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Open AccessArticle

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

1
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
2
Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, TX 77843, USA
3
School of Geology and Geometics, Tianjin Chengjian University, Tianjin 300384, China
4
School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(14), 3839; https://doi.org/10.3390/s20143839
Received: 22 April 2020 / Revised: 27 June 2020 / Accepted: 7 July 2020 / Published: 9 July 2020
(This article belongs to the Section Remote Sensors)
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. View Full-Text
Keywords: land desertification; remote sensing; enhanced vegetation index; leaf area index; vegetation trend; nonlinear changes; East Inner Mongolia land desertification; remote sensing; enhanced vegetation index; leaf area index; vegetation trend; nonlinear changes; East Inner Mongolia
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Ding, C.; Huang, W.; Li, Y.; Zhao, S.; Huang, F. Nonlinear Changes in Dryland Vegetation Greenness over East Inner Mongolia, China, in Recent Years from Satellite Time Series. Sensors 2020, 20, 3839.

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