基于GEE的翁牛特旗土地沙漠化遥感监测

doi:10.13866/j.azr.2023.03.16

干旱区研究 ›› 2023, Vol. 40 ›› Issue (3): 504-516.doi: 10.13866/j.azr.2023.03.16

• 生态与环境 • 上一篇

基于GEE的翁牛特旗土地沙漠化遥感监测

马浩文^1,²(),王永芳^1,^2,³(),郭恩亮^1,²

1.内蒙古师范大学地理科学学院，内蒙古呼和浩特 010022
2.内蒙古自治区蒙古高原灾害与生态安全重点实验室，内蒙古呼和浩特 010022
3.蒙古高原气候变化与区域响应高校重点实验室，内蒙古呼和浩特 010022

收稿日期:2022-06-09 修回日期:2022-08-10 出版日期:2023-03-15 发布日期:2023-03-31
通讯作者: 王永芳. E-mail: wangyongfang@imnu.edu.cn
作者简介:马浩文（1999-），男，硕士研究生，主要从事沙漠化遥感监测方面的研究. E-mail: chnmahaowen@163.com
基金资助:
内蒙古自治区自然科学基金(2021BS04008);内蒙古自治区自然科学基金(2019MS04010);内蒙古师范大学基本科研业务费专项资金(2022JBQN092);内蒙古师范大学高层次人才科研启动经费项目(2019YJRC003)

Remote sensing monitoring of aeolian desertification in Ongniud Banner based on GEE

MA Haowen^1,²(),WANG Yongfang^1,^2,³(),GUO Enliang^1,²

1. College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, Inner Mongolia, China
2. Inner Mongolia Key Laboratory of Disaster and Ecological Security on the Mongolian Plateau, Hohhot 010022, Inner Mongolia, China
3. University Key Laboratory of Climate Change and Regional Response in Mongolian Plateau, Hohhot 010022, Inner Mongolia, China

Received:2022-06-09 Revised:2022-08-10 Online:2023-03-15 Published:2023-03-31

摘要/Abstract

摘要：

基于谷歌地球引擎(Google Earth Engine，GEE)，通过提取归一化植被指数(Normalized Difference Vegetation Index，NDVI)和地表反照率(Albedo)两个参量，构建NDVI-Albedo特征空间，对翁牛特旗1991—2015年沙漠化进行监测，并利用地理探测器结合自然和人为因子分析翁牛特旗沙漠化驱动因子及其影响力。结果表明：（1）翁牛特旗土地沙漠化经历了先发展后逆转的演变进程。1991—2000年为发展期，沙漠化土地总面积增加了2130.29 km²；2000—2015年为逆转期，沙漠化土地总面积减少了3364.61 km²。（2）翁牛特旗沙漠化严重的区域主要是分布在中东部以及北部的西辽河平原地区，而西南区域的冀北辽西山地大部分区域沙漠化程度较轻。（3）自然因子和人为因子共同驱动翁牛特旗沙漠化演变过程。地形和沙源是翁牛特旗沙漠化土地空间分布格局形成的主要原因；翁牛特旗1991—2000年沙漠化发展是在自然条件不利的背景下人口增加所带来的环境压力造成的结果，而2000—2015年沙漠化逆转是在自然条件利好的背景下一系列防沙治沙政策有效实施的结果。

关键词: GEE, 沙漠化, NDVI-Albedo特征空间, 地理探测器, 科尔沁沙地

Abstract:

In this study, google earth engine (GEE) was used to extract the normalized difference vegetation index (NDVI) and Albedo parameters. The NDVI-Albedo space was constructed to monitor aeolian desertification in Ongniud Banner from 1991 to 2015, and the influence of key driving factors and mechanism of aeolian desertification in Ongniud Banner were analyzed using geographical detectors combined with natural and anthropogenic factors. The following key results were obtained: (1) Aeolian desertification in Ongniud Banner first experienced the development of evolution process, which then was reversed. During the development period from 1991 to 2000, the total area of aeolian desertified land increased by 2130.29 km², with extremely severe changes in both aeolian and non-aeolian desertified land, which had dynamic attitudes of 9.5 and -4.8, respectively. From 2000 to 2015, the total desertified land area of aeolian decreased by 3364.61 km², and the extreme severe aeolian and non-aeolian desertification land were the main changes, with dynamic attitudes of -4.2 and 8.3, respectively; (2) The extreme areas of aeolian desertification in the Ongniud Banner were mainly distributed in the central east and the north of Xiliaohe Plain, while the aeolian desertification in most areas of Jibeiliaoxi Mountain in southwest region is relatively light. From the perspective of transfer, the development area of various types of aeolian desertification land was 5333.75 km², while the reversed area from 1991 to 2000 was 1157.29 km². Notably, the non-aeolian desertified to moderate aeolian desertified land area was the largest covering 1000.24 km². From 2000 to 2015, the development area of all types of aeolian desertified land was only 424.65 km², while the reversed area was 7041.80 km². The area of moderate desertified land covering 1449.74 km² was reverted to non-desertified land; (3) From 1991 to 2000, both natural and anthropogenic factors drove the aeolian desertification process in the study area, with terrain and sand source as the main reasons for the formation of spatial distribution pattern of aeolian desertified land in Ongniud Banner. The warm and dry climate conditions, as well as intensified human activities led to the development of aeolian desertification in Ongniud Banner. From 2000 to 2015, aeolian desertification reversal was driven by the implementation of a series of anti-desertification policies and the improvement of natural conditions.

Key words: GEE, aeolian desertification, NDVI-Albedo space, geographical detector, Horqin Sandy Land

马浩文, 王永芳, 郭恩亮. 基于GEE的翁牛特旗土地沙漠化遥感监测[J]. 干旱区研究, 2023, 40(3): 504-516.

MA Haowen, WANG Yongfang, GUO Enliang. Remote sensing monitoring of aeolian desertification in Ongniud Banner based on GEE[J]. Arid Zone Research, 2023, 40(3): 504-516.

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参考文献 47

[1]	胡云锋, 张云芝, 韩月琪. 2000—2015年中国荒漠化土地识别和监测[J]. 干旱区地理, 2018, 41(6): 1321-1332.
	[Hu Yunfeng, Zhang Yunzhi, Han Yueqi. Identification and monitoring of desertification lands in China from 2000 to 2015[J]. Arid Land Geography, 2018, 41(6): 1321-1332.]
[2]	阿如旱, 都来, 盛艳, 等. 基于Logistic回归模型的内蒙古多伦县土地沙漠化驱动力分析[J]. 干旱区地理, 2019, 42(1): 137-143.
	[Aruhan, Du Lai, Sheng Yan, et al. Driving forces on land desertification in Duolun County Inner Mongolia based on logistic regress model[J]. Arid Land Geography, 2019, 42(1): 137-143.]
[3]	王涛. 我国沙漠化研究的若干问题——3. 沙漠化研究和防治的重点区域[J]. 中国沙漠, 2004, 24(1): 1-9.
	[Wang Tao. Study on sandy desertification in China: 3. Key regions for studying and combating sandy desertification[J]. Journal of Desert Research, 2004, 24(1): 1-9.]
[4]	李金亚. 科尔沁沙地草原沙化时空变化特征遥感监测及驱动力分析[D]. 北京: 中国农业科学院, 2014.
	[Li Jinya. Spatio-temporal Variations and Its Driving Factors of the Grassland Sandy Desertification in Horqin Sandy Land Based on Remote Sensing[D]. Beijing: Chinese Academy of Agricultural Sciences, 2014.]
[5]	王娟, 李宝林, 余万里. 近30年内蒙古自治区植被变化趋势及影响因素分析[J]. 干旱区资源与环境, 2012, 26(2): 132-138.
	[Wang Juan, Li Baolin, Yu Wanli. Analysis of vegetation trend and their causes during recent 30 years in Inner Mongolia Autonomous Region[J]. Journal of Arid Land Resources and Environment, 2012, 26(2): 132-138.]
[6]	牛存洋, 阿拉木萨, 刘亚, 等. 科尔沁沙地固沙植物根系与土壤水分特征研究[J]. 干旱区资源与环境, 2015, 29(10): 106-111.
	[Niu Cunyang, Alamusa, Liu Ya, et al. The characteristics of sand-fixation plantations roots and soil moisture in Horqin Sandy Land[J]. Journal of Arid Land Resources and Environment, 2015, 29(10): 106-111.]
[7]	郭翠萍, 郭浩, 霍俊澎, 等. 中国主要沙漠和沙地碳同位素特征[J]. 干旱区资源与环境, 2020, 34(2): 135-140.
	[Guo Cuiping, Guo Hao, Huo Junpeng, et al. Carbon isotope characteristics of deserts and sandy lands in China[J]. Journal of Arid Land Resources and Environment, 2020, 34(2): 135-140.]
[8]	康文平, 刘树林. 沙漠化遥感监测与定量评价研究综述[J]. 中国沙漠, 2014, 34(5): 1222-1229.
	[Kang Wenping, Liu Shulin. A review of remote sensing monitoring and quantitative assessment of aeolian desertification[J]. Journal of Desert Research, 2014, 34(5): 1222-1229.]
[9]	王永芳. 基于多源数据融合与DPSIR模型的科尔沁沙地沙漠化生态风险评价[D]. 长春: 东北师范大学, 2016.
	[Wang Yongfang. Ecological Risk Assessment on Aeolian Desertification in Horqin Sandy Land Using Multi-source Data Fusion and DPSIR Model[D]. Changchun: Northeast Normal University, 2016.]
[10]	白壮壮, 崔建新, 丁晓辉. 1986—2015年鄂尔多斯高原沙漠化及其驱动因素研究[J]. 干旱区研究, 2020, 37(3): 749-756.
	[Bai Zhuangzhuang, Cui Jianxin, Ding Xiaohui. Desertification and its driving factors in the Ordos Plateau, from 1986 to 2015[J]. Arid Zone Research, 2020, 37(3): 749-756.]
[11]	黄伟, 张懿, 王利明. 基于TM影像的土地荒漠化变化研究——以巴彦淖尔地区为例[J]. 内蒙古林业调查设计, 2015, 38(5): 132-134.
	[Huang Wei, Zhang Yi, Wang Liming. Desertification change based on TM image: A case study of Bayannur Region[J]. Inner Mongolia Forestry Investigation and Design, 2015, 38(5): 132-134.]
[12]	岳喜元, 常学礼, 刘良旭, 等. 科尔沁沙地植被NDVI对太阳辐射照度变化的响应机制[J]. 干旱区资源与环境, 2015, 29(3): 98-102.
	[Yue Xiyuan, Chang Xueli, Liu Liangxu, et al. The responding mechanism of NDVI to solar radiation intensity change in Horqin Sandy Land[J]. Journal of Arid Land Resources and Environment, 2015, 29(3): 98-102.]
[13]	于显双, 赵明, 陈凤臻, 等. 基于GIS的北方农牧交错带荒漠化遥感动态监测与成因分析——以内蒙古通辽市为例[J]. 干旱区资源与环境, 2010, 24(4): 107-111.
	[Yu Xianshuang, Zhao Ming, Chen Fengzhen, et al. Dynamic remote sensing monitoring and analysis on desertification in the northern farming: Pastoral zone based on GIS[J]. Journal of Arid Land Resources and Environment, 2010, 24(4): 107-111.]
[14]	那音太, 乌兰图雅, 秦福莹. 基于3S技术的科尔沁沙地土地荒漠化动态监测——以科尔沁左翼后旗为例[J]. 干旱区资源与环境, 2010, 24(10): 50-54.
	[Na Yintai, Wulan Tuya, Qin Fuying. Dynamic monitoring of Horqin sandy land desertification based on 3S techniques: A case study in Horqin Left Wing Banner[J]. Journal of Arid Land Resources and Environment, 2010, 24(10): 50-54.]
[15]	段英杰, 何政伟, 王永前, 等. 基于遥感数据的西藏自治区土地沙漠化监测分析研究[J]. 干旱区资源与环境, 2014, 28(1): 55-61.
	[Duan Yingjie, He Zhengwei, Wang Yongqian, et al. Monitoring land desertification of Tibet Autonomous Region based on remote sensing[J]. Journal of Arid Land Resources and Environment, 2014, 28(1): 55-61.]
[16]	曾永年, 向南平, 冯兆东, 等. Albedo-NDVI特征空间及沙漠化遥感监测指数研究[J]. 地理科学, 2006, 26(1): 75-81. doi: 10.13249/j.cnki.sgs.2006.01.75
	[Zeng Yongnian, Xiang Nanping, Feng Zhaodong, et al. Albedo-NDVI space and remote sensing synthesis index models for desertification monitoring[J]. Scientia Geographica Sinica, 2006, 26(1): 75-81.] doi: 10.13249/j.cnki.sgs.2006.01.75
[17]	岳辉, 刘英. 基于NDVI-Albedo特征空间的陕西省干旱与荒漠化遥感监测[J]. 西北林学院学报, 2019, 34(1): 198-205.
	[Yue Hui, Liu Ying. Remote sensing monitoring of drought and desertification in Shaanxi Province based on NDVI-Albedo feature space[J]. Journal of Northwest Forestry University, 2019, 34(1): 198-205.]
[18]	王家琪. 内蒙古赤峰及其周边地区荒漠化变化趋势研究——基于遥感技术中反照率和归一化植被指数特征空间[J]. 安徽农业科学, 2016, 44(27): 217-219.
	[Wang Jiaqi. Study on the change trend of desertification in Chifeng and its surrounding areas: Based on albedo and normalized vegetation index feature space in remote sensing technology[J]. Journal of Anhui Agricultural Sciences, 2016, 44(27): 217-219.]
[19]	任艳群, 刘海隆, 唐立新, 等. 基于NDVI-Albedo特征空间的沙漠化动态变化研究——以准格尔盆地南缘为例[J]. 水土保持通报, 2014, 34(2): 267-271.
	[Ren Yanqun, Liu Hailong, Tang Lixin, et al. A study on dynamic changes of desertification in south edge of Junggar Basin based on NDVI-Albedo features[J]. Bulletin of Soil and Water Conservation, 2014, 34(2): 267-271.]
[20]	王劲峰, 徐成东. 地理探测器: 原理与展望[J]. 地理学报, 2017, 72(1): 116-134. doi: 10.11821/dlxb201701010
	[Wang Jinfeng, Xu Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1): 116-134.] doi: 10.11821/dlxb201701010
[21]	王晓峰, 张明明, 尹礼唱, 等. 2000—2015年中国干旱半干旱地区沙漠化进程驱动力研究[J]. 生态环境学报, 2019, 28(5): 948-957. doi: 10.16258/j.cnki.1674-5906.2019.05.011
	[Wang Xiaofeng, Zhang Mingming, Yin Lichang, et al. Study on the driving factors in desertification process in arid and semi-arid region of China from 2000 to 2015[J]. Ecology and Environmental Sciences, 2019, 28(5): 948-957.] doi: 10.16258/j.cnki.1674-5906.2019.05.011
[22]	王嘉妮, 陈海, 史琴琴, 等. 陕西省县域土地利用多功能性时空分异及影响因素研究[J]. 中国农业资源与区划, 2019, 40(5): 101-108.
	[Wang Jiani, Chen Hai, Shi Qinqin, et al. Research on spatial-temporal differentiation and influencing factors of land use multi-functionality in County Areas of Shaanxi Province[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2019, 40(5): 101-108.]
[23]	常亚斌, 朱睿, 肖生春, 等. 1980—2015年阿拉善盟沙地面积变化及其驱动因子[J]. 中国沙漠, 2020, 40(6): 82-90.
	[Chang Yabin, Zhu Rui, Xiao Shengchun, et al. Sandy land change from 1980 to 2015 in Alxa League, China and its driving factors[J]. Journal of Desert Research, 2020, 40(6): 82-90.]
[24]	席文涛, 高晶. 基于地理探测器分析青藏高原降水δ¹⁸O空间分异特征[J]. 干旱区研究, 2021, 38(5): 1199-1206.
	[Xi Wentao, Gao Jing. Spatial heterogentity of annual precipitation δ¹⁸O over the Tibetan Plateau based on the use of a geographical detector[J]. Arid Zone Research, 2021, 38(5): 1199-1206.]
[25]	连杰, 赵学勇, 左小安, 等. 科尔沁沙地水域景观格局的时空动态——以奈曼旗为例[J]. 中国沙漠, 2012, 32(1): 210-218.
	[Lian Jie, Zhao Xueyong, Zuo Xiao’an, et al. Dynamics of landscape pattern of water areas in Horqin Sandy Land, China: A case study in Naiman Banner of Inner Mongolia[J]. Journal of Desert Research, 2012, 32(1): 210-218.]
[26]	岳喜元, 左小安, 赵学勇, 等. 科尔沁沙地沙漠化风险评价[J]. 中国沙漠, 2018, 38(1): 8-16.
	[Yue Xiyuan, Zuo Xiao’an, Zhao Xueyong, et al. Desertification risk assessment in Horqin Sandy Land[J]. Journal of Desert Research, 2018, 38(1): 8-16.]
[27]	吕家欣, 李秀芬, 郑晓, 等. 近40年科尔沁沙地植被时空变化及其驱动力[J]. 生态学杂志, 2020, 39(5): 1399-1408.
	[Lv Jiaxin, Li Xiufen, Zheng Xiao, et al. Temporal and spatial changes and their driving forces of vegetation cover in Horqin Sandy Land in recent 40 years[J]. Chinese Journal of Ecology, 2020, 39(5): 1399-1408.]
[28]	Abatzoglou J T, Dobrowski S Z, Parks S A, et al. Terra Climate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015[J]. Scientific Data, 2018, 5: 170191. doi: 10.1038/sdata.2017.191
[29]	Liu H, Jiang D, Yang X, et al. Spatialization approach to 1 km Grid GDP supported by Remote Sensing[J]. Geo-information Science, 2005, 7(2): 120-123.
[30]	徐涵秋. 利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J]. 遥感学报, 2005, 9(5): 589-595.
	[Xu Hanqiu. A study on information extraction of water body with the modified normalized water index (MNDWI)[J]. Journal of Remote Sensing, 2005, 9(5): 589-595.]
[31]	Liang S, Shuey C J, Russ A L, et al. Narrowband to broadband conversions of land surface albedo: II. Validation[J]. Remote Sensing of Environment, 2003, 84(1): 25-41. doi: 10.1016/S0034-4257(02)00068-8
[32]	Liang S. Narrowband to broadband conversions of land surface albedo I algorithms[J]. Remote Sensing of Environment, 2001, 76(2): 213-238. doi: 10.1016/S0034-4257(00)00205-4
[33]	Duan H C, Wang T, Xue X, et al. Dynamics of aeolian desertification and its driving forces in the Horqin Sandy Land, Northern China[J]. Environmental Monitoring & Assessment, 2014, 186(10): 6083-6096.
[34]	Duan H C, Wang T, Xue X, et al. Dynamic monitoring of aeolian desertification based on multiple indicators in Horqin Sandy Land, China[J]. Science of The Total Environment, 2019, 650: 2374-2388. doi: 10.1016/j.scitotenv.2018.09.374
[35]	Wang J, Hu Y. Environmental health risk detection with GeogDetector[J]. Environmental Modelling & Software, 2012, 33: 114-115.
[36]	Wang J F, Li X H, Christakos G, et al. Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region, China[J]. International Journal of Geographical Information Science, 2010, 24(1): 107-127. doi: 10.1080/13658810802443457
[37]	Song Y, Wang J, Ge Y, et al. An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: Cases with different types of spatial data[J]. GIScience & Remote Sensing, 2020, 57(5): 1760434.
[38]	胡光印, 董治宝, 逯军峰, 等. 黄河流域沙漠化空间格局与成因[J]. 中国沙漠, 2021, 41(4): 213-224.
	[Hu Guangyin, Dong Zhibao, Lu Junfeng, et al. Spatial pattern of aeolian desertification and its causes in the Yellow River catchment[J]. Journal of Desert Research, 2021, 41(4): 213-224.]
[39]	段翰晨, 薛娴. 基于DEM的科尔沁沙地沙漠化土地时空分布特征[J]. 干旱区资源与环境, 2018, 32(8): 74-79.
	[Duan Hanchen, Xue Xian. Spatio-temporal distribution of aeolian desertification in Horqin Sandy Land based on DEM[J]. Journal of Arid Land Resources and Environment, 2018, 32(8): 74-79.]
[40]	郭茵, 雷加强, 范敬龙, 等. 近20 a蒙古国土壤风蚀变化特征及主要影响因素分析[J]. 干旱区研究, 2022, 39(4): 1200-1211.
	[Guo Yin, Lei Jiaqiang, Fan Jinglong, et al. Soil wind erosion characteristics and main influencing factors in Mongolia in recent 20 years[J]. Arid Zone Research, 2022, 39(4): 1200-1211.]
[41]	王旭东, 陈秀芳, 敖东. 荒漠化防治开启“翁牛特模式”[J]. 内蒙古林业, 2015, 60(1): 8.
	[Wang Xudong, Chen Xiufang, Ao Dong. “Ongniud Model” for desertification prevention and control[J]. Inner Mongolia Forestry, 2015, 60(1): 8.]
[42]	朱孟娜, 韩广, 郭宇航. 近10年来翁牛特旗土地沙漠化动态特征及其成因分析[J]. 湖南师范大学自然科学学报, 2016, 39(5): 16-21.
	[Zhu Mengna, Han Guang, Guo Yuhang. Analysis on dynamic characteristics and reasons of land desertification in Wengniut Banner in Recent 10 Years[J]. Journal of Natural Science of Hunan Normal University, 2016, 39(5): 16-21.]
[43]	马秀梅. 赤峰市树立防沙治沙与绿色富民典型[J]. 内蒙古林业, 2020, 65(7): 8-13.
	[Ma Xiumei. Chifeng to establish a model of sand control and green prosperity[J]. Inner Mongolia Forestry, 2020, 65(7): 8-13.]
[44]	段翰晨, 王涛, 薛娴, 等. 基于RS与GIS的科尔沁沙地沙漠化时空演变[J]. 中国沙漠, 2013, 33(2): 470-477.
	[Duan Hanchen, Wang Tao, Xue Xian, et al. Spatial-temporal evolution of aeolian desertification in the Horqin Sandy Land based on RS and GIS[J]. Journal of Desert Research, 2013, 33(2): 470-477.]
[45]	王旭, 刁兆岩, 郑志荣, 等. 中蒙毗邻草原区荒漠化时空动态研究[J]. 环境科学研究, 2021, 34(12): 2935-2944.
	[Wang Xu, Diao Zhaoyan, Zheng Zhirong, et al. Temporal and spatial dynamics of desertification in adjacent steppe of China and Mongolia[J]. Research of Environmental Sciences, 2021, 34(12): 2935-2944.]
[46]	杨军, 程玉琴, 尤莉. 翁牛特旗玉米生育期与气象条件的相关分析[J]. 内蒙古气象, 2014, 38(5): 33-35, 65.
	[Yang Jun, Cheng Yuqin, You Li. Correlation analysis on corn growth period and meteorological conditions in Ongniud Banner[J]. Meteorology Journal of Inner Mongolia, 2014, 38(5): 33-35, 65.]
[47]	张丽, 杨国范, 刘吉平. 1986—2012年抚顺市土地利用动态变化及热点分析[J]. 地理科学, 2014, 34(2): 185-191. doi: 10.13249/j.cnki.sgs.2014.02.185
	[Zhang Li, Yang Guofan, Liu Jiping. The cynamic changes and hot spots of land use in Fushun City from 1986 to 2012[J]. Scientia Geographica Sinica, 2014, 34(2): 185-191.] doi: 10.13249/j.cnki.sgs.2014.02.185

驱动因子	分辨率	时间范围	数据名称	数据来源
海拔	900 m	2000年	GMTED 2010	https://www2.jpl.nasa.gov/srtm/
坡度	900 m	2000年
坡向	900 m	2000年
气温	0.042°	1991—2015年	Terra Climate^[28]	https://climate.northwestknowledge.net/
降水量	0.042°	1991—2015年
潜在蒸散量	0.042°	1991—2015年
风速	0.042°	1991—2015年
土壤湿度	0.042°	1991—2015年
土壤类型	900 m	2000年	中国土壤类型空间分布数据	https://www.resdc.cn/DOI/
人口	1 km	1995年，2010年	中国人口空间分布公里网格数据	https://www.resdc.cn/DOI/
GDP	1 km	1995年，2010年	中国GDP空间分布公里网格数据	https://www.resdc.cn/DOI/
牲畜数量	0.083°	2010年	粮农组织牲畜系统^[29]	https:// www.fao.org/livestock-systems/

	1991年		2000年		2015年		1991—2000年		2000—2015年
	面积 /km²	比例 /%	面积 /km²	比例 /%	面积 /km²	比例 /%	面积变化 /km²	动态度/%	面积变化 /km²	动态度/%
非沙化	4820.17	40.72	2722.79	22.94	6104.75	51.36	-2097.38	-4.8	3381.96	8.3
轻度	1545.47	13.06	1135.12	9.56	1398.46	11.76	-410.35	-3.0	263.34	1.5
中度	1767.07	14.93	2345.36	19.76	1807.44	15.20	578.29	3.6	-537.92	-1.5
重度	1754.52	14.82	3255.94	27.43	1667.82	14.03	1501.42	9.5	-1588.12	-3.3
极重度	1950.46	16.47	2411.39	20.31	909.48	7.65	460.93	2.6	-1501.91	-4.2

	土壤类型	土壤湿度	海拔	降水量	气温	坡度	风速	人口	牲畜数量	GDP	坡向	潜在蒸散量
1991—2000年	0.153^*	0.124^*	0.122^*	0.121^*	0.095^*	0.093^*	0.086^*	0.081^*	0.05	0.035	0.02	0.026
2000—2015年	0.082	0.069^*	0.071	0.103^*	0.099^*	0.068^*	0.053	0.04	0.069	0.042	0.047	0.056

基于GEE的翁牛特旗土地沙漠化遥感监测

Remote sensing monitoring of aeolian desertification in Ongniud Banner based on GEE

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