毛乌素沙地归一化植被指数时空演变及其驱动力:以内蒙古乌审旗为例

doi:10.13287/j.1001-9332.202603.060

应用生态学报 ›› 2026, Vol. 37 ›› Issue (3): 805-813.doi: 10.13287/j.1001-9332.202603.060

毛乌素沙地归一化植被指数时空演变及其驱动力:以内蒙古乌审旗为例

刘一丹^1,5, 黄海广^2,3, 李晓兰⁴, 李雪华^1*

¹中国科学院沈阳应用生态研究所, 沈阳 110016;
²内蒙古自治区林业科学研究院, 呼和浩特 010010;
³内蒙古多伦浑善达克沙地生态系统定位观测研究站, 内蒙古锡林郭勒 027300;
⁴伊犁师范大学资源与环境学院, 新疆伊宁 835000;
⁵中国科学院大学, 北京 100049

收稿日期:2025-10-20 接受日期:2026-01-28 出版日期:2026-03-18 发布日期:2026-09-18
通讯作者: *E-mail: lixuehua@iae.ac.cn
作者简介:刘一丹, 女, 2002年生, 硕士研究生。主要从事基于遥感和GIS的沙地生态水文过程研究。E-mail: 2422112882@qq.com
基金资助:
内蒙古自治区科技计划项目(2023YFHH0111)和新疆维吾尔自治区天池英才创新领军人才计划项目(2025CXLJ005)

Spatiotemporal variations of normalized difference vegetation index in the Mu Us Sandy Land and the dri-ving forces: A case study of Uxin Banner, Inner Mongolia, China

LIU Yidan^1,5, HUANG Haiguang^2,3, LI Xiaolan⁴, LI Xuehua^1*

¹Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;
²Inner Mongolia Academy of Forestry, Hohhot 010010, China;
³Inner Mongolia Duolun Hunshandake Sandland Ecosystem Observation and Research Station, Xilingguole 027300, Inner Mongolia, China;
⁴School of Resources and Environment, Yili Normal University, Yining 835000, Xinjiang, China;
⁵University of Chinese Academy of Sciences, Beijing 100049, China

Received:2025-10-20 Accepted:2026-01-28 Online:2026-03-18 Published:2026-09-18

摘要/Abstract

摘要： 毛乌素沙地是中国北方生态屏障区的重要组成部分,明确气候变化和人类活动对该区归一化植被指数(NDVI)影响的时空分异特征至关重要。基于1990—2023年遥感影像和气象数据,系统分析了内蒙古乌审旗NDVI动态演变及与气象要素的响应关系,明确量化了气候变化和人类活动对NDVI驱动力的时空格局。结果表明:1990—2023年间,乌审旗NDVI整体呈极显著上升趋势[0.03·(10 a)^-1],植被以轻中度改善为主(71.6%),但低植被覆盖区域占主导(90.5%),轻度下降像元占比为28.4%,且与NDVI极低值区(<0.1)高度重合在中部偏西北部。乌审旗年降水量和年均气温分别以49.40 mm·(10 a)^-1和0.37 ℃·(10 a)^-1变化倾向率极显著增加,并与NDVI呈现极显著正相关;相对重要性分析结果表明,年均气温是影响NDVI变化的主导气候因子而年降水量次之,相对重要性占比分别为74.9%和18.4%。气候变化和人类活动共同驱动乌审旗绝大部分区域NDVI增加(98.9%),二者相对贡献率具有明显空间分异特征:气候变化对乌审旗中部偏南局域NDVI相对贡献率为60%～80%,人类活动对乌审旗北部NDVI相对贡献率为60%～80%。本研究结果可为毛乌素沙地中部核心区的生态恢复和可持续管理提供科学依据。

关键词: 气候变化, 人类活动, 归一化植被指数, 相对贡献率, 毛乌素沙地

Abstract: The Mu Us Sandy Land is a crucial component of China's northern ecological barrier. It is of paramount importance to clarify the spatiotemporal variations of the impacts of climate change and human activities on the normalized difference vegetation index (NDVI). Based on remote sensing imagery and meteorological data from 1990 to 2023, we analyzed the variations of NDVI and its response to meteorological factors in Uxin Banner, Inner Mongolia, and quantitatively delineated the spatiotemporal patterns for the impacts of climate change and human activities on NDVI. The results showed that the NDVI in Uxin Banner showed a overall significant increasing trend [0.03·(10 a)^-1]. The vegetation showed a predominance of moderate improvement (71.6%), but areas with low vegetation cover dominated (90.5%). Pixels with slight decline accounted for 28.4%, highly overlapping with the extremely low NDVI zones (<0.1) in the northwestern central region. Annual precipitation and mean annual temperature in Uxin Banner increased with rates of 49.40 mm·(10 a)^-1 and 0.37 ℃·(10 a)^-1, respectively, both showing significant positive correlation with NDVI. Relative importance analysis showed that mean annual temperature was the dominant climatic factor affecting NDVI, followed by annual precipitation, with relative importance contribution of 74.9% and 18.4%. Both climate change and human activities drove NDVI increases in the vast majority of the region (98.9%), with their relative contribution rates exhibiting distinct spatially differentiated and complementary characteristics. Climate change contributed 60%-80% to NDVI increases in localized areas of south-central Uxin Banner, while human activities contributed 60%-80% in the northern part. This study could provide scientific evidence for the ecological restoration and sustainable management of the core area in the central Mu Us Sandy Land.

Key words: climate change, human activity, normalized difference vegetation index, relative contribution rate, Mu Us Sandy Land

刘一丹, 黄海广, 李晓兰, 李雪华. 毛乌素沙地归一化植被指数时空演变及其驱动力:以内蒙古乌审旗为例[J]. 应用生态学报, 2026, 37(3): 805-813.

LIU Yidan, HUANG Haiguang, LI Xiaolan, LI Xuehua. Spatiotemporal variations of normalized difference vegetation index in the Mu Us Sandy Land and the dri-ving forces: A case study of Uxin Banner, Inner Mongolia, China[J]. Chinese Journal of Applied Ecology, 2026, 37(3): 805-813.

参考文献

[1] 郭泽呈, 魏伟, 石培基, 等. 中国西北干旱区土地沙漠化敏感性时空格局. 地理学报, 2020, 75(9): 1948-1965
[2] 胡玲, 孙聪, 范闻捷, 等. 近20年防风固沙重点生态工程区植被动态分析. 生态学报, 2021, 41(21): 8341-8351
[3] Chang YQ, Han L, Chen R, et al. Modelling of the trade-off between the deep soil moisture and vegetation restoration in the hilly area of the Loess Plateau, China. Journal of Hydrology, 2024, 645: 132274
[4] Roels B, Donders S, Werger MJA, et al. Relation of wind-induced sand displacement to plant biomass and plant sand-binding capacity. Acta Botanica Sinica, 2001, 43: 979-982
[5] Forzieri G, Miralles DG, Ciais P, et al. Increased control of vegetation on global terrestrial energy fluxes. Nature Climate Change, 2020, 10: 356-361
[6] Shi SY, Yu JJ, Wang F, et al. Quantitative contributions of climate change and human activities to vegetation changes over multiple time scales on the Loess Plateau. Science of the Total Environment, 2021, 755: 142419
[7] Zhang YL, Song CH, Band LE, et al. Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening? Remote Sensing of Environment, 2017, 191: 145-155
[8] 敖登, 杨佳慧, 丁维婷, 等. 54种植被指数研究进展综述. 安徽农业科学, 2023, 51(1): 13-21, 28
[9] Xu HJ, Wang XP, Yang TB. Trend shifts in satellite derived vegetation growth in Central Eurasia, 1982-2013. Science of the Total Environment, 2017, 579: 1658-1674
[10] Chen C, Li D, Li Y, et al. Biophysical impacts of earth greening largely controlled by aerodynamics resistance. Science Advances, 2020, 6: eabb1981
[11] 赵倩倩, 张京朋, 赵天保, 等. 2000年以来中国区域植被变化及其对气候变化的响应. 高原气象, 2021, 40(2): 292-301
[12] 杨达, 易桂花, 张廷斌, 等. 青藏高原植被生长季NDVI时空变化与影像因素. 应用生态学报, 2021, 32(4): 1361-1372
[13] Yan F, Wu B, Wang YJ. Estimating spatiotemporal patterns of aboveground biomass using Landsat TM and MODIS images in the Mu Us Sandy Land, China. Agricultural and Forest Meteorology, 2015, 200: 119-128
[14] Cai HY, Yang XH, Xu XL. Human-induced grassland degradation/restoration in the central Tibetan Plateau: The effects of ecological protection and restoration project. Ecological Engineering, 2015, 83: 112-119
[15] 郭紫晨, 刘树林, 康文平, 等. 2000—2015年毛乌素沙区植被覆盖度变化趋势. 中国沙漠, 2018, 38(5): 1099-1107
[16] 胡尔查, 王铮, 李梓豪, 等. 毛乌素沙地不同林龄樟子松人工林林下植物多样性和生物量的动态变化. 生态学杂志, 2024, 43(11): 3246-3254
[17] 常文静, 丛士翔, 王融融, 等. 气候变化和人类活动对毛乌素沙地NDVI变化的量化分析. 干旱区地理, 2025, 48(1): 63-74
[18] Gao WD, Zheng C, Liu XH, et al. NDVI-based vegetation dynamics and their responses to climate change and human activities from 1982 to 2020: A case study in the Mu Us Sandy Land, China. Ecological Indicators, 2022, 137: 108745
[19] Chao Y, Zhu YH, Wang XH, et al. Dynamic evolution of the NDVI and driving factors in the Mu Us Sandy Land of China from 2002 to 2021. Journal of Arid Land, 2025, 17: 605-623
[20] Li YR, Cao Z, Long HL, et al. Dynamic analysis of ecological environment combined with land cover and NDVI changes and implications for sustainable urban-rural development: The case of Mu Us Sandy Land, China. Journal of Cleaner Production, 2017, 142: 697-715
[21] Miao I, Moore JC, Zeng F, et al. Footprint of research in desertification management in China. Land Degradation & Development, 2015, 26: 450-457
[22] Sun Z, Mao Z, Yang L, et al. Impacts of climate change and afforestation on vegetation dynamics in the Mu Us Desert, China. Ecological Indicators, 2021, 129: 108020
[23] 朱永华, 罗平平, 郭倩, 等. 毛乌素沙地暖湿化特征分析及其对植被变化的影响. 水土保持学报, 2022, 36(5): 160-172
[24] 刘娟, 刘华民, 卓义, 等. 毛乌素沙地1990—2014年景观格局变化及驱动力. 草业科学, 2017, 34(2): 255-263
[25] 杨梅焕, 张美晨. 毛乌素沙地东南缘NDVI植被变化特征分析. 地理空间信息, 2020, 18(5): 105-108
[26] 贺军奇, 魏燕, 高万德, 等. 毛乌素沙地东南缘植被NDVI时空变化及其对气候因子的响应. 干旱区地理, 2022, 45(5): 1523-1533
[27] Chen A, Park T, Wang XH, et al. China and India lead in greening of the world through land-use management. Nature Sustainability, 2019, 2: 122-129
[28] Piao SL, Yin GD, Tan JG, et al. Detection and attribution of vegetation greening trend in China over the last 30 years. Global Change Biology, 2015, 21: 1601-1609
[29] Li SS, Yang SN, Liu XF, et al. NDVI-based analysis on the influence of climate change and human activities on vegetation restoration in the Shaanxi-Gansu-Ningxia region, central China. Remote Sensing, 2015, 7: 11163-11182
[30] 王强, 张勃, 戴声佩, 等. 基于GIMMS AVHRR NDVI数据的三北防护林工程区植被覆盖动态变化. 资源科学, 2011, 33(8): 1613-1620
[31] Cao R, Jiang WG, Yuan LH, et al. Inter-annual variations in vegetation and their response to climatic factors in the upper catchments of the Yellow River from 2000 to 2010. Journal of Geographical Sciences, 2014, 24: 963-979
[32] 陈发虎, 陈捷, 黄伟. 东亚夏季风减弱诱发我国西北干旱区降水增加. 中国科学: 地球科学, 2021, 51(5): 824-826
[33] Zeng N, Ren XL, Niu ZE, et al. The adaptability of vegetation productivity to precipitation variability determines its resistance in central Asian grassland ecosystem. Journal of Arid Environments, 2025, 230: 05428

毛乌素沙地归一化植被指数时空演变及其驱动力:以内蒙古乌审旗为例

Spatiotemporal variations of normalized difference vegetation index in the Mu Us Sandy Land and the dri-ving forces: A case study of Uxin Banner, Inner Mongolia, China

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	朱文聪, 赵秋兰, 刘亚龙, 全先奎. 兴安落叶松根系非结构性碳水化合物对气候变暖的响应及种源差异 [J]. 应用生态学报, 2026, 37(8): 2547-2555.
[2]	马婷, 杨光磊, 王紫娟. 气候变化下中国3种桫椤科植物的分布格局变迁及优先保护区域识别 [J]. 应用生态学报, 2026, 37(7): 2257-2270.
[3]	许树涛, 李超骕, 杨华杰. 中国主要地级及以上城市空间形态与极端高温事件的关系 [J]. 应用生态学报, 2026, 37(7): 2343-2352.
[4]	杨阳, 王宝荣, 陈骥, 方临川, 王云强, 安韶山. 土壤胞外酶对全球变化响应研究进展 [J]. 应用生态学报, 2026, 37(7): 2441-2452.
[5]	张云, 杨艺婷, 文晓晨, 张万涛, 朱许可, 马理辉. 2000—2020年黄土高原植被净初级生产力的时空变化及驱动因素 [J]. 应用生态学报, 2026, 37(6): 1991-1999.
[6]	金睿, 罗肇河, 刘璇, 刘锦荃, 苏尚柯, 杜虹, 杜建国, 康建华, 胡文佳. 中国近海具刺环胺藻分布及其对气候变化的响应 [J]. 应用生态学报, 2026, 37(6): 2020-2030.
[7]	陈晓霞, 石福孙, 陶伯山, 李婧怡, 马文宝. 四川大沟流域优势树种径向生长及其对气候的响应 [J]. 应用生态学报, 2026, 37(5): 1449-1458.
[8]	吕文璇, 高露双, 李军锋, 王佳茜, 李国雷, 张志艺, 张昕宇, 李思杰. 气候变化背景下栓皮栎在中国的适生区格局 [J]. 应用生态学报, 2026, 37(5): 1466-1476.
[9]	何晓茜, 李攀, 丁虎, 李晶, 王金枝, 崔丽娟, 晏智锋. 河口湿地碳氮耦合过程与调控 [J]. 应用生态学报, 2026, 37(5): 1685-1696.
[10]	冯娟, 买吾拉夏·木巴热克, 刘卫平. 玛纳斯河流域植被生态质量变化及驱动力 [J]. 应用生态学报, 2026, 37(4): 1134-1140.
[11]	谢涵琦, 张庆吉, 马小雪, 田琳琳. 气候变化对凤眼莲在长江中下游地区潜在适生区的影响 [J]. 应用生态学报, 2026, 37(3): 917-925.
[12]	王金睿, 胡爱莲, 杨娟. 气候变化对南极阿德利属企鹅潜在适宜生境分布的影响 [J]. 应用生态学报, 2026, 37(3): 926-932.
[13]	党建毓, 麻小见, 杨馨逸, 盘昱良, 何寻阳, 王克林, 李德军, 段鹏鹏. 土壤微生物碳利用效率对气候变化响应的研究进展 [J]. 应用生态学报, 2026, 37(2): 609-621.
[14]	曾岩, 林佳瑾, 聂佳莉, 尤孟阳, 李禄军. 生态系统类型对铁氧化物结合态有机碳形成机制的影响 [J]. 应用生态学报, 2026, 37(1): 295-304.
[15]	陈江波, 赵媛媛, 丁国栋, 王学林, 董鹏, 刘雅丹, 卢佳雪. 雅鲁藏布江流域归一化植被指数变化及其对气候因子的响应 [J]. 应用生态学报, 2025, 36(9): 2797-2804.