Nonlinear Changes in Dryland Vegetation Greenness over East Inner Mongolia, China, in Recent Years from Satellite Time Series

被引:10
|
作者
Ding, Chao [1 ]
Huang, Wenjiang [1 ]
Li, Yao [2 ]
Zhao, Shuang [3 ]
Huang, Fang [4 ]
机构
[1] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[2] Texas A&M Univ, Zachry Dept Civil & Environm Engn, College Stn, TX 77843 USA
[3] Tianjin Chengjian Univ, Sch Geol & Geomet, Tianjin 300384, Peoples R China
[4] Northeast Normal Univ, Sch Geog Sci, Changchun 130024, Peoples R China
基金
中国博士后科学基金; 国家重点研发计划;
关键词
land desertification; remote sensing; enhanced vegetation index; leaf area index; vegetation trend; nonlinear changes; East Inner Mongolia; HORQIN SANDY LAND; ECOLOGICAL RESTORATION PROGRAM; SEMIARID AREAS; COVER CHANGE; DESERTIFICATION; DEGRADATION; DYNAMICS; TRENDS; FRAMEWORK; INCREASE;
D O I
10.3390/s20143839
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Knowledge of the dynamics of dryland vegetation in recent years is essential for combating desertification. Here, we aimed to characterize nonlinear changes in dryland vegetation greenness over East Inner Mongolia, an ecotone of forest-grassland-cropland in northern China, with time series of Moderate-resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) and GEOV2 leaf area index (LAI) values during 2000 to 2016. Changes in the growing season EVI and LAI were detected with the polynomial change fitting method. This method characterizes nonlinear changes in time series by polynomial fitting with the highest polynomial order of three, and simultaneously provides an estimation of monotonic trends over the time series by linear fitting. The relative contribution of climatic factors (precipitation and temperature) to changes in the EVI and LAI were analyzed using linear regression. In general, we observed similar patterns of change in the EVI and LAI. Nonlinear changes in the EVI were detected for about 21% of the region, and for the LAI, the percentage of nonlinear changes was about 16%. The major types of nonlinear changes include decrease-increase, decrease-increase-decrease, and increase-decrease-increase changes. For the overall monotonic trends, very small percentages of decrease (less than 1%) and widespread increases in the EVI and LAI were detected. Furthermore, large areas where the effects of climate variation on vegetation changes were not significant were observed for all major types of change in the grasslands and rainfed croplands. Changes with an increase-decrease-increase process had large percentages of non-significant effects of climate. The further analysis of increase-decrease-increase changes in different regions suggest that the increasing phases were likely to be mainly driven by human activities, and droughts induced the decreasing phase. In particular, some increase-decrease changes were observed around the large patch of bare areas. This may be an early signal of degradation, to which more attention needs to be paid to combat desertification.
引用
收藏
页码:1 / 14
页数:14
相关论文
共 41 条
  • [21] Assessing the Nonlinear Changes in Global Navigation Satellite System Vertical Time Series with Environmental Loading in Mainland China
    Zhang, Jie
    Li, Zhicai
    Zhang, Peng
    Yang, Fei
    Wu, Junli
    Liu, Xuchun
    Wang, Xiaoqing
    Tan, Qianchi
    REMOTE SENSING, 2023, 15 (16)
  • [22] Climate condition of the significant precipitation decrease over the middle-eastern region of Inner Mongolia, China in recent 10 years (2001-2010)
    Gao, Tao
    Jiang, Xuegong
    Hu, Yinghua
    THEORETICAL AND APPLIED CLIMATOLOGY, 2013, 111 (1-2) : 265 - 274
  • [23] DETECTING LONG-TERM TRENDS OF VEGETATION CHANGE AT LOCAL SCALE THROUGH TIME-SERIES IMAGE ANALYSIS: A CASE STUDY IN INNER MONGOLIA, CHINA
    Liu, Xinxia
    Zhang, Anbing
    Xie, Yichun
    Hua, Jin
    Liu, Haixin
    FRESENIUS ENVIRONMENTAL BULLETIN, 2019, 28 (03): : 1881 - 1895
  • [24] Vegetation history with implication of climate changes and human impacts over the last 9000 years in the Lake Nanyi area, Anhui Province, East China
    Chen, Wei
    Song, Bing
    Shu, Jun-Wu
    Jin, Chuan-Fang
    Wang, Wei-Ming
    PALAEOWORLD, 2021, 30 (03) : 583 - 592
  • [25] Establishing forest resilience indicators in the hilly red soil region of southern China from vegetation greenness and landscape metrics using dense Landsat time series
    Liu, Meiling
    Liu, Xiangnan
    Wu, Ling
    Tang, Yibo
    Li, Yu
    Zhang, Yaqi
    Ye, Lu
    Zhang, Biyao
    ECOLOGICAL INDICATORS, 2021, 121
  • [26] Climate variability over the last 2000 years inferred from glycerol dialkyl glycerol tetraethers (GDGTs) in alkaline Nalin Lake of Inner Mongolia, China
    Yang, Guifang
    Chen, Zhenghong
    Wu, Fadong
    Gao, Meiling
    Yin, Zhigang
    Guo, Bin
    ENVIRONMENTAL EARTH SCIENCES, 2016, 75 (08)
  • [27] Climate variability over the last 2000 years inferred from glycerol dialkyl glycerol tetraethers (GDGTs) in alkaline Nalin Lake of Inner Mongolia, China
    Guifang Yang
    Zhenghong Chen
    Fadong Wu
    Meiling Gao
    Zhigang Yin
    Bin Guo
    Environmental Earth Sciences, 2016, 75
  • [28] Unmixing the coupling influence from driving factors on vegetation changes considering spatio-temporal heterogeneity in mining areas: a case study in Xilinhot, Inner Mongolia, China
    Li, Jun
    Xu, Yaling
    Zhang, Chengye
    Guo, Junting
    Wang, Xingjuan
    Zhang, Yicong
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2023, 195 (01)
  • [29] Unmixing the coupling influence from driving factors on vegetation changes considering spatio-temporal heterogeneity in mining areas: a case study in Xilinhot, Inner Mongolia, China
    Jun Li
    Yaling Xu
    Chengye Zhang
    Junting Guo
    Xingjuan Wang
    Yicong Zhang
    Environmental Monitoring and Assessment, 2023, 195
  • [30] Seasonal Vegetation Trends for Europe over 30 Years from a Novel Normalised Difference Vegetation Index (NDVI) Time-Series-The TIMELINE NDVI Product
    Eisfelder, Christina
    Asam, Sarah
    Hirner, Andreas
    Reiners, Philipp
    Holzwarth, Stefanie
    Bachmann, Martin
    Gessner, Ursula
    Dietz, Andreas
    Huth, Juliane
    Bachofer, Felix
    Kuenzer, Claudia
    REMOTE SENSING, 2023, 15 (14)