Combine MODIS and HJ-1 CCD NDVI with logistic model to generate high spatial and temporal resolution NDVI data

Abstract

High spatial and temporal resolution Normalized Difference Vegetation Index (NDVI) data can be used to describe vegetation dynamics and provide the variation of surface for monitoring phenology and land cover change quantitatively. This paper presents a method using MODIS Land Cover data with 30m LULC map calculates the percentage of every class in the MODIS pixel. And the mean MODIS NDVI can be got through the average value of pure pixels using MODIS NBAR product from 2004 to 2010. Then the logistic model is fitted to the average MODIS NDVI to simulate the variation in NDVI time series. At last, the simulated NDVI time series of all vegetation types are extracted as background values and the HJ-1 CCD NDVI is used to adjust the curve of time-series NDVI to estimate the NDVI at high spatial and temporal resolution. The method is applied to the Heihe River basin and the region growing two crops a year. The results are compared with some filed measured data, which shows the high feasibility of the method to generate accurate and reliable data. It is proved that the method can be used in small scales to lager regions and the results can be a kind of fundamental data in other studies.