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Remote Sensing for Natural Resources    2023, Vol. 35 Issue (3) : 264-273     DOI: 10.6046/zrzyyg.2022217
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Influence of urban rivers and their surrounding land on the surface thermal environment
FENG Xiaogang1(), ZHAO Yi2, LI Meng1, ZHOU Zaihui1, LI Fengxia1, WANG Yuan1, YANG Yongquan3
1. College of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, China
2. CCC Urban and Rural Construction Planning and Design Institute, Wuhan 430050, China
3. Shandong Province Metallurgical Engineering Co., Ltd., Jinan 250101, China
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Abstract  

As an integral component of the urban ecosystem, water bodies hold considerable ecological significance for mitigating the urban heat island effect and the thermal environment of human habitat. With multi-temporal Landsat and SPOT data as experimental data, this study proposed a method for determining surface emissivity for mixed pixels based on the principle behind the construction of the support vector machine (SVM) optimal endmember subset. Then, this study employed the surface emissivity determination method to analyze the coupling relationship of the water bodies and surrounding land of the Bahe River with the surface temperature using a mono-window algorithm. The results are as follows: ① The SVM optimal endmember subset construction method for mixed pixels yielded an error of surface emissivity less than 0.005 (R = 0.832) relative to the MODIS LSE product. This result indicates that the method has high accuracy and thus can be used to extract surface emissivity. ② Over the past 27 years, the land types and local surface temperature patterns on both sides of the Bahe River have changed significantly, with a sharp increase in construction land and a significant warming trend. The effects of land use types surrounding the Bahe River on surface temperature varied in different periods, with construction land, grassland, water bodies, and forest land being the principal land use types affecting the thermal environment on both sides of the Bahe River. The cooling effects of water bodies, forest land, grassland, and cultivated land are in the order of water bodies > forest land > grassland > cultivated land. ③ The effects of land use types on both sides of the Bahe River on local temperatures exhibited spatial differences during the same period. To the east of the Bahe River, the water bodies, forest land, grassland, and cultivated land show significant cooling effects. In contrast, to the west of the river, only water bodies, forest land, and grassland showed significant cooling effects. This study contributes to the proper understanding of the influence of urban rivers on the local thermal environment, providing a scientific reference for mitigating the local thermal environment of urban rivers and their surrounding areas.
Keywords surface emissivity      thermal environment      urban heat island effect      water body      Bahe River     
ZTFLH:  TP79  
  TP701  
Issue Date: 19 September 2023
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Xiaogang FENG
Yi ZHAO
Meng LI
Zaihui ZHOU
Fengxia LI
Yuan WANG
Yongquan YANG
Cite this article:   
Xiaogang FENG,Yi ZHAO,Meng LI, et al. Influence of urban rivers and their surrounding land on the surface thermal environment[J]. Remote Sensing for Natural Resources, 2023, 35(3): 264-273.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2022217     OR     https://www.gtzyyg.com/EN/Y2023/V35/I3/264
Fig.1  Location of study area
辐射常量 Landsat5
TM6波段		 Landsat7
ETM+6
波段		 Landsat8
TIRS10
波段		 Landsat8
TIRS11
波段
K1/(W·m-2·sr-1·μm-1) 607.76 666.09 774.89 480.89
K2/K 1 284.30 1 282.71 1 321.08 1 201.14
Tab.1  Values of radiation constants of Landsat5/7/8 TIR bands
Fig.2  Land use of Bahe River in 1992, 2000, 2010 and 2019
年份 区位 建设用地 草地 耕地 林地 裸地 水体
1992年 灞河以东 15.549 8.046 7.873 2.240 0.601 0.774
灞河以西 21.219 8.159 4.001 1.986 0.747 0.621
2000年 灞河以东 15.899 7.257 6.849 3.412 0.914 0.752
灞河以西 21.221 7.455 4.179 2.423 0.811 0.644
2010年 灞河以东 17.849 5.221 4.511 5.412 1.393 0.699
灞河以西 21.014 5.143 4.275 5.145 0.655 0.541
2019年 灞河以东 18.124 4.548 6.486 4.672 0.583 0.675
灞河以西 21.375 4.597 5.851 5.105 0.226 0.592
Tab.2  Land use data of the Bahe River both banks(km2)
方法 平均值 标准差 平均
误差		 均方根
误差		 相关
系数
结合支持向量机的混合像元最优端元子集模型 0.980 64 0.004 1 0.002 1 0.004 6 0.832
MODIS LSE 0.986 41 0.003 2
Tab.3  Comparative analysis of surface emissivity
Fig.3  Land surface temperature of Bahe River in 1992,2000,2010 and 2019
Fig.4  Temperature variation from 1992 to 2019
Fig.5  Correlation between land use and surface temperature on both banks of Bahe River
Fig.6  Linear relationship between the proportion of cooling land area and surface temperature in different periods
Fig.7  Variation of land use and buffer zone temperature on both banks of the Bahe River in different years
Fig.8  Cooling effect of land use in buffer zones on both banks of the Bahe River in different periods
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