Several satellite sensor systems useful in Earth observation and monitoring have recently been launched and their derived products are being used in regional and global vegetation studies. The joint use of these multi-resolution sensors offers many opportunities for vegetation studies. Spectral vegetation indices obtained from Landsat, Spot, IRS and other sensors are now widely available for monitoring ecosystem dynamics. However, the joint use of data from different satellites requires inter-satellite cross-calibration. We will use a multi-temporal data synthesising procedure for this purpose.
In this paper we analyze the broadband reflectance and NDVI relationships among the various relevant sensors. The key to the method is in using synchronous or nearsynchronous imagery from different sensors.
Comparison between reflectances for different bands shows that a linear function fits well to describe the relation between different sensors. Observations made from different sensors at different spatial scales can be reliably compared only if they are spatially aggregated to an adequate grid size. This minimum spatial aggregation size depends on the spatial resolution of the sensors involved in the comparison. In any case, it must be at least 3 x 3 pixels of the coarser resolution sensor.