Vegetation Indices Based On Different Sources Of Remote Sensing Data Analyzed In Qinling Region

Consistent NDVI time series are basic and prerequisite in long-term monitoring of land surface properties. Advanced very high resolution radiometer( AVHRR)measurements provide the longest records of continuous global satellite measurements sensitive to live green vegetation, moderate resolution imaging spectroradiometer(MODIS) and SPOT are more recent typical with high spatial and temporal resolution.Understanding the relation between the AVHRR-derived NDVI,MODIS NDVI and SPOT NDVI is critical to continued long-term monitoring of ecological resources. Based on the different time series NDVI data, the different and suitability of AVHRR-NDVI,VGT-NDVI and MODIS-NDVI response to vegetation change in Qinling Mountains were analyzed in this study, and using Landsat samples covering major land cover type independently assessing the performance of AVHRR, MODIS and SPOT, it is very important significance to establish Consistent NDVI time series in the vegetation change research of Qinling mountain area. The main conclusions as following:These data had generally similar distribution patterns in space, MODIS and SPOT-VGT NDVI matched well. MODIS could recognize objects more clearly on the earth surface due to its spectrally narrow sensors with high spatial resolution. In MODIS NDVI, values varied within a wide range, therefore more vegetation types could be detected. Three types of NDVI changed seasonally similar to the same amplitude.MODIS NDVI reflected vegetation seasonally change more accurately. Although different vegetation types seasonally change in the same way in there types of NDVI,changes in a more temporally identical pace could be found in MODIS NDVI and SPOT-VGT NDVI compared with AVHRR NDVI.High correlation existed between the three datasets at the four scales, indicating their mostly equal capability of capturing seasonal and monthly phenological variations.Similarities of the three datasets differed significantly among different vegetation types.The correlations were strong and the deviations were small in bare land, yet the relative low correlation coefficients and large difference of NDVI value between the three datasets were found among Shrub, Needleleaf forest and Crop. In the Landsat NDVI vs.AVHRR, SPOT and MODIS NDVI comparison of absolute values, the MODIS NDVI performed slightly better than AVHRR NDVI and SPOT NDVI, whereas in thecomparison of temporal change values, the AVHRR data set performed best. Similar with comparison results of AVHRR, SPOT and MODIS NDVI, the consistency across the four datasets was clearly different among various vegetation types. In dynamic changes,differences between Landsat and MODIS NDVI were better than others for Broadleaf forest and Crop, Landsat and SPOT NDVI was better for Needleleaf forest,but Landsat and AVHRR NDVI agreed smaller than others.The advantage of prominent sensitivity of red spectrum,removing water vapor absorption band in infrared spectrum and higher spatial resolution of MODIS NDVI and VGT-NDVI, which resulted these two types data are more sensitive to the change of vegetation and more suitable to the study of vegetation than AVHRR NDVI data in Qinling area. However, there is on significant difference among the three NDVI data, and the AVHRR NDVI has longer time series than the other two data, and it still will play an important role on the study of vegetation change.