9852. [27] 徐涵秋, 陈本清. 不同时相的遥感热红外图像在研究城市热岛 变化中的处理方法[J]. 遥感技术与应用, 2003, (3): 129-133. [XU Hanqiu, CHEN Benqing. An image processing technique for the study of urban heat island changes using different seasonal re⁃ mote sensing data [J]. Remote Sensing Technology and Applica⁃ tion, 2003, (3): 129-133. ] [28] 栾庆祖, 叶彩华, 刘勇洪, 等. 城市绿地对周边热环境影响遥感 研究—以北京为例[J]. 生态环境学报, 2014, (2): 252-261. [LU⁃ AN Qingzu, YE Caihua, LIU Yonghong, et al. Effect of urban green land on thermal environment of surroundings based on re⁃ mote sensing: A case study of Beijing, China[J]. Ecology and Envi⁃ ronmental Sciences, 2014, (2): 252-261. ]
