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The applied methodology that are used for habitat description – classification was based on broad scale GIS of the Egyptian lands.
The approach to the formation of common geo-informational space (GIS) of the territories on the base of using of space information with features of fuzzy approach to its processing is proposed in the paper.
Using existing data on the deer population spatial distribution and size, as well as data on the landscape and ecological properties (GIS) of the area inhabited by this population, we develop a habitat suitability model by automated data analysis using machine learning of classification trees.
We extracted three main classes of ground covers from a GIS of the Soil Occupation Model classification database [22]: artificial urban cover (including 54 habitat classes such as buildings, parking or roads), open urban cover (including 14 habitat classes such as gardens) and rural cover (including 15 habitat classes like forest and crop fields).
Landscape scale variables were determined a posteriori using a Geographic Information System (GIS) of the study area, in a grid (30 × 30 m) corresponding to the available digital elevation model (DEM) for the study area (Fig. 1).
GIS of the HDSS generates spatial data: geo-coordinates of each bari (group of households that share a common yard and whose heads are usually related by blood) and land marks (tube-wells, health facilities, schools, markets, mosques and temples) in degree decimal format.
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State-of-the-art GIS technologies are used in processing space images and compiling landscape maps.
With the help of GIS, the number of streams of different orders and the total number of streams in the basin are counted independently (Table 2).
This paper will focus on the development of the GIS for the purpose of development control.
The GIS record of the drainage system shown in Fig. 1 is probably incomplete.
GIS analysis of the spatial variability in arsenic indicates groundwater having no arsenic.
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