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Journal of Arid Land
Journal of Arid Land  2022, Vol. 14 Issue (1): 14-33    DOI: 10.1007/s40333-022-0057-1
Research article     
Ecological environment quality evaluation of the Sahel region in Africa based on remote sensing ecological index
WU Shupu1,2, GAO Xin1,2,*(), LEI Jiaqiang1,2, ZHOU Na1,2, GUO Zengkun1,2, SHANG Baijun1,2
1State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2University of Chinese Academy of Sciences, Beijing 100049, China
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Abstract  

Long-term monitoring of the ecological environment changes is helpful for the protection of the ecological environment. Based on the ecological environment of the Sahel region in Africa, we established a remote sensing ecological index (RSEI) model for this region by combining dryness, moisture, greenness, and desertification indicators. Using the Moderate-resolution Imaging Spectroradiometer (MODIS) data in Google Earth Engine (GEE) platform, this study analyzed the ecological environment quality of the Sahel region during the period of 2001-2020. We used liner regression and fluctuation analysis methods to study the trend and fluctuation of RSEI, and utilized the stepwise regression approach to analyze the contribution of each indicator to the RSEI. Further, the correlation analysis was used to analyze the correlation between RSEI and precipitation, and Hurst index was applied to evaluate the change trend of RSEI in the future. The results show that RSEI of the Sahel region exhibited spatial heterogeneity. Specifically, it exhibited a decrease in gradient from south to north of the Sahel region. Moreover, RSEI in parts of the Sahel region presented non-zonal features. Different land-cover types demonstrated different RSEI values and changing trends. We found that RSEI and precipitation were positively correlated, suggesting that precipitation is the controlling factor of RSEI. The areas where RSEI values presented an increasing trend were slightly less than the areas where RSEI values presented a decreasing trend. In the Sahel region, the areas with the ecological environment characterized by continuous deterioration and continuous improvement accounted for 44.02% and 28.29% of the total study area, respectively, and the areas in which the ecological environment was changing from improvement to deterioration and from deterioration to improvement accounted for 12.42% and 15.26% of the whole area, respectively. In the face of the current ecological environment and future change trends of RSEI in the Sahel region, the research results provide a reference for the construction of the ''Green Great Wall'' (GGW) ecological environment project in Africa.

Key words： ecological environment      remote sensing ecological index      human activities      climate change      Sahel region      ''Green Great Wall'' (GGW)     
Received: 16 April 2021      Published: 31 January 2022
Corresponding Authors: * GAO Xin (E-mail: gaoxin@ms.xjb.ac.cn)
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WU Shupu
GAO Xin
LEI Jiaqiang
ZHOU Na
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SHANG Baijun
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WU Shupu, GAO Xin, LEI Jiaqiang, ZHOU Na, GUO Zengkun, SHANG Baijun. Ecological environment quality evaluation of the Sahel region in Africa based on remote sensing ecological index. Journal of Arid Land, 2022, 14(1): 14-33.

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http://jal.xjegi.com/10.1007/s40333-022-0057-1     OR     http://jal.xjegi.com/Y2022/V14/I1/14

Fig. 1 Location of the Sahel region in Africa (study area) and the paths of the ''Green Great Wall'' (GGW) ecological environment project
Product Band Time resolution Spatial resolution
MOD09A1 B1 (Red) 8 d 500 m
B2 (NIR 1)
B3 (Blue)
B4 (Green)
B5 (NIR 2)
B6 (SWIR 1)
B7 (SWIR 2)
MOD13A1 NDVI 16 d 500 m
MCD43A3 Black sky albedo 16 d 500 m
ERA5 Total precipitation 0.1°
GlobeLand30 10 a 30 m
JRC Monthly Water 30 d 30 m
Table 1 Data products used in the study and their spatial-temporal resolutions
Fig. 2 Correlation between albedo and normalized difference vegetation index (NDVI). The red line represents the best linear fit, and colors represent the frequency of point-to-point overlap
Fig. 3 Spatial distribution of mean reverse desert difference index (RDDI) in the Sahel region during the period of 2001-2020
Year Indicator PC1 PC2 PC3 PC4
2001 NDVI 0.39 -0.50 -0.42 0.65
WETI 0.52 0.55 0.50 0.43
RDDI -0.63 -0.27 0.52 0.51
NDSI -0.42 0.61 -0.56 0.37
Eigenvalue 0.1030 0.0052 0.0023 0.0001
Contribution rate (%) 93.15 4.68 2.07 0.10
2006 NDVI 0.43 -0.56 -0.41 0.57
WETI 0.53 0.53 0.48 0.46
RDDI -0.61 -0.30 0.50 0.53
NDSI -0.39 0.56 -0.59 0.43
Eigenvalue 0.1128 0.0068 0.0023 0.0001
Contribution rate (%) 92.45 5.57 1.87 0.11
2011 NDVI 0.42 -0.58 -0.36 0.60
WETI 0.53 0.57 0.44 0.45
RDDI -0.62 -0.24 0.53 0.53
NDSI -0.39 0.53 -0.63 0.41
Eigenvalue 0.1083 0.0064 0.0025 0.0001
Contribution rate (%) 92.26 5.47 2.16 0.11
2016 NDVI 0.39 -0.51 0.39 -0.65
WETI 0.52 0.59 -0.45 -0.42
RDDI -0.63 -0.23 -0.53 -0.52
NDSI -0.43 0.58 0.60 -0.35
Eigenvalue 0.1058 0.0054 0.0022 0.0001
Contribution rate (%) 93.13 4.79 1.98 0.10
Table 2 Principal component analysis (PCA) results
Fig. 4 Spatial distribution of the mean remote sensing ecological index (RSEI) during the period of 2001-2020 in the Sahel region as well as in the locations of regions A, B, and C
Fig. 5 High spatial resolution images of regions A (a), B (b), and C (c) from the Google Earth software. (a), sandy soil; (b), sparse vegetation; (c), trees and shrubs with high vegetation coverage.
Fig. 6 Spatial distribution of land-cover types in the Sahel region in 2020
Item Cultivated land Forest Grassland Shrubland Wetland Artificial surface Bare land
Area (×104 km2) 56.64 10.72 113.92 12.84 3.22 1.02 36.69
Percentage (%) 24.10 4.56 48.47 5.46 1.37 0.43 15.61
RSEI 0.41 0.54 0.40 0.49 0.64 0.39 0.27
Table 3 RESI values of different land-cover types in the Sahel region
Fig. 7 Spatial distribution of the correlation coefficients between RSEI and precipitation in the Sahel region during the period of 2001-2020
Fig. 8 Correlation between RSEI and normalized precipitation. The red line represents the best linear fit, and the colors represent the frequency of point-to-point overlap.
Fig. 9 Spatial distributions of the coefficient of variance (CV) values of RSEI (a) and different fluctuation levels of the CV values of RSEI (b) in the Sahel region during the period of 2001-2020
Fluctuation level CV Area proportion (%)
Very low fluctuation 0.02-0.07 28.99
Low fluctuation 0.07-0.10 31.48
Moderate fluctuation 0.10-0.13 22.75
High fluctuation 0.13-0.18 12.66
Very high fluctuation 0.18-0.49 4.13
Table 4 Fluctuation levels of the coefficient of variance (CV) values of RSEI in the Sahel region
Fig. 10 Spatial distributions of RSEI trend in the Sahel region during the period of 2001-2020. (a), the slope of RSEI change trend; (b), significance test of slope variation.
Country RSEI Area proportion of change trend (%)
Decreasing Increasing
Eritrea 0.43 48.84 51.16
Burkina Faso 0.46 68.42 31.58
Mali 0.39 53.57 46.43
Mauritania 0.26 70.00 30.00
Niger 0.26 56.12 43.88
Nigeria 0.44 48.53 51.47
Senegal 0.44 79.57 20.43
Sudan 0.45 43.98 56.02
Chad 0.36 45.00 55.00
Table 5 RSEI and its trends in different countries within the Sahel region
Fig. 11 Three dimensions scattered feature maps showing (a) the projection of the correlations among RSEI, RDDI, and normalized dry soil index (NDSI) and (b) the projection of the correlations among RSEI, NDVI, and wetness index (WETI)
Fig. 12 Spatial distributions of the slope of RSEI trend (a), the Hurst index (HI) (b), and the predicted RSEI change trend in the Sahel region in the future (c)
Fig. 13 Area proportions of predicated RSEI trend for different land-cover types in the Sahel region in the future. GL, grassland; BL, bare land; WL, wetland; FR, forest; CL, cultivated land; SL, shrubland; AS, artificial surface.
Fig. 14 Spatial distribution of CV values of precipitation in the Sahel region from 2000 to 2019
Fig. 15 Spatial distribution of precipitation variation trend (expressed as slope) in the Sahel region from 2000 to 2019
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