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Remote Sensing for Natural Resources    2022, Vol. 34 Issue (2) : 203-214     DOI: 10.6046/zrzyyg.2021224
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MODIS-based comprehensive assessment and spatial-temporal change monitoring of ecological quality in Beijing-Tianjin-Hebei region
ZUO Lu1,2(), SUN Leigang1,2,3(), LU Junjing1,2, XU Quanhong1,2, LIU Jianfeng1,2, MA Xiaoqian1,2
1. Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhuang 050021, China
2. Hebei Engineering Research Center for Geographic Information Application, Shijiazhuang 050021, China
3. Julu Institute of Applied Technology, Xingtai 055250, China
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Abstract  

Ecological quality assessment is an important prerequisite for guaranteeing the harmony and stability of the production and life of human beings and the ecological environment and for achieving the sustainable development of regional social economy. It has become a new trend to quickly, accurately, and objectively assess the regional ecological quality using use remote sensing technology. This study used the MODIS data of the Beijing-Tianjin-Hebei region in 2001, 2010, and 2019 to extract four important indices, namely, NDVI (greenness), LSM (humidity), NDBSI (dryness), and LST (heat). Then, this study obtained the MODIS remote sensing ecological index (RSEIM) using the principal component analysis method to conduct a comprehensive assessment and change monitoring of the ecological quality in the Beijing-Tianjin-Hebei region over the past 20 years. The results are as follows. ① The ecological quality of the Beijing-Tianjin-Hebei region shows distinct regional differences. The Yanshan Mountain in the north and the Taihang Mountain in the west have high ecological quality, while the Zhangjiakou area in the northwestern part of Hebei Province and the urban center in the southeastern part of Hebei Province suffer low ecological quality. ② In 2001, 2010, and 2019, the average RSEIM of the Beijing-Tianjin-Hebei region was 0.556, 0.583, and 0.527, respectively, with the overall ecological quality showing a downward trend. ③ From 2001 to 2019, the area with improved and degraded ecological quality in the Beijing-Tianjin-Hebei region accounted for 20.18% and 35.69% respectively, and the ecological quality in this region showed a pattern of improvement in the northwest and degradation in the southeast. The main reasons for the ecological improvement in the northwestern part of the region are the changes in water and heat conditions, such as an increase in precipitation and temperature, and a series of man-made protection measures. The reasons for ecological degradation in the southeastern part of the Beijing-Tianjin-Hebei region mainly include the rapid advancement of urbanization and the enhancement of social and economic activities. The comprehensive assessment of regional ecological quality can be effectively achieved based on MODIS data, thus providing a reference for the green and high-quality development of regional social economy.
Keywords ecological quality      comprehensive evaluation      remote sensing monitoring      MODIS      spatial-temporal changes     
ZTFLH:  TP79  
Corresponding Authors: SUN Leigang     E-mail: zuol.14b@igsnrr.ac.cn;sunleigang3s@163.com
Issue Date: 20 June 2022
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Lu ZUO
Leigang SUN
Junjing LU
Quanhong XU
Jianfeng LIU
Xiaoqian MA
Cite this article:   
Lu ZUO,Leigang SUN,Junjing LU, et al. MODIS-based comprehensive assessment and spatial-temporal change monitoring of ecological quality in Beijing-Tianjin-Hebei region[J]. Remote Sensing for Natural Resources, 2022, 34(2): 203-214.
URL:  
https://www.gtzyyg.com/EN/10.6046/zrzyyg.2021224     OR     https://www.gtzyyg.com/EN/Y2022/V34/I2/203
指标 2001年 2010年 2019年
PC1 PC2 PC3 PC4 PC1 PC2 PC3 PC4 PC1 PC2 PC3 PC4
LST -0.353 0.923 0.139 -0.063 -0.333 0.933 0.122 -0.059 -0.392 0.914 0.068 -0.085
NDSIM -0.543 -0.327 0.538 -0.556 -0.530 -0.300 0.605 -0.513 -0.512 -0.304 0.735 -0.325
SWCI 0.552 0.180 -0.158 -0.799 0.560 0.163 -0.110 -0.804 0.561 0.158 0.099 -0.806
NDVI 0.525 0.093 0.816 0.222 0.543 0.111 0.779 0.294 0.519 0.218 0.667 0.487
特征值 0.217 0.020 0.004 0.002 0.195 0.019 0.005 0.002 0.176 0.029 0.005 0.003
特征值贡献率/% 89.31 8.25 1.77 0.67 88.33 8.76 2.03 0.88 82.81 13.74 2.19 1.26
Tab.1  Principal component analysis results of the indicators
指标 2001年 2010年 2019年
均值 标准差 均值 标准差 均值 标准差
LST 0.622 0.210 0.605 0.196 0.646 0.227
NDSIM 0.439 0.260 0.424 0.242 0.466 0.227
SWCI 0.549 0.260 0.573 0.251 0.525 0.241
NDVI 0.607 0.251 0.635 0.246 0.618 0.227
RSEIM 0.556 0.257 0.583 0.244 0.527 0.239
Tab.2  Statistics of each indictor and RSEIM
指标 2001年 2010年 2019年
LST NDSIM SWCI NDVI RSEIM LST NDSIM SWCI NDVI RSEIM LST NDSIM SWCI NDVI RSEIM
LST 1.000 -0.779 1.000 -0.745 1.000 -0.722
NDSIM 0.656 1.000 -0.971 0.618 1.000 -0.966 0.533 1.000 -0.945
SWCI -0.711 -0.970 1.000 0.987 -0.678 -0.959 1.000 0.986 -0.627 -0.931 1.000 0.979
NDVI -0.721 -0.930 0.954 1.000 0.975 -0.680 -0.921 0.952 1.000 0.974 -0.580 -0.909 0.943 1.000 0.959
平均相关度① 0.696 0.852 0.879 0.868 0.928 0.658 0.833 0.863 0.851 0.918 0.580 0.791 0.834 0.811 0.901
3 a均值 LST=0.645,NDSIM=0.825,SWCI=0.858,NDVI=0.843,RSEIM=0.916
Tab.3  Statistical results of correlation coefficient between each indictor and RSEIM
Fig.1  Spatial distribution of RSEIM in the study area
Fig.2  Area and proportion of ecological quality of each grade in the study area from 2001 to 2019
Fig.3  Spatial distribution of RSEIM change in the study area
变化类别 极差 2001—2010年 2010—2019年 2001—2019年
面积/km2 占比/% 面积/km2 占比/% 面积/km2 占比/%
明显变差 -4,-3 225.72 0.10 712.40 0.33 1502.91 0.69
变差 -2,-1 32 838.31 15.13 76 358.30 35.18 75 967.23 35.00
不变 0 128 285.30 59.11 119 116.43 54.88 95 766.28 44.13
变好 1,2 55 369.04 25.51 20 841.91 9.60 42 920.70 19.78
明显变好 3,4 314.73 0.15 4.06 0.00 875.98 0.40
Tab.4  Area and proportion of ecological quality change in the study area from 2001 to 2019
Fig.4  Statistics of RSEIM of cities in the study area from 2001 to 2019
Fig.5  Change trend of climate factors form 2001 to 2019
Fig.6  Comparison of social and economic factors of cities in the study area from 2001 to 2019
指标 2001年 2010年 2019年
RSEIM LST NDVI RSEIM LST NDVI RSEIM LST NDVI
干度 NDSIM -0.971 0.656 -0.930 -0.966 0.618 -0.921 -0.945 0.533 -0.909
NDSI -0.916 0.561 -0.876 -0.908 0.523 -0.864 -0.857 0.403 -0.850
湿度 SWCI 0.987 -0.711 0.954 0.986 -0.678 0.952 0.979 -0.627 0.943
Wet 0.775 -0.549 0.685 0.736 -0.486 0.651 0.620 -0.307 0.559
Tab.5  Correlation coefficient between dryness, wetness before and after improvement and remote sensing ecological index, heat and greenness
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