Marzieh Mokarram; Majid Hojjati; Abdol Rassoul Zareiee
Abstract
Extended Abstract Topography is a factor controlling the spatialdistribution of soil moisture, vegetation, soil salinity, soil texture andso on. It has an important role in changing thecharacteristics of the soil and hydrological processes. In recent yearsthe topographyhave been used as an important ...
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Extended Abstract Topography is a factor controlling the spatialdistribution of soil moisture, vegetation, soil salinity, soil texture andso on. It has an important role in changing thecharacteristics of the soil and hydrological processes. In recent yearsthe topographyhave been used as an important factor forpredicting the properties of soil, climate, geology, etc. According tothe importance of topography to extract different information, use ofsatellite images with high spatial resolution seems very necessary. Digitalelevation models (DEM) have become a widely used tool andproduct in the last 20 years. They provide a snapshot of the landscape and landscape features while also providingelevation values. They have allowed us to better visualize andinterrogate topographic features. In addition to increasing the spatial resolution, information of the digital elevation model (DEM) that isthe most important issues in quantitative geomorphology have increased. In orderto increase the spatial resolution several modelshave been proposed. Among the models, the attraction model as the newest modelhas very high accuracy. The sub-pixel attraction models convertthe pixel towards sub-pixels based on the fraction valuesin neighboring pixels that can be attracted only by centralpixel. Based on this approach only a maximum of eightneighboring pixels can be selected for the attraction. In themodel, other pixels are supposed to be far from thecentral pixel to have any attraction. In this study byusing sub-pixel attraction model, the spatial resolution of digitalelevation models (DEM) was increased (Sub-pixel mapping technology is apromising method of increasing the spatial resolution of the classificationresults derived from remote sensing imagery). The design of thealgorithm is accomplished by using digital elevation model (DEM) withspatial resolution of 30 m (Advanced Space borne Thermal Emissionand Reflection Radiometer (ASTER)) and 90 m (Shuttle Radar TopographyMission (SRTM)). This study was carried out in the EastMount Sahand, Iran is located at the longitude of N 37° 31َto 37° 30َand latitude of E 45° 55َto 45° 58َ. It is expected that usingattraction model increasesthe spatial resolution of DEM. The attraction model does not need any calibration and training similar to the machine learningalgorithms. So, to run the algorithm in the model, the computing time was reduced. In attraction model, scale factors of (2, 3 and 4) with two neighboring methods of touching andquadrant are applied to DEMs using Matlab software and thenusing RMSE (Root mean square error), determined the best model. The algorithm is evaluated using 2118 sample points that aremeasured by surveyors. As the result of Root mean squareerror (RMSE), it showed that the spatial attraction model withscale factor of (S=2 and T=2) for digitalelevation model (DEM) 30m and digital elevation model (DEM) 90mgives better results compared to scale factors that are greaterthan 2 and also touching neighborhood method proved to bemore accurate than quadrant. In fact, subtracting each pixel tomore than two sub-pixels caused to decrease the accuracyof resulted DEM which makes the value ofroot mean square error (RMSE)to increase and showed that attraction modelscould not be used for S which is greater than 2. So, according to the results, it is suggested that themodel to be used for increasing spatial resolution of DEM in the studiescatchment. Comparing the digital elevation model (DEM) as inputsin the attraction models determined that digital elevation model (DEM) 30 m (root mean square error < 5.54) has better spatialresolution than digital elevation model (DEM) 90 m (root meansquare error = 9.13) to find the best model for increasingspatial resolution. The results showed that by using the method, thespatial resolution of digital elevation model (DEM) with lower timeand cost could be increased. Digital elevation model (DEM) mapwith high resolution as a base can be used for findingmore information from the Earth surface. For different study such asamount of vegetation, temperature, rainfall and hydrological status the results of sub-pixel attractions on digital elevation model (DEM) can be used and more details of study area could be found. Therefore, it issuggested that the same researches should be done in other areas withdifferent topographic and geographical conditions in order to confirm theresults of this study.
