GIS based risk modeling of soil erosion under different scenarios of land use change in Simly watershed of Pakistan

Analysis of the spatial variability of the land use classes were performed through both visual (ideal technique land use and land cover interpretation in medium and low resolution satellite images, its application being limited o high spatial resolution imagery because of the increase of details to recognize) and digital interpretation (widely accepted among the scientific community because of its statistical validation and automatic processing) (Puig et al., 2002). Supervised classification technique was petitioned outlining land use classes by selecting training samples for every individual class focused on former information and knowledge of the field and training sites were defined in the feature space image of the study area Ground truthing was additionally completed using source information/data of Google earth image to verify the classification results. Erodibility was calculated using equation 3 (Lal and Elliot, 1994). k = 2.8 x 10 - 7 x M1.14 (1.2 - a) + 4.3 x 10 - 3 (b - 2) + 3.3 x (c - 3)(3) Where M is the extent of soil particles (% residue + % fine sand)x(100 - % dirt), a is the percent of organic matter , b is the code number characterizing the soil structure (fine granular = l, fine granular = 2, coarse granular = 3, cross section or gigantic = 4), and c is the soil seepage class (quick = 1, quick to reasonably quick = 2, moderately fast= 3, moderately fast to slow = 4, slow = 5, very slow= 6) (Soil Survey Report, 1967). [...]estimation of l was relegated for estimation of potential soil loss in the watershed region.