长时序丹江口水源区NDVI数据集构建及其时空动态变化分析

由于不同传感器时空分辨率不一致，当前NDVI动态变化研究存在研究时间较短的问题。基于EOT算法，以丹江口水源区为例，借助重叠时期的GIMMS NDVI和MODIS NDVI数据，将8 km分辨率GIMMS NDVI数据重采样为1 km，构建了1982～2018年NDVI长时序数据集，并在此基础上分析丹江口水源区NDVI时空动态变化。结果表明：EOT算法在空间重采样中具有良好的适用性。EOT NDVI与MODIS NDVI之间拟合度较高（R=0.929，P<0.01，n=24），EOT NDVI与Landsat NDVI之间表现出显著相关关系（R=0.702，P<0.01，n=200）。空间上，EOT算法在土地利用类型较为复杂的区域受混合像元的影响，预测精度降低，在植被分布连片的区域预测精度较高。基于时序NDVI数据分析，研究时段内NDVI呈现波动上升趋势，变化趋势为0.002 9 year-1。空间上，丹江口水源区NDVI以显著增加为主（P<0.05），在汉中市、安康市河流附近以及北部商州市、南部竹溪县等区域年均NDVI增加趋势较其他区域明显；年均NDVI呈现减小的区域主要分布在丹江口水库、十堰市、南阳市、平利县等经济发展较快的区域。Mann-Kendall检验显示年均NDVI时间序列没有突变现象，但局部区域NDVI在不同时间呈现差异。

Construction of Long Time Series NDVI Dataset in Danjiangkou Water Source Area and Its Temporal and Spatial Dynamic Changes

Due to the different spatial and temporal resolution of different sensors, the research period of NDVI dynamic change is relatively short. Based on EOT algorithm, taking Danjiangkou Water Source Area as an example, with the help of GIMMS NDVI and MODIS NDVI data in overlapping period, the 8 km resolution GIMMS NDVI data is resampled to 1 km, and the long-term NDVI data set of 1982-2018 is constructed. On this basis, the temporal and spatial dynamic changes of NDVI in Danjiangkou Water source area are analyzed. The results show that EOT algorithm has good applicability in spatial resampling. The fit between EOT NDVI and MODIS NDVI was higher (r=0.929, P<0.01, n=24), and there was a significant correlation between EOT NDVI and Landsat NDVI (r=0.702, P<0.01, n=200). In space, the EOT algorithm is affected by the mixed pixel in the area with complex land use types, the prediction accuracy is reduced, and higher in the area with continuous vegetation distribution. In space, the EOT algorithm is affected by the mixed pixel in the area with complex land use types, the prediction accuracy is reduced, and higher in the area with continuous vegetation distribution. Based on the analysis of time series NDVI data, the NDVI showed an upward trend of 0.002 9 year-1. Spatially, the NDVI in Danjiangkou Water source area increased significantly (P<0.05), and the annual average NDVI increased significantly in Hanzhong City, Ankang City, Shangzhou city in the north, Zhuxi County in the South and other regions. The areas with decreased annual NDVI are mainly distributed in Danjiangkou reservoir, Shiyan City, Nanyang City, Pingli County and other areas with rapid economic development. The Mann Kendall test showed that there was no mutation in the annual NDVI time series, but the NDVI in some regions was different at different times.