Environmental Engineering Reference
In-Depth Information
method useful for land use classification with a more smoothing capacity. Then, all
GIS layers were projected onto the following projection system:
NTF_Lambert_Zone_III
Projection: Lambert_Conformal_Conic
False_Easting: 600000.00000000
False_Northing: 200000.00000000
Central_Meridian: 2.33722917
Standard_Parallel_1: 43.19929139
Standard_Parallel_2: 44.99609389
Scale_Factor: 1.00000000
Latitude_Of_Origin: 44.10000000
Linear Unit: Meter
Geographic Coordinate System: GCS_NTF
Datum: D_NTF
Prime Meridian: Greenwich
Angular Unit: Degree
3.2 DEM Quality Control Modeling
This part was carried out to analyze the effect of statistically improved DEM on
the outputs of the flood inundation model in comparison with the existing DEM.
According to Vaze [ 1 ], one of the most commonly used and widely available basic
spatial information models, especially in hydrodynamic simulation, is the DEM.
Alkema [ 2 ] also realized in the related research that within hydraulic modeling, the
output is affected to a large extent by model input parameters, and a reliable input
data set is required to accomplish successful modeling [ 3 ]. Therefore, in preparing
the input data, a major emphasis has to be placed to increase the quality of the
DEM as much as possible.
The DEM applied in this research, with 5 and 10 m resolutions, was derived
from Radar, which was retrieved from the OMIV Coordinator, OSUG-LGIT of
France. The DEM was controlled using a variety of interpolation methods. All the
interpolation methods were available in the Geostatistical Analyst extension of
ArcGIS and use observed points as input data. The selected interpolation methods
were commonly used and suggested by many investigators
3.2.1 Interpolation Techniques
The quality of a derived DEM can vary greatly depending on the data source and
the interpolation technique which is applied. Burrough and McDonnell [ 4 ] have
defined the interpolation method as a technique to construct and predict the new
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