41 The squared shape of cells will be clipped with polygon
boundary of study area. The result will be shown in Figure 4.8. Illustration of the attribute table that accommodate all the
tabular data as the result of extracting binary data 0 and 1; and statistical calculation from each independent variables and is shown
in Appendix II. By using Query builder in ArcView, shapefile as the result of
extracting contour by Global Mapper can query the polygon greater than or equal 250 meters to obtain the area with topography greater
than or equal 250 meter. Polygon that greater than or equal 250 meters is identified as 0 and less than 250 meters as 1. These both
values must be entered inside the whole cells as wide as the study area. Each cell have to be filled by either value 0 or 1.
Joining process to fill each cell, will be easy by using ArcView Extension, Edit Tool 3.5 - Geoprocessing Assign data by
location Spatial Join - Inside. This tool will join the ID of cell correlated by either value 0 or 1 as the attribute source and squared
shape polygon as target, saved as by a name Polygon VectorCell PVC.
The results process are spatial and its attribute, that must be saved into a new shapefile.
4.2.2. Data Extracting of Contour from SRTM Data Image
Image data of topography was obtained from GLCF Global LandCover Facility website http:glcf.umiacs.umd.eduindex.shtml
in .tif format TIFF. The .tif Tag Image File is displayed by ERDAS Imagine 8.7 and using AOI Area of Interest and Raster
Contrast the image will appear Figure 4.9. Both boundary of Nature Reserve Cagar Alam Cibanteng
and Wildlife Reserve Suaka Margasatwa Citepuh is needed to subset the SRTM image to obtain contour vector data by ERDAS Imagine
8.7 subset feature. Extracting contour itself was done by using Globar Mapper 7 program.
Actually SRTM data have XY resolution 90 meters, for this purpose generate contours will be 50 meters interval. Global Mapper
7 in this case will interpolate 90 meter resolution into 50 meters interval.
Figure 4.9
. SRTM Shuttle Radar Topography Mission data of topography was obtained from GLCF website, and displaying by ERDAS
Imagine 8.7 .
Un-scale Vector Map
Figure 4.10. The result of assigning data by location spatial join of contour or
altitude data LogR_Alt, where yellow cells is altitude 250 m 1 and light blue is
≥250 m 0. 42
43 After extracting contour data, there should be two value of
contour as dependent variables that going to be used in logistic regression analysis. The values of independent variables are 0 for
polygon or contour greater or equal than 250 meters and 1 for less
than 250 meters. These values was added in a column LogR_Alt, in
PVC attribute data. Joining PVC and contour data can be done by Edit Tool 3.5
and Assign Data by Location Spatial Join tool Figure 4.10. The value of 250 is based on statistical data that the elevation
of Ciemas and Ciracap subdistrict is between 0 -1000 meter from sea level BPS 2000. 250 meter height from sea level is assumed that
deforestation tend to occur more compared to 250 meter up.
4.2.3. Data Extracting River Buffer Process
The attribute such as river name should be exist, and make sure all features correctly spatial such as no split line, and so on. If
no, it needs to be edited . This river feature was buffered as a specified distance 1,000
meters on the right and left side. River buffer is an area, so it is possible two or more rivers will
join each other become a wider area, so that inside the buffer area means less than 1 kilometers 1,000 meters will be named by a
group of rivers buffered area and numbered by 0. Greater or equal than 1,000 meters will be valued by 1 or non-buffered Area.
LogR_Riv is made for identifying value of 0 and 1.
According to Jianquan and Messer 2001 that in their research in Wuhan City, China have categorized the independent
variable of distance from river and road into 2,000 meter buffered. The category variable value of distance from river less than 1 km in
this research is based on the small study area, and according to the river networking. In this research, only big river was analyzed.
By the same procedure with to extract contour, attribute data of buffered river have to be assigned data by location spatial join to
included in PVC attribute data, and the result can be seen in Figure 4.11.
Un-scale Vector Map
Figure 4.11.
The result of assigning data by location spatial join of river
buffer LogR_Riv 1,000 m, where yellow cells is river or group of river 1,000 m 1 and light blue is
≥ 1,000 m 0.
4.2.4. Data Extracting of Road Buffer Process
