3 years ago

Morphometric analysis of stream as one of resources for agricultural lands irrigation using high spatial resolution of digital elevation model (DEM)

The aim of the study in this area is the extraction of streams using a sub-pixel spatial attraction model as a new method for increasing spatial resolution of digital elevation model (DEM) in the north of Darab, Fars province, Iran. The sub-pixel attraction models convert the pixel to sub-pixels based on the fraction values in neighboring pixels that can be attracted only by a central pixel. Based on this approach only a maximum of eight neighboring pixels can be selected for the attraction. In the model, other pixels are supposed to be far from the central pixel to have any attraction. In this study, the spatial resolution of digital elevation models (DEM) was increased by using sub-pixel attraction model. The design of the algorithm is accomplished through using digital elevation model (DEM) with spatial resolution of 30m (Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)) and 90m (Shuttle Radar Topography Mission (SRTM)) in the north of Darab, Fars province, Iran. In attraction model scale factors of (2,3,4) with two neighboring methods of touching and quadrant are applied to DEMs using Matlab. The algorithm is evaluated using 487 sample points that are measured by researchers. As the result, it was revealed that the spatial attraction model with scale factor of (S=2) gives better results compared to scale factors that are greater than 2 and also touching neighborhood method proved to be more accurate then quadrant. In fact, subtracting each pixel to more than two sub-pixels caused to the decrease of the accuracy of resulted DEM which leads to the increase of the value of root-mean-square error (RMSE) and showed that attraction models could not be used for S which is greater than 2. So according to the results, it is suggested that the model can be used for increasing spatial resolution of DEM in the studies catchment.

Publisher URL: www.sciencedirect.com/science

DOI: S016816991731089X

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