Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.
Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, TX 77843, USA.
Sensors (Basel). 2020 Jul 9;20(14):3839. doi: 10.3390/s20143839.
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.
近年来,对旱地植被动态的了解对于防治荒漠化至关重要。在这里,我们旨在描述中国北方森林-草原-农田交错带的内蒙古东部地区旱地植被绿色度的非线性变化,使用 2000 年至 2016 年期间 Moderate-resolution Imaging Spectroradiometer(MODIS)增强植被指数(EVI)和 GEOV2 叶面积指数(LAI)的时间序列。使用多项式变化拟合方法检测生长季节 EVI 和 LAI 的变化。该方法通过使用最高阶数为三的多项式拟合来描述时间序列的非线性变化,并通过线性拟合同时提供时间序列上单调趋势的估计。使用线性回归分析气候因素(降水和温度)对 EVI 和 LAI 变化的相对贡献。总的来说,我们观察到 EVI 和 LAI 的变化模式相似。大约 21%的区域检测到 EVI 的非线性变化,对于 LAI,非线性变化的百分比约为 16%。非线性变化的主要类型包括减少-增加、减少-增加-减少和增加-减少-增加变化。对于整体单调趋势,检测到 EVI 和 LAI 的非常小的减少(小于 1%)和广泛的增加。此外,对于草地和雨养农田的所有主要变化类型,都观察到气候变化对植被变化影响不显著的大面积区域。具有增加-减少-增加过程的变化具有较大比例的气候影响不显著。对不同地区增加-减少-增加变化的进一步分析表明,增加阶段可能主要是由人类活动驱动的,而干旱导致了减少阶段。特别是,在大面积裸地区周围观察到一些增加-减少变化。这可能是退化的早期信号,需要更加关注防治荒漠化。