19 The hardware requirement for processing data at least has to fulfill the
specification: PC Pentium III, 256 MB RAM and 40 MB Hard disk.
3.3. Research Methodology
The procedures of this research consist of data compilation, data preparation, spatial analysis, modeling approach, and data validation. The flowchart of
research procedure is represented in Figure 3.2.
3.3.1. Data Collection
The data input is collected from various sources, e.g.: -
Topographic data which is obtained from National Coordinating Agency for Surveys and Mapping BAKOSURTANAL,
- Information of soil type is derived from regional soil maps produced
by Center for Soil and Agro Climate Research PUSLITANAK, -
Climate data were obtained from Bureau of Meteorology and Geophysics BMG and Puslittanak Bogor,
- and Imagery data.
3.3.2. Data Preparation
1. Image Processing
The first step of data preparation is to process the satellite image of research area, while the activities comprise of image processing and vector data processing
and analysis. In image processing the activities consist of identifying the data source coordinate system, format conversions, radiometric correction, geometric
correction, cropping image in research area, and image enhancement.
Figure 3.2. Scheme flowchart of the research Respondent
Data
Revenue Cost Analysis
Land Overlay Tentative Map
Land Suitability Map
Weighting
Area Selection with more
than one suitability criteria
Existing Condition
Spatial Analysis Land
Suitability Rainfall
Map Climate
Data
Image Processing
Land use Map
Landsat TM
Soil Map
Digitizing Generate
Rainfall Map Derive
Temperature Map
Soil Map Generate
Slope Map
Slope Map
Temperature Map
Topographic Map
Data Collection
Agricultural Potential Map
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Figure 3.3. Description of Image Processing The image was then classified by using Supervised Classification technique
into several types of land uses. The classification processed was completed by landuse data, which obtained from the Bantul local government.
One of main steps in image classification is the ‘partitioning’ of the feature
space. In supervised classification the process is realized by defining the spectral
characteristic of the classes by identifying sample areas training areas. A sample of a specific land use class like rice field, comprising of a number training pixels,
form a cluster in feature space. Classification Result Data
Image Enhancement Cropping Image
Landsat Imagery
21
After that, all vector data required were extracted using spatial processing
software. The landuse data result will be used for the next spatial processing and analysis steps.
2. Generated Slope Map
The topographic data provide varying altitude of the research area. A slope map was derived from the contour of topographic map and was classified into
several classes. The topographic data that used in this research were already in digital format, so for generating slope map only took the contour data and
processing by 3D analysis tool in ArcGIS 9 application.
Figure 3.4. Generating of Slope Process Contour Data
Slope Map TIN Slope
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The slopes were classed or grouped depending on the rank that each crop requires this was done based on available literature. The detail slope class of
each crop can be seen in appendix.
3. Generated Temperature Map
