Assimilation MODIS and HJ-1 Reflectance Images to Produce NDVI of High Spatial and Temporal Resolution

NDVI time series represent vegetation changes on land surfaces in time and space. MODIS, revisiting the earth once or twice a day, provides time series NDVI, which is a big advantage in global change study. However, the 1-km resolution of MODIS is too low to quantify the changes of heterogeneous landscapes. HJ-1 30-m CCD sensor can show detailed spatial information, but is affected badly by the weather, which has limited its use in studying biophysical process evolving rapidly in growing season. In cloudy areas, the problem is compounded, only several images can be obtained in a year. In this study, a data assimilation method was used to combine the advantages of the high temporal information of MODIS and the high spatial information of HJ-1 CCD to generate high temporal and spatial resolution NDVI to meet the need of the applications requiring NDVI in time and space. The MODIS multi-year mean NDVI time series for each type of vegetation is used as background field, and HJ-1 NDVI of the corresponding type of vegetation is taken as observations. The uncertainties of the two kinds of data sources are also taken into account. In this paper, MODIS 16-day NBAR product and HJ-1 30-m reflectance images, which NDVI are derived from, are used to produce the 16-day NDVI at HJ-1 spatial resolution in Heihe River Basin, Gansu province, China, in 2009. And comparing the assimilated data with the filed data, the results show that, the assimilated data and ground data are in good agreement, so this method used in our study is feasible.