Remote Sensing and GIS Applications in Environmental Sciences

- Comparative evaluation of land slope calculation algorithms using digital elevation model

Document Type : Original Article

Authors

1 Department of GIS and Environmental Hazards, Faculty of Engineering, Lenjan Branch, Islamic Azad University, Isfahan, Iran

2 Assistant Professor, Department of Environmental Hazards and Geographical Information Systems, Lenjan Branch, Islamic Azad University, Isfahan, Iran

Abstract

Digital Elevation Model (DEM) has been used in various earth science processes as one of the main sources of studies. The average slope factor of an area is one of the basic and important physical characteristics, and the calculation and determination of this factor are necessary in all plans related to earth sciences. In many experimental relationships, determining the concentration time and the average slope of the study area is the main factor and plays a decisive role in the estimations. Therefore, failure to accurately estimate and determine the average slope value will lead to incorrect estimates of the major and fundamental factors of an area. Therefore, in this research, in order to evaluate slope algorithms using a digital height model, two areas were first considered based on special conditions and characteristics. Then 30 and 90 meters of SRTM were prepared for each of these areas (DEM). By using coding in a Python environment, the slope algorithms such as neighborhood, quadratic, maximum slope, and maximum slope were calculated and the time library and psutil library were used to calculate the time of the algorithm and the memory consumption of the system. using a number of default points; Slope algorithms were spatially compared. The obtained results showed that the downhill slope algorithm obtained higher maximum values ​​and the maximum slope algorithm obtained lower values ​​compared to other algorithms.

Keywords

Main Subjects

 

هذل استفبػی سلَهی )DEM( دس پشداصؽّبی هختلف ػلَم صهیی ثِ ػ َاى یىی اص هٌبٍثغ اصلی هغبلؼبت ثىبسگشفت ؿذُ اػت. ػبهل ؿیت هتَػظ یه هٌٌغم یىی اص خصَصیبت اػبػی  فیضیىی هْْن ثَ دُ   هحبػجِ  تؼییی ایی ػبهل دس توبهی عشحّبی هشتجظ ثب ػلََم صهیی ضشٍٍسی اػت. اص ایی سٍ دس اییٍ پظ ّؾ ثٍِ هٌ ظَس اسصیبثی الگَسیتن ّبی ؿیت ثب اػتفبدُ اص هذل سلَهی استفبػی اثتذا دٍ هٌ غمِ ثشاػبعٍ ؿشایظ  ٍیظگیّبی خبف دس ًظش گشفتِ ؿذ. ػپغ ثشای ّشیه اص ایی هٌبعک )DEM( 30  90 هتشیٍ SRTM تْ یِ گشدیذ .ثب اػتفبدُ اصوذًَیؼی دس هحیظ پبیتََى الگََسیتنّبی ؿیت اِص خولِ ّوؼبیگی، دسخِ دٍٍم، ؿیتِ حذاوثش ٍ ػشاؿیِجی حذاوثش هحبػجِ  اص وتبثخبً time   وتبثخبًpsutil  ث تشتیت ثشای صهبى هحبػج الگََسیتن ٍ حبفظ هصشفی ػیؼتن اػتٍفبداػتفبدُ ؿذ. ثب اػتفبدُ اٍص تؼذادی ًمبط پیؾ فشض الگََسیتن ّبی ؿیت اص ًظش هىبی هََسد همبیٍؼِ لشاس گشفتٌٌذ. ًتبیح ثِ دػت آهذُ ًـبى داد الگََسیتن هحبػجِ ؿیت، ػشاؿیجی حذاوثش همبدیش ثبلاتش  الگََسیتن ؿیت حذاوثش همبدیش پبیییتشی سا ًؼجت ثِ ػبیش الگَسیتٍن ّب وؼت و دُ اػت.  وچٌٌیی اصًظش صهبًًی الگَسیتن ػغح دسخِِ دٍ دس ووتشیی صهبى )02/4( ثبیِ  الگََسیتن ػشاؿیجی حذاوثش دس ثبلاتشیی صهبى )13/7( ثبیِ هحبػج گشدیذ. الگََسیتن ػشِاؿیجی حذاوثش ًیض ثبلاتشیی همذاس حبفظِ (RAM) سا دس هٌ غمِ اٍٍل ٍ ثب ا

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Remote Sensing and GIS Applications in Environmental Sciences
Volume 2, Issue 4 - Serial Number 4
October 2023
Pages 16-1
  • Receive Date: 05 October 2022
  • Revise Date: 13 November 2022
  • Accept Date: 05 March 2023