Rating Absolute Measurement Supervised Classification

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2.8 Rating Absolute Measurement

Duarte Junior 2005 defines ratings as a set of intensity levels or categories that serves as a base to evaluate the performance of the alternatives in terms of each criteria andor sub criteria. The categories that form the ratings must be clearly defined, in the less ambiguous way as possible, to adequately describe the criterionsub criteria. The rating is considered suitable as the decision makers consider it an appropriate tool to evaluate alternatives. Figure 8 shows the hierarchy structure from the rating mode. The hierarchy begins with the global objective. The criteria are at the second level. The categories associated to the sub criteria are at the last level. The structure with ratings differs from the traditional AHP relative measurement, because in the last level the alternatives are not found. The evaluation is performed by intensity levels categories attributed to each sub criteria related to each alternative, instead of evaluating the alternatives by pair wise comparisons. The main advantage of using ratings is to decrease the number of comparisons necessary when there are a large number of alternatives. Besides, when using absolute measurement ratings, it does not matter how many new alternatives are introduced, or old ones are excluded because there is no inversion of the alternatives ranking. In this research AHP application with ratings use the software Expert Choice version 9.50A05.

2.9 Supervised Classification

A classification describes the systematic framework with the names of the classes and the criteria used to distinguish them, and the relation between classes. In image classification there are two classification technique kinds that commonly known, supervised classification and unsupervised classification involves a training step followed by classification step. In the unsupervised approach the image data are first classified by aggregating them into natural grouping or clusters present in the scene Lillesand and Kiefer, 1987. 20 In supervised classification this is realized by a operator who defines the spectral characteristics of the classes by identifying simple areas training areas. Supervised classification requires that the operator be familiar with areas of interest. The operator needs to know where to find the classes of interest in the area covered by the image. This information can be derived from general area knowledge or from dedicated field observations Janssen and Goerte, 2000. Supervised classification is the procedure most often used for quantitative analysis of remote sensing image data. It rests upon using suitable algorithm to label the pixels in an image as representing particular ground cover types, or classes. A variety of algorithms is available for this, ranging from those based upon probability distribution models for the classes of interest to those in which the multi spectral space in partitioned into class-specific using optimally located sutface Richards, 1993. 21

III. METHODOLOGY

3.1 Time and Location

This research was conducted from February to July 2011 that consisted of data collection, data analysis, method development, and model analysis. The data were collected from some government agencies such as meteorology, climatology, and geophysics agencies BMKG and rainfall gauges station near to the study area. The data analysis, method development and model analysis were accomplished at Bogor Agricultural University. The study area is located in Banyuasin Regency, South Sumatra, Indonesia, which covers an area of 11,832.99 Km 2 or about 12.18 of South Sumatra Province and consists of 15 fifteen sub regencies. Banyuasin Regency is located between 1 18’ 00” and 4 00’ 00” South and 104 40’ 00” and 105 15’ 00” East Figure 3, with the regency boundaries as follows: Northern part: Muara Jambi Regency, Jambi Province and Bangka Strait, Eastern part: The Air Sugihan of Ogan Komering Ilir Regency, Western - part: The Sei Lilin Sub Regency, Lais, Bayung Lencir of Musi Banyuasin regency, Southside: Abut The Sira Pulao Padang Sub Regency of Ogan Komering Ilir; Gulumbang Sub Regency, Talang Ubi Sub Regency of Muara Enim Regency. Figure 3. The Study Site