Landforms are one of the most important landscape components in lithosphere that the landform elements include land such as hills, mountains, plateaus, canyons, valleys… The main objective of this study is Landforms classification by Topographic Position Index and assessment of the relation between landforms and lithological features. For landform classification, the 10 m Digital Elevation Model (DEM) and Geology map (1:100000) was used. In this paper Topographic Position Index and the Deviation from mean elevation (DEV), were used for classification of landforms. Result shown that, the valley was the largest category, with percentages 33.37 %. The lower slops was the lowest category, with percentages 5.63 %. Each of the other four categories (flat area, middle slope, upper slope and ridge) represented between 5.8 % and 30.79%. Accordant to these result, the most variable classes were the valley, increasing from 20.62% (50 m) to 55.7% (750 m), and the middle slope area, decreasing from 6.4% (50 m) to 1.01% (750 m). The results of ANOVA shown a significant relationship at 99% probability level for landform classification map and geology formation map. More than 60% limestones (OMl, El, TRjm, K2, TRkh, Jgr-vc, OMas, K1) were middle slopes, upper slopes and ridge.
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(2018). Landforms classification by Topographic Position Index and assessment of the relation between landforms and lithological features. Researches in Earth Sciences, 9(1), 30-45. doi: 10.29252/esrj.9.1.30
MLA
. "Landforms classification by Topographic Position Index and assessment of the relation between landforms and lithological features". Researches in Earth Sciences, 9, 1, 2018, 30-45. doi: 10.29252/esrj.9.1.30
HARVARD
(2018). 'Landforms classification by Topographic Position Index and assessment of the relation between landforms and lithological features', Researches in Earth Sciences, 9(1), pp. 30-45. doi: 10.29252/esrj.9.1.30
VANCOUVER
Landforms classification by Topographic Position Index and assessment of the relation between landforms and lithological features. Researches in Earth Sciences, 2018; 9(1): 30-45. doi: 10.29252/esrj.9.1.30