JWSS - Journal of Water and Soil Science

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Of the applications of remote sensing and satellite images in natural resources is distinguishing and detection of changes in land surface. The image classification using Maximum Likelihood (MLC) is one the prevalent method which is used in a study of the application of TM and ETM+ satellite images to detect sediment deposition on an implemented floodwater spreading scheme. In order to implement the research, field sampling and checking were done using transect networking method by selection of 30 sample points in floodwater spreading area as well as another 30 control points in the study area. The results of the study are shown that detection of sediment deposition using MLC method by application of LANDSAT TM and ETM+ can lead to increase the precision of change detection up to 82 percent. Furthermore, the results also show that the trend and changes due to sediment deposition on water spreading area can be precisely detected. Considering the present and potential applicability of the applied method in distinguishing changes due to sediment deposition on land surface which is absorbed on 450 hectares of water spreading area in this research study, it can be pointed out that the use of this method in larger area could be tend to increase the precision of change detection and to decrease the required time.

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Integrated management of watershed basins depends on deep knowledge of basic concepts such as the arrangement of lands and their uses. Location and distribution of agricultural land use help to balance water resources in the watershed basins. In this research with the help of satellite images of Landsat 5 and 8, and the method of maximum likelihood classification algorithm, land use types of water, barren areas and salt lands, and irrigated agriculture were studied in the Urmia watershed in the years 2010 and 2013.Then applications of modis images and product Urmia watershed land cover for years 2010 and 2012 were compared and finally modis and Landsat land covers in 2010 were compared. Results showed that the area of irrigated farmlands of Urmia basin has increased in the years between 2010 and 2013; while, the water zone has declined. Comparison between modis and landsat in 2010 showed that modis can estimate irrigated lands and water zone better than barren areas. The kappa coefficient for years 2010 and 2013 in Landsat images are 0/77 and 0/87, respectively.