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| 2000—2016年黄土高原不同土地覆盖类型植被NDVI时空变化 | |
| 引用本文： | 孙锐,陈少辉,苏红波.2000—2016年黄土高原不同土地覆盖类型植被NDVI时空变化[J].地理科学进展,2019,38(8):1248-1258. |
| 作者姓名： | 孙锐 陈少辉 苏红波 |
| 作者单位： | 中国科学院地理科学与资源研究所 陆地水循环及地表过程重点实验室,北京 100101 中国科学院大学,北京 100049 |
| 基金项目： | 国家自然科学基金项目(41671368);国家自然科学基金项目(41371348);中国科学院战略重点研究计划A(XDA20010301) |
| 摘 要： | 了解植被覆盖的时空变化对区域环境保护及生态环境建设具有重要意义。基于MOD13A1数据,辅以Sen+Mann-Kendall、变异系数、Hurst指数,通过分析2000—2016年间黄土高原NDVI年最大值(NDVIymax)和生长季均值(NDVIgsmean)时空变化特征及趋势,以了解黄土高原实施退耕还林(草)等生态工程后的植被覆盖恢复情况。结果表明：① 2000—2016年植被NDVIymax和NDVIgsmean呈现波动式增长趋势,增长率分别为0.0070/a(P<0.01)和0.0063/a(P<0.01),生态环境整体不断改善。② NDVIymax和NDVIgsmean显示黄土高原植被覆盖呈增加趋势的面积远高于呈减少趋势的面积(93.42%和96.22%、6.58%和3.78%),植被覆盖状态正在不断改善。2种数据变化趋势下,不同土地覆盖类型表现略有差异,森林极显著增加趋势面积最大(73.02%和82.60%),其次为耕地(47.87%和67.43%),再次为裸地(47.03%和61.68%)。③ NDVIgsmean的变异系数小于NDVIymax的变异系数,相对稳定区域面积比分别为63.31%与56.64%,2种数据分析下森林变异系数最小,植被稳定性最好。④ 从植被NDVI变化趋势与Hurst组合结果得出,NDVIymax未来呈现改善趋势面积占41.35%,退化趋势面积占58.65%;NDVIgsmean呈现改善趋势面积占49.19%,退化趋势面积占50.81%。2种数据下,灌木地未来发展趋势最好,森林和耕地退化趋势面积超过了50%。研究人员应持续关注退化趋势地区的植被状态。 |
| 关 键 词： | 黄土高原 NDVI MOD13A1 植被变化 土地覆盖 |
| 收稿时间： | 2018-12-12 |
| 修稿时间： | 2019-01-31 |
Spatiotemporal variations of NDVI of different land cover types on the Loess Plateau from 2000 to 2016 |
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| SUN Rui,CHEN Shaohui,SU Hongbo.Spatiotemporal variations of NDVI of different land cover types on the Loess Plateau from 2000 to 2016[J].Progress in Geography,2019,38(8):1248-1258. | |
| Authors: | SUN Rui CHEN Shaohui SU Hongbo |
| Institution: | Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China University of Chinese Academy of Sciences, Beijing 100049, China |
| Abstract: | Understanding the spatial-temporal changes of vegetation and future trends of spatial pattern is of great significance to regional environmental protection and ecological construction. In order to understand the vegetation changes on the Loess Plateau after the implementation of the Grain for Green Project, the spatial-temporal variation characteristics of annual maximum Normalized Difference Vegetation Index (NDVI) (NDVIymax) and growing seasonal mean NDVI (NDVIgsmean) were analyzed based on MOD13A1 data for the Loess Plateau during 2000-2016, supplemented by Sen+Mann-Kendall, coefficient of variation, and Hurst index analysis. The results indicate that: 1) NDVIymax and NDVIgsmean showed a fluctuating growth trend from 2000 to 2016, with growth rates of 0.0070/a (P<0.01) and 0.0063/a (P<0.01), respectively, and the ecological environment improved continuously. 2) NDVIymax and NDVIgsmean showed that the area of vegetation coverage on the Loess Plateau with increasing trend were much higher than that with decreasing trend (93.42% and 96.22% versus 6.58% and 3.78%). This means that vegetation coverage was improving. With regard to the trends of change of the two evaluation indices, the performance of different land cover types slightly differed. The area of forest with most significant increasing trend was 73.02% and 82.60%, followed by cultivated land (47.87% and 67.43%) and bare land (47.03% and 61.68%). The coefficient of variation of NDVIgsmean was smaller than that of NDVIymax, and the stable area was 63.31% and 56.64%, respectively. Of the two evaluation indices, the coefficient of variation of forest was the smallest, representing the best stability. According to the coupling results of NDVI and Hurst index, the areas with increasing trend of NDVIymax account for 41.35%, and the areas with degrading trend account for 58.65% of the total area in the future. The areas with increasing trend of NDVIgsmean account for 49.19%, and the areas with degrading trend account for 50.81% of the total area. The two evaluation indices show that shrubland has the best growth trend. The areas of forest and cultivated land with degrading trend would be greater than 50%. The vegetation status in the areas of unsustainable increase and sustainable degradation need continuous attention of researchers. |
| Keywords: | Loess Plateau NDVI MOD13A1 vegetation change land cover |
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