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Abstract. Historically droughts have had a huge impact on conditions of life on earth. With growing population of the Earth the impacts of droughts grow even more severe. Human beings are also affected by drought like other life forms. Studies have taken place to understand and thereby mitigate the effects of these climatological phenomena on humans. The study of drought trends is of great importance since it is directly related to food and water resources availability, that could become scarce in case of droughts. In this paper by using SPI, SSI and TSDI indices we try to understand the drought behaviour in Iran using Mann-Kendall and Sen’s slope methods. Canonical correlation analysis between SPI and SSI shows a positive correlation for the most parts of Iran. Also the correlation between TSDI and SPI/SSI is positive for majority of the Iran. Drought trends in Iran are analysed using Mann-Kendall and Sen’s slope estimator with 95% confidence level.

ABSTRACT:Due to the SAR 1 geometry imaging, SAR images include geometric distortions that would be erroneous image information and the images should be geometrically calibrated. As the radar systems are side looking, geometric distortion such as shadow, foreshortening and layover are occurred. To compensate these geometric distortions, information about sensor position, imaging geometry and target altitude from ellipsoid should be available. In this paper, a method for geometric calibration of SAR images is proposed. The method uses Range-Doppler equations. In this method, for the image georeferencing, the DEM 2 of SRTM with 30m pixel size is used and also exact ephemeris data of the sensor is required. In the algorithm proposed in this paper, first digital elevation model transmit to range and azimuth direction. By applying this process, errors caused by topography such as foreshortening and layover are removed in the transferred DEM. Then, the position of the corners on original image is found base on the transferred DEM. Next, original image registered to transfer DEM by 8 parameters projective transformation. The output is the georeferenced image that its geometric distortions are removed. The advantage of the method described in this article is that it does not require any control point as well as the need to attitude and rotational parameters of the sensor. Since the ground range resolution of used images are about 30m, the geocoded images using the method described in this paper have an accuracy about 20m (subpixel) in planimetry and about 30m in altimetry.