Evaluation of terrain geomorphometric characteristics for ground clearance charts production

Geomorphometric exploration applied in the military terrain analysis is based on the GIS methodology of spatial analyses and is related primarily to military terrain analyses. It includes relief assessment aiming at producing ground clearance charts for the analysis of terrain maneuverability and its deployment, cover and concealment possibilities. An evaluation analysis of geomorphological parameters was performed for the Avala test area using a few terrain parameters (visibility, terrain aspect and slope) as well as some terrain qualitative categories (e.g. vegetation density). Terrain slope Slope and aspect are morphometric terrain parameters that can be derived directly from the DTM using some GIS operations. Slope is the first derivative of a surface and has both magnitude and direction. Slope is perhaps the most important aspect of the surface form, since surfaces are formed completely of slopes, and slope angles control the gravitational force available for geomorphic work. Mathematically, the tangent of the slope angle is the first derivative of altitude, and it is a tangent or percent slope as this surface parameter is generally referred to. Slope is defined at each point as the slope of a plane tangent to the surface at that point. In practice, however, slope is generally measured over a finite distance, especially when data are obtained from a contour map. Terrain aspect Aspect is also the first derivative of a surface and has both magnitude and direction. The term aspect is defined as the direction of the biggest slope vector on the tangent plane projected onto the horizontal plane. Aspect is the bearing (or azimuth) of the slope direction, and its angle ranges from 0 to 360°. Analyses of terrain slope and ground clearance for military forces The analysis of land assessment of the Avala test area included the definition of relief categories in relation to cover and concealment purposes with the aim to include the geomorphological basis into the standard military procedure OCOKA (Observation and fields of fires; Cover and concealment; Obstacles and movement; Key terrain; Avenues of approach). A few parameters of relief significantly influencing the possibilities for cover and concealment (visibility, slope and aspect) were included into the definition of the model of terrain spatial analysis The morphometric data included in partial assessment categories were determined on the basis of the digital model relief analysis and by using GIS tools and given morphometric relief exploration methods. Analysis of vegetation effects on ground clearance for military forces Vegetation, in addition to terrain slope, presents one of the main factors in cross-country analyses and ground clearance assessments. In classification and extraction of vegetation from satellite images, numerous algorithms of two basic classification types, supervised and unsupervised classification, are applied. Supervised classification requires the identification of cover types of interest by user. Samples of pixels are then selected, based on available ground real information to represent each cover type. These samples are called training areas. The selection of appropriate training areas is based on the analyst's familiarity with the geographical area and his knowledge of the actual surface cover types presented in the image. Thus, the analyst 'supervises' the categorization of a set of specific classes. Unsupervised classification basically reverses the supervised classification process. Spectral classes are grouped first, based solely on the numerical information in the data, and then they are matched by the analyst to information classes (if possible). Programs, called clustering algorithms, are used to determine the natural (statistical) groupings or structures in the data. The analyst usually specifies how many groups or clusters are to be looked for in the data. In addition to specifying the desired number of classes, the analyst may also specify parameters related to the separation distance among the clusters and the variation within each cluster. The result of this iterative clustering process may result in some clusters that the analyst will want to combine subsequently, or clusters that should be broken down further on - each of these requiring a further application of the clustering algorithm. Thus, unsupervised classification is not completely without human intervention. Study area and THE used data The Avala hill test area, located in the central part of the Republic of Serbia, has been mapped extensively over the years and several GIS layers are available at various scales. The study area corresponds with one sheet topographic map at a scale of 1:25 000 (TM25 430-3-1) produced in the Military Geographical Institute (MGI). The main geomorphometric features of the test area include hill summits and shoulders, eroded slopes of small valleys, valley bottoms, a large abandoned river channel, and the river terrace. The elevation of the area ranges from 70 m to 500 m with an average of 195.05 m and a standard deviation of 56.7 m. The basic sources of information were the SPOT 5 image and the digital elevation model generated from the contour lines.