Geography Reference
In-Depth Information
II.
M
ETHOD AND
T
OOLS
Landsat ETM+ (2010) images were respectively processed using Erdas
IMAGINE 9.2 and ASTER images, by Arc GIS 9.3. Landsat images were
filtered for highlighting lineaments by low pass band (3x3 filter) and
directional filtering (Sobel filter 7x7). The processing of ASTER images were
carried out in Arc GIS 9.3 by spatial analyst tools with the Hydrology module
in order to generate the drainage network and Slopes. So, lineament density
and drainage density are carried out by using Line Density tool that calculates
the density of linear features in the neighborhood of each output raster cell.
Density is calculated in units of length per unit of area. All input rasters were
generated, reclassified, weighted and overlaid using Weighted Overlay
module. The Reclassification tools provide an effective way to compute the
conversion. Each class value in an input raster is assigned a new value based
on an evaluation scale. These new values were computed from the original
input raster values. Each input raster is weighted according to its importance
or its percent influence. The weight is a relative percentage, and the sum of the
percent influence weights must equal 100. Changing the evaluation scales or
the percentage influences can change the results of the weighted overlay
analysis (Silverman,. 1986). The output data were combined in the model with
parameters controlling groundwater accumulation such as rainfall, and
lithology (Al Saud., 2010, Hossam., & al, 2011). These parameters were
evaluated in terms of 5 potential classes namely: very good potentials
potential, good; moderate; and low potential and very low and weighted from
1 to 9 prior to integrate them into the GIS tools. All the thematic maps, such
as: rainfall, geology, lineament density, geology, slope, drainage density, were
converted to raster format followed by assigning respective theme weight and
class rank as shown in (Table.1). Each raster map is reclassify into five classes
of potentiality, ranging from very good potentials to very low potentials
passing through to the moderate, good and low potentials. The weighted
overlay analysis was performed ―Spatial Analyst Module‖ of ArcGIS 9.3
(Mehnaz, 2011), with integration of all the most influencing parameters
controlling groundwater storage in the study area. NDVI (Normalized
Difference Vegetation Index) from Landsat (ETM+, April 2010) was
calculated from Landsat Bands NIR (ETM4+) and Red (ETM3+) and formula
is given in (equation. 1). The NDVI is used to analyze Remote Sensing
measurements to assess the presence of live green vegetation. In areas of a
shallow water table, the presence of live green vegetation indicates the
availability of groundwater during summer and hence NDVI is highly
