NDVI obtained from NOAA AVHRR is suitable for vegetation monitoring at global scale. However, NDVI values are affected not only by seasonal changes of vegetation but also by other factors, such as anisotropy of ground, cloud, and atmospheric effect. In this paper, we propose a new method of correcting reflectance to remove undesirable variations from NDVI. This method is based on statistical time series analysis. Simple BRDF model is modified to state space model, which is a kind of time series model, and Kalman filter algorithm is applied for the estimation of surface reflectance. The result of sample points shows the possibility of correcting the ground reflectance. And some are discussed for the further improvement.
A method for spatial resolution enhancement based on Maximum Entropy Method (MEM) with simulated annieling is proposed. Using overlap sampling with a low resolution of sensor, high spatial resolution (corresponding to the sampling interval) can be achieved through ground data processing with image restoration methods. Through the experiments with simulation imagery data derived from AVHRR data, it was found that spatial resolution enhancement can be achieved, MEM is superior to the others when S/N is poor (less than 33) while Conjugate Gradient method is superior when the S/N is higher than 33. It was also found that the Conjugate Gradient method is superior to the proposed method for the existing sampling jitter.
A discovery of the buried Egyptian remains has been made by using satellite SAR data. L-band (HH) signal of SIR-C (Shuttle imaging Radar Mission-C), which was very similar to the characteristics of the existing Egyptian pyramids, was detected on a hilltop of Saqqara where nothing has been reported so far. As the result of the ground truth, some artificial lime stone blocks and significant fragments were found. The area is situated approximately 200m west of the pyramid of Merenre. This is a preliminary report of the study for satellite SAR application in Egypt.