The aim of this research is to study and prognosis oil and gas by utilization of Remote Sensing (RS) data Geographic Information
System (GIS) and Digital Elevation Model (DEM), and 3D. The integration of the data by using program (Arc GIS). The inte
gration data led to divide the lineaments circular structures and drainage network. Which present direct and indirection indicate on earth surface for surface and subsurface structures Which play important role in prospecting oil and gas.
This study aimed to describe the water erosion modeling in Daher Aljabal
and its surrounding areas in Al-Sowaida Governorate based on GIA and RS.
The water erosion risk map was obtained by applying GIS model developed on
the basis of ten factors i
nfluencing the erosion process. GIS layers were built
for every factor. The weights for all factors were added together. Based on sum
of these factors, water erosion was divided into six erosion risk levels. Results
showed that 12% of the study area was classified in levels 5 and 6, which reflect
high and very high water erosion risks. Land topography was the main factor
in water soil erosion. Terraces are effective ways to decrease the water soil
erodability. Results also showed that GIS and RS were powerful tools in water
erosion risk assessment mapping.
This research aimed to use space image at certain growth stage for
predicting cotton yield in its direct physio-spectral relationship with
productivity. Timely, at the beginning of August better spectral growth stage is
coincidence with a maximum
leaf area index of cotton plants at Al-Kaltta fields.
Normalized difference vegetation index (NDVI) showed superiority on each of
red and near infrared channels in relation with productivity. Exponential
model was used to predict cotton productivity depending on NDVI values
during stage that maximum LAI.
