The Normalized Difference Vegetation Index （NDVI） is an important vegetation greenness indicator. Compared to the AVHRR GIMMS NDVI data, the availability of two datasets with 1 km spatial resolution, i.e., Terra MOD...The Normalized Difference Vegetation Index （NDVI） is an important vegetation greenness indicator. Compared to the AVHRR GIMMS NDVI data, the availability of two datasets with 1 km spatial resolution, i.e., Terra MODIS （MODI3A3） monthly composite and SPOT Vegetation （VGT） 10-day composite NDVI, extends the application dimensions at spatial and temporal scales. An overlapping period of 12 years between the datasets now makes it possible to investigate the consistency of the two datasets. Linear regression trend analysis was performed to compare the two datasets in this study. The results show greater consistency in regression slopes in the semi-arid regions of northern China. Alternatively, the results show only slight changes in the Terra MODIS NDVI regression slope in most areas of southern China whereas the SPOT VGT NDVI shows positive changes over a large area. The corresponding regression slope values between Terra MODIS and SPOT VGT NDVI datasets from the linear fit had a fair agreement in the spatial dimension. However, larger positive and negative differences were observed at the junction of the three regions （East China, Central China, and North China）. These differences can be partially explained by the positive standard deviation differences distributed over a large area at the junction of these three regions. This study demonstrated that Terra MODIS and SPOT VGT NDVI have a relatively robust basis for characterizing vegetation changes in annual NDVI in most of the semi-arid and arid regions in northern China.展开更多
文摘The Normalized Difference Vegetation Index （NDVI） is an important vegetation greenness indicator. Compared to the AVHRR GIMMS NDVI data, the availability of two datasets with 1 km spatial resolution, i.e., Terra MODIS （MODI3A3） monthly composite and SPOT Vegetation （VGT） 10-day composite NDVI, extends the application dimensions at spatial and temporal scales. An overlapping period of 12 years between the datasets now makes it possible to investigate the consistency of the two datasets. Linear regression trend analysis was performed to compare the two datasets in this study. The results show greater consistency in regression slopes in the semi-arid regions of northern China. Alternatively, the results show only slight changes in the Terra MODIS NDVI regression slope in most areas of southern China whereas the SPOT VGT NDVI shows positive changes over a large area. The corresponding regression slope values between Terra MODIS and SPOT VGT NDVI datasets from the linear fit had a fair agreement in the spatial dimension. However, larger positive and negative differences were observed at the junction of the three regions （East China, Central China, and North China）. These differences can be partially explained by the positive standard deviation differences distributed over a large area at the junction of these three regions. This study demonstrated that Terra MODIS and SPOT VGT NDVI have a relatively robust basis for characterizing vegetation changes in annual NDVI in most of the semi-arid and arid regions in northern China.
