基于GEE的干旱区县域生态环境质量时空变化及驱动力分析——以阿拉善左旗为例

doi:10.13866/j.azr.2025.02.15

干旱区研究 ›› 2025, Vol. 42 ›› Issue (2): 360-371.doi: 10.13866/j.azr.2025.02.15 cstr: 32277.14.AZR.20250215

基于GEE的干旱区县域生态环境质量时空变化及驱动力分析——以阿拉善左旗为例

李琪¹(), 党国锋¹, 鱼腾飞²(), 张浪¹, 陈薇宇²

1.西北师范大学地理与环境科学学院，甘肃兰州 730070
2.中国科学院西北生态环境资源研究院阿拉善荒漠生态水文试验研究站，甘肃兰州 730000

收稿日期:2024-08-15 修回日期:2024-12-17 出版日期:2025-02-15 发布日期:2025-02-21
通讯作者: 鱼腾飞. E-mail: yutf@lzb.ac.cn
作者简介:李琪（1995-），男，硕士研究生，主要从事生态环境遥感监测研究. E-mail: 176924194@qq.com
基金资助:
中国科学院“西部青年学者”重点项目([2020]82);内蒙古自治区关键技术攻关项目(2020GG0306);阿拉善盟科技计划项目(AMY2020-18);甘肃省自然科学基金项目(21JR7RA038);阿拉善盟林业和草原局自选项目(2021LC0001)

Spatial-temporal variation and driving forces analysis of ecological environment quality in arid counties based on GEE: A case study of Alxa Left Banner

LI Qi¹(), DANG Guofeng¹, YU Tengfei²(), ZHANG Lang¹, CHEN Weiyu²

1. College of Geography and Environment Science, Northwest Normal University, Lanzhou 730070, Gansu, China
2. Alax Desert Eco-hydrological Experimental Research Station, Northwest institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, Gansu, China

Received:2024-08-15 Revised:2024-12-17 Published:2025-02-15 Online:2025-02-21

摘要/Abstract

摘要：

客观、准确、及时地评价生态环境质量时空变化及驱动力对生态环境保护方案与政策的制定具有重要意义。以阿拉善左旗为例，基于Google Earth Engine（GEE）平台构建了干旱区改进的遥感生态指数（Remote Sensing-based Ecological Index，RSEI），分析了近30 a（1991—2021年）RSEI的时空变化及其驱动力。结果表明：（1）近30 a阿拉善左旗RSEI呈波动上升趋势，其中2012年RSEI最大（0.360），2007年最小（0.264）。（2）近30 a阿拉善左旗生态环境改善区面积（RSEI>0.2，3.15%）大于退化区（RSEI<-0.2，2.48%），无变化区面积最大（-0.2<RSEI<0.2，94.37%）。RSEI较差的区域主要分布在裸地区域，而林地、草地、耕地、不透水面区域RSEI逐渐变好。（3）1991—2021年Global Morans’I指数在0.600~0.650之间，表现出较高的聚集特征。（4）从线性混合效应模型的结果来看，引起RSEI变化的原因，人类活动占89%，气候变化占11%。综上所述，近30 a来阿拉善荒漠区生态环境质量整体逐步改善，腾格里沙漠北缘局部地区生态环境质量提升显著，人类活动尤其是飞播造林工程起到了关键作用。

关键词: 遥感生态指数, GEE, 空间自相关, 干旱区

Abstract:

Objective, accurate, and timely evaluation of the spatiotemporal changes and driving forces of ecological environment quality is of great significance for the formulation of ecological protection plans and policies. Taking Alxa Left Banner as an example, this study constructs a Remote Sensing-based Ecological Index (RSEI) for arid regions based on the Google Earth Engine (GEE) platform and analyzes the spatiotemporal changes and driving forces of RSEI over the past 30 years (1991-2021). The study shows that: (1) Over the past 30 years, the RSEI of Alxa Left Banner has shown a fluctuating upward trend, with the maximum RSEI in 2012 (0.360) and the minimum in 2007 (0.264). (2) Over the past 30 years, the area of ecological improvement (RSEI>0.2, 3.15%) in Alxa Left Banner is larger than the area of degradation (RSEI<-0.2, 2.48%), with the largest area showing no change (-0.2<RSEI<0.2, 94.37%). Regions with poorer RSEI are mainly distributed in bare land areas, while the RSEI of forest, grassland, farmland, and impervious surface areas has gradually improved. (3) From 1991 to 2021, the Global Moran’s I index ranged between 0.600 and 0.650, indicating a high degree of clustering. (4) According to the results of the linear mixed-effects model, human activities account for 89% of the changes in RSEI, while climate change accounts for 11%. In summary, over the past 30 years, the overall ecological environment quality in the Alxa Desert area has gradually improved, with significant improvements in the northern edge of the Tengger Desert, primarily due to human activities, especially the aerial seeding afforestation projects.

Key words: remote sensing-based ecological index, GEE, spatial autocorrelation, arid region

李琪, 党国锋, 鱼腾飞, 张浪, 陈薇宇. 基于GEE的干旱区县域生态环境质量时空变化及驱动力分析——以阿拉善左旗为例[J]. 干旱区研究, 2025, 42(2): 360-371.

LI Qi, DANG Guofeng, YU Tengfei, ZHANG Lang, CHEN Weiyu. Spatial-temporal variation and driving forces analysis of ecological environment quality in arid counties based on GEE: A case study of Alxa Left Banner[J]. Arid Zone Research, 2025, 42(2): 360-371.

图/表 13

图1

表1

图2

表2

各指标计算公式"

指标	计算方法	描述
NDVI	$N D V I = ρ N I R - ρ R e d ρ N I R + ρ N I R$	$ρ B l u e$ 、 $ρ G r e e n$ 、 $ρ R e d$ 、 $ρ N I R$ 、 $ρ S W I R 1$ 、 $ρ S W I R 2$ 分别表示Landsat TM、 ETM+、OLI影像的蓝色、绿色、红色、近红外、短波红外1和短波红外2波段的反射率。
WET	$W E T T M = 0.0315 ρ B l u e + 0.2021 ρ G r e e n + 0.3102 ρ R e d + 0.1594 ρ N I R - 0.6806 ρ S W I R 1 - 0.6109 ρ S W I R 2$ $W E T E T M + = 0.0315 ρ B l u e + 0.2021 ρ G r e e n + 0.0926 ρ R e d + 0.0656 ρ N I R - 0.7629 ρ S W I R 1 - 0.5388 ρ S W I R 2$ $W E T O L I = 0.1511 ρ B l u e + 0.1972 ρ G r e e n + 0.3283 ρ R e d + 0.3407 ρ N I R - 0.7117 ρ S W I R 1 - 0.4559 ρ S W I R 2$
SI	$S I = ρ B l u e + ρ R e d$
NDBSI	$I B I = 2 ρ S W I R 1 ρ S W I R 1 + ρ N I R - ρ N I R / ρ N I R + ρ R e d + ρ G r e e n / ρ G r e e n + ρ S W I R 1 2 ρ S W I R 1 ρ S W I R 1 + ρ N I R + ρ N I R / ρ N I R + ρ R e d + ρ G r e e n / ρ G r e e n + ρ S W I R 1$ $B S I = ρ S W I R 1 + ρ R e d - ρ B l u e + ρ N I R ρ S W I R 1 + ρ R e d + ρ B l u e + ρ N I R$ $N D B S I = I B I + S I 2$

表2

图3

图4

图5

图6

表3

表4

表5

图7

图8

参考文献 35

[1]	Yu H, Wang L, Zhang J, et al. A global drought-aridity index: The spatiotemporal standardized precipitation evapotranspiration index[J]. Ecological Indicators, 2023, 153: 110484.
[2]	程静, 王鹏, 陈红翔, 等. 半干旱区生态风险时空演变及其影响因素的地理探测——以宁夏盐池县为例[J]. 干旱区地理, 2022, 45(5): 1637-1648. doi: 10.12118/j.issn.1000-6060.2022.033
	[Cheng Jing, Wang Peng, Chen Hongxiang, et al. Geographical exploration of the spatial and temporal evolution of ecological risk and its influencing factors in semi-arid regions: A case of Yanchi County in Ningxia[J]. Arid Land Geography, 2022, 45(5): 1637-1648. ] doi: 10.12118/j.issn.1000-6060.2022.033
[3]	Pravalie R. Drylands extent and environmental issues. A global approach[J]. Earth-Science Reviews, 2016, 161: 259-278.
[4]	Liu H, Li X J, Mao F J, et al. Spatiotemporal evolution of fractional vegetation cover and its response to climate change based on MODIS data in the subtropical region of China[J]. Remote Sensing, 2021, 13(5): 913.
[5]	Chen X, Liu C, Yu X. Urbanization, economic development, and ecological environment: Evidence from provincial panel data in China[J]. Sustainability, 2022, 14(3): 1124.
[6]	Li J, Song C, Cao L, et al. Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China[J]. Remote Sensing of Environment, 2011, 115(12): 3249-3263.
[7]	Singh P, Kikon N, Verma P. Impact of land use change and urbanization on urban heat island in Lucknow City, Central India. A remote sensing based estimate[J]. Sustainable Cities and Society, 2017, 32: 100-114.
[8]	Zhang X, Estoque R C, Murayama Y. An urban heat island study in Nanchang City, China based on land surface temperature and social-ecological variables[J]. Sustainable Cities and Society, 2017, 32: 557-568.
[9]	Xu H, Wang Y, Guan H, et al. Detecting ecological changes with a remote sensing based ecological index (RSEI) produced time series and change vector analysis[J]. Remote Sensing, 2019, 11(20): 2345.
[10]	Xu H. A remote sensing index for assessment of regional ecological changes[J]. China Environmental Science, 2013, 33(5): 889-897.
[11]	冯自贤, 佘璐, 王秀慧, 等. 基于改进遥感生态指数的宁夏生态环境质量时空变化[J]. 生态环境学报, 2024, 33(1): 131-143. doi: 10.16258/j.cnki.1674-5906.2024.01.014
	[Feng Zixian, She Lu, Wang Xiuhui, et al. Spatial and temporal variations of ecological environment quality in Ningxia based on improved remote sensing ecological index[J]. Ecology and Environmental Sciences, 2024, 33(1): 131-143. ]
[12]	刘尚钦, 张福浩, 赵习枝, 等. 干旱区绿洲遥感生态指数的改进[J]. 测绘科学, 2022, 47(6): 143-151, 203.
	[Liu Shangqin, Zhang Fuhao, Zhao Xizhi, et al. Improvement of remote sensing ecological index in oases in arid area[J]. Science of Surveying and Mapping, 2022, 47(6): 143-151, 203. ]
[13]	陈丽红, 刘普幸, 花亚萍. 基于RSEI的疏勒河流域生态质量综合评价及其成因分析[J]. 土壤通报, 2021, 52(1): 25-33.
	[Chen Lihong, Liu Puxing, Hua Yaping. Comprehensive evaluation of ecological quality and its factors analysis in the Shule River Basin based on RSEI[J]. Chinese Journal of Soil Science, 2021, 52(1): 25-33. ]
[14]	李朋轩, 杨永崇, 王涛, 等. 新疆地区土地利用变化及其对生态环境质量的影响[J]. 北方园艺, 2022(8): 67-75.
	[Li Pengxuan, Yang Yongchong, Wang Tao, et al. Land use changes and its impact on ecological environment quality in Xinjiang[J]. Northern Horticulture, 2022(8): 67-75. ]
[15]	Lyu X, Li X, Gong J, et al. Comprehensive grassland degradation monitoring by remote sensing in Xilinhot, Inner Mongolia, China[J]. Sustainability, 2020, 12(9): 3682.
[16]	Su X, Singh V P, Niu J, et al. Spatiotemporal trends of aridity index in Shiyang River basin of northwest China[J]. Stochastic Environmental Research and Risk Assessment, 2015, 29: 1571-1582.
[17]	Cook M, Schott J R, Mandel J, et al. Development of an operational calibration methodology for the Landsat thermal data archive and initial testing of the atmospheric compensation component of a Land Surface Temperature (LST) product from the archive[J]. Remote Sensing, 2014, 6(11): 11244-11266.
[18]	Yang J, Huang X. 30 m annual land cover dataset and its dynamics in China from 1990 to 2019[J]. Earth System Science Data Discussions, 2021, 13(8): 3907-3925.
[19]	Hu X, Xu H. A new remote sensing index for assessing the spatial heterogeneity in urban ecological quality: A case from Fuzhou City, China[J]. Ecological Indicators, 2018, 89: 11-21.
[20]	Huang C, Wylie B, Yang L, et al. Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance[J]. International Journal of Remote Sensing, 2002, 23(8): 1741-1748.
[21]	Baig M H A, Zhang L, Shuai T, et al. Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance[J]. Remote Sensing Letters, 2014, 5(5): 423-431.
[22]	杜秉晨曦, 程勇翔, 吴玲. 准噶尔盆地植被与土壤盐渍化关联性变化趋势分析[J]. 生态学报, 2021, 41(23): 9364-9376.
	[Du Bingchenxi, Cheng Yongxiang, Wu Ling. Analysis of negative correlation between vegetation and soil salinization in Junggar Basin[J]. Acta Ecologica Sinica, 2021, 41(23): 9364-9376. ]
[23]	Yu R, Liu T, Xu Y, et al. Analysis of salinization dynamics by remote sensing in Hetao Irrigation District of North China[J]. Agricultural Water Management, 2010, 97(12): 1952-1960.
[24]	Wan L H, Wang S, Chen X. GeoDA-based spatial correlation analysis of GDP in Hadaqi industrial corridor[J]. Geographical Research, 2011, 30(6): 977-984.
[25]	Anselin L. Local indicators of spatial association-LISA[J]. Geographical Analysis, 1995, 27(2): 93-115.
[26]	赵晨光, 程业森, 李慧瑛, 等. 腾格里沙漠东北缘人工植被恢复区土地利用/覆被变化及其驱动因素分析[J]. 干旱区资源与环境, 2021, 35(6): 131-138.
	[Zhao Chenguang, Cheng Yesen, Li Huiying, et al. Land use/cover change of an artificial vegetation system in the northeastern edge of Tengger Desert[J]. Journal of Arid Land Resources and Environment, 2021, 35(6): 131-138. ]
[27]	吴亚坤, 李金彪, 高昊辰, 等. 阿拉善左旗土壤盐分空间变异特征研究[J]. 土壤, 2019, 51(5): 1030-1035.
	[Wu Yakun, Li Jinbiao, Gao Haochen, et al. Study on spatial variability of soil salinity in Alxa Zuoqi[J]. Soil, 2019, 51(5): 1030-1035. ]
[28]	张飞, 塔西甫拉提·特依拜, 丁建丽, 等. 干旱区土壤盐渍化及其对生态环境的损害评估——以新疆沙雅县为例[J]. 自然灾害学报, 2009, 18(4): 55-62.
	[Zhang Fei, Tashpolat Tiyip, Ding Jianli, et al. Soil salinization in arid area and its economic loss evaluation of eco-environmental damages: A case of Shaya County in Xinjiang[J]. Journal of Natural Disasters, 2009, 18(4): 55-62. ]
[29]	罗镕基, 王宏涛, 王成. 基于改进遥感生态指数的甘肃省古浪县生态质量评价[J]. 干旱区地理, 2023, 46(4): 539-549. doi: 10.12118/j.issn.1000-6060.2022.322
	[Luo Rongji, Wang Hongtao, Wang Cheng. Ecological quality evaluation of Gulang County in Gansu Province based on improved remote sensing ecological index[J]. Arid Land Geography, 2023, 46(4): 539-549. ] doi: 10.12118/j.issn.1000-6060.2022.322
[30]	郭泽呈, 魏伟, 庞素菲, 等. 基于SPCA和遥感指数的干旱内陆河流域生态脆弱性时空演变及动因分析——以石羊河流域为例[J]. 生态学报, 2019, 39(7): 2558-2572.
	[Guo Zecheng, Wei Wei, Pang Sufei, et al. Spatio-temporal evolution and motivation analysis of ecological vulnerability in arid inland river basin based on SPCA and remote sensing index: A case study on the Shiyang River Basin[J]. Acta Ecologica Sinica, 2019, 39(7): 2558-2572. ]
[31]	代云豪, 管瑶, 刘孟琴, 等. 1990—2020年阿拉尔垦区生态环境质量动态监测与评价[J]. 水土保持通报, 2022, 42(2): 122-128.
	[Dai Yunhao, Guan Yao, Liu Mengqin, et al. Dynamic monitoring and evaluation of ecological environment quality in Alar Reclamation Area from 1990 to 2020[J]. Bulletin of Soil and Water Conservation, 2022, 42(2): 122-128. ]
[32]	杜高奇, 李自强, 赵勇, 等. 基于RSEI的黄河流域生态环境质量监测与驱动因素分析[J]. 水利水电技术, 2022, 53(12): 81-93.
	[Du Gaoqi, Li Ziqiang, Zhao Yong, et al. RSEI-based analysis on eco-environment quality monitoring and driving factors of Yellow River Basin[J]. Water Resources and Hydropower Engineering, 2022, 53(12): 81-93. ]
[33]	高吉喜, 张小华, 邹长新, 等. 筑牢生态屏障建设美丽中国[J]. 环境保护, 2021, 49(6): 17-20.
	[Gao Jixi, Zhang Xiaohua, Zou Changxin, et al. Constructing ecological barriers to build a beautiful China[J]. Environmental Protection, 2021, 49(6): 17-20. ]
[34]	Chen W Y, Yu T F, Han T, et al. Effects of afforestation by aerial sowing on topsoil physicochemical properties in the sandy desert, NW China[J]. Journal of Soils and Sediments, 2023, 23(6): 2417-2427
[35]	赵晨光, 李慧瑛, 鱼腾飞, 等. 腾格里沙漠东北缘人工植被对土壤物理性质的影响[J]. 干旱区研究, 2022, 39(4): 1112-1121. doi: 10.13866/j.azr.2022.04.12
	[Zhao Chenguang, Li Huiying, Yu Tengfei, et al. Effects of artificial vegetation construction on soil physical properties in the northeastern edge of Tengger Desert[J]. Arid Zone Research, 2022, 39(4): 1112-1121. ] doi: 10.13866/j.azr.2022.04.12

年份	数据集	卫星	使用波段	月/云/空间分辨率
1991—2011	LANDSAT/LT05/C02/T1_L2	Landsat 5/TM	SR_B（1，2，3，4，5，7）ST_B6	7—9月 <20% 30 m
2012	LANDSAT/LE07/C02/T1_L2	Landsat 7/ETM+	SR_B（1，2，3，4，5，7）ST_B6
2013—2021	LANDSAT/LC08/C02/T1_L2	Landsat 8/OLI/TIRS	SR_B（2，3，4，5，6，7）ST_B10

1991年	2008年
1991年	劣	差	中	良	优
劣	20837.54	6388.98	772.57	77.57	23.20
差	11384.72	26602.14	3675.01	493.89	208.30
中	62.32	3309.34	6598.99	1120.84	200.68
良	1.76	30.54	1475.00	2024.40	585.54
优	0.35	3.33	23.16	645.20	1776.98

2008年	2020年
2008年	劣	差	中	良	优
劣	20395.57	11355.27	481.44	31.82	17.81
差	6178.71	24840.16	5029.51	186.36	81.75
中	390.01	3061.34	7854.05	1125.48	92.59
良	38.79	184.52	1279.73	2543.47	303.50
优	9.15	38.84	119.60	917.33	1686.13

年份	土地利用	显著变差 (-1.0~-0.6)	变差 (-0.6~-0.2)	不变 (-0.2~0.2)	变好 (0.2~0.6)	显著变好 (0.6~1.0)
1991—2008	耕地	0.00	0.02	0.51	0.41	0.07
	林地	0.00	0.00	0.97	0.03	0.00
	草地	0.00	0.05	0.87	0.08	0.00
	裸地	0.00	0.05	0.91	0.04	0.00
	不透水面	0.00	0.20	5.43	0.45	0.03
2008—2020	耕地	0.01	0.07	0.80	0.11	0.01
	林地	0.00	0.00	0.96	0.04	0.00
	草地	0.00	0.05	0.89	0.06	0.00
	裸地	0.00	0.04	0.95	0.01	0.00
	不透水面	0.01	0.13	0.80	0.06	0.00

基于GEE的干旱区县域生态环境质量时空变化及驱动力分析——以阿拉善左旗为例

Spatial-temporal variation and driving forces analysis of ecological environment quality in arid counties based on GEE: A case study of Alxa Left Banner

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