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Remote Sensing for Land & Resources    2020, Vol. 32 Issue (4) : 209-218     DOI: 10.6046/gtzyyg.2020.04.26
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Urban ecological environment evaluation based on Tiangong-2 and Landsat8 data
MUHADAISI Ariken1,2(), ZHANG Fei1,2,3(), LIU Kang4, AYINUER Yushanjiang1,2
1. Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China
2. Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China
3. Engineering Research Center of Central Asia Geoinformation Development and Utilization, National Administration of Surveying, Mapping and Geoinformation, Urumqi 830002, China
4. Technology and Engineering Center for Space Utilization, Key Laboratory of Space Utilization, Chinese Academy of Sciences, Beijing 100094, China
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Abstract  

At present, China has entered into the rapid development stage of urbanization, and urbanization is exerting its positive effect. Such a situation inevitably brings negative effects, but remote sensing technique can quickly, accurately, objectively and quantitatively reveal the present situation of the regional ecological environment quality. Bohu County is one of the most typical areas in arid oasis in Northwest China. Based on Tiangong-2 wide-band images spectrometer and Landsat8 images, the authors constructed a multi-factor comprehensive index RSEI evaluation model in combination with principal components, which was established to evaluate the ecological environment of Bohu County. Additionally, the authors explored the application of Tiangong-2 wide-band images to ecological environment monitoring. The result shows that the greenness (NDVI) and wetness (WET) have positive effects on promoting the ecological environment quality, while the heat (LST) and dryness (NDBI) have restraining effects on ecological environment quality. Greenness (NDVI) has a greater impact on the ecological environment than the other three indicators. In 2018, the RSEI poor grade (0 ~ 0.2) in Bohu County was mainly distributed over urban land and unused land in the north;the fair grade (0.2 ~ 0.4) was mainly distributed among mountains and sandy land. Quantitative and qualitative analysis shows that the driving factors included urban economic development, higher average temperature, greater evaporation, longer sunshine and other natural factors. The ecological environment of wetland and cultivated land was between good (0.6 ~ 0.8) and excellent (0.8 ~ 1.0), indicating that the ecological environment quality of this region was good. According to the spatial differentiation characteristics of ecological and environmental quality, the ecological and environmental quality of the research area in 2018 had a strong positive correlation and certain internal relations, and tended to cluster. This study offers important results and information for planning of regional ecological environment protection and development.
Keywords Tiangong-2 WIS      principal component analysis      RSEI      urbanization     
:  TP79  
Corresponding Authors: ZHANG Fei     E-mail: 18240988292@163.com;zhangfei3s@163.com
Issue Date: 23 December 2020
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Ariken MUHADAISI
Fei ZHANG
Kang LIU
Yushanjiang AYINUER
Cite this article:   
Ariken MUHADAISI,Fei ZHANG,Kang LIU, et al. Urban ecological environment evaluation based on Tiangong-2 and Landsat8 data[J]. Remote Sensing for Land & Resources, 2020, 32(4): 209-218.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020.04.26     OR     https://www.gtzyyg.com/EN/Y2020/V32/I4/209
Fig.1  Location of study area
波段 可见近红外谱段 短波红
外谱段		 热红外
谱段
通道范围/μm V1: 0.970~0.990 V8: 0.655~0.675 S1: 1.230~
1.250		 T1: 8.125~
8.825
V2: 0.930~0.950 V9: 0.610~0.630 S2: 1.630~
1.650		 T2: 8.925~
9.275
V3: 0.895~0.915 V10: 0.555~0.575
V4: 0.845~0.885 V11: 0.510~0.530
V5: 0.810~0.830 V12: 0.480~0.500
V6: 0.740~0.760 V13: 0.433~0.453
V7: 0.6775~0.6875 V14: 0.403~0.423
空间分辨率/m 100 200 400
Tab.1  Wide band imager index of Tiangong-2
Fig.2  RSEI flow chart of calculation
年份 指标 PC1 PC2 PC3 PC4
2018年 绿度(NDVI) 0.936 0.174 0.025 0.306
干度(NDBI) -0.828 0.218 0.503 0.117
湿度(WET) 0.737 0.608 0.216 -0.200
热度(LST) -0.642 0.671 -0.365 -0.064
特征值 2.517 0.898 0.434 0.151
贡献率/% 62.922 22.455 10.839 3.785
Tab.2  Result of PCAs
指标 绿度
(NDVI)		 湿度
(WET)		 干度
(NDBI)		 热度
(LST)		 RSEI
绿度
(NDVI)		 1.000 0.783**① -0.723** -0.669** 0.935**
湿度
(WET)		 0.783** 1.000 -0.747** -0.667** 0.842**
干度
(NDBI)		 -0.723** -0.747** 1.000 0.52** -0.858**
热度
(LST)		 -0.669** -0.667** 0.52** 1.000 -0.683**
RSEI 0.935** 0.842** -0.858** -0.683** 1.000
Tab.3  Correlation analysis of RSEI and four indicators
指标 均值 标准差
绿度(NDVI) 0.574 0.148
干度(NDBI) 0.365 0.117
湿度(WET) 0.423 0.028
热度(LST) 0.779 0.084
RSEI 0.393 0.291
Tab.4  Statistical value of RSEI and indicators
RSEI等级 划分依据 面积/km2 比例/%
差 [0,0.2) 1 012.80 38.83
较差 [0.2,0.4) 616.22 23.62
中 [0.4,0.6) 158.19 6.06
良 [0.6,0.8) 415.36 15.92
优 [0.8,1.0] 405.79 15.56
Tab.5  Scale and proportion of ecological environment level in Bohu
Fig.3  LUCC and RSEI result grade diagram of Bohu in 2018
Fig.4  Moran scatter plots of the RSEI of Bohu in 2018
Fig.5  LISA cluster map and significance map
Fig.6  3D-scatter plots of feature space
气象指标 1月 2月 3月 4月 5月 6月 7月 8月 9月 10月 11月 12月 合计 年平均
平均气温/℃ -10.7 -5.3 8.3 14.1 18.2 22.9 23.9 22.9 16.3 8.8 0.1 -10.2 109.3 9.11
平均相对湿度/% 68 62 50 34 40 46 49 56 52 55 67 65 644 53.67
降水量/mm 0.8 0.1 5.6 0 25.2 4.7 1 15.4 1.9 14.3 0.2 0 69.2 5.77
蒸发量/mm 17.6 39.2 146 3 276.6 3 276.6 3 276.6 3 276.6 3 276.6 3 276.6 3 276.6 44.9 19.4 23 203.3 1 933.61
平均风速/(m.s-1) 1.4 1.5 2.2 2.8 3 2.4 2.3 2.1 2.1 1.8 1.7 1.6 24.9 2.08
日照时数/h 201 201.3 245.9 273.3 301.6 266.6 290.5 296.7 309.8 275.7 199.3 195.3 3057 254.75
Tab.6  Climate characteristic value of Bohu in 2018
Fig.7  Social and economic development of Bohu from 2014 to 2018
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