Research Methodology in General.

13

2.3. Methodology

Changes in land use pattern are related to a large number of biophysical and socio-economic factors. The modeling of spatially explicit changes in land use pattern requires, therefore, a large database of factors considered to be important in the case study. Therefore, the database is not similar for every application. To run the model it is minimally needed to have spatially explicit data for at least 1 year. However, to allow calibration and validation model works, it is necessary to have data of another different year. To meet this necessity, the research will employ data from 2 different years, with 6 years’ time difference, i.e. 1991 and 2009.

2.3.1. Data Preparation

2.3.1.1. Data Requirement for Land Use Change Model

For the simulation of dynamics of the spatial pattern of different land use types, data are needed for the land use distribution and a number of biophysical and socio-economic parameters that are considered as important potential drivers of the land use pattern. These drivers are most commonly variables that describe the demography, soil, geology, climate and infrastructural situation. This study only considers the biophysical aspects, while the socio-economic aspect is considered constant Business as usual. The data required to analyze land use change process and build scenario development were obtained from various sources. The data are derived from multispectral satellite data, extracted from digital topographic data, and from spatial processing of statistical data. According to type, data are divided in three: remotely sensed data, digital topographic data and statistical data. How the data were collected and used will be explained below. Remotely Sensed Data Remotely data used in this study comprises of Landsat images 1991 30 m, and ALOS-AVNIR image 2009 10 m. These data will be used for land use change analysis and input for trend extrapolation to calculate land use requirements year 1991-2030. 14 Table 1. Remotely Sensed Data Requirement for Land Use Model Image Resolution Date Acquisition Source of Data Landsat TM 30 m 28 July 1991 GLOVIS ALOS AVNIR 10 m 17 July 2009 BTIC – BIOTROP Topographic data Topographic data sets are obtained from Agency of National Survey and Mapping Bakosurtanal – Geospatial Information AgencyBIG, nowadays, Bogor. These data are digitized from topographic map scale 1:25.000 and are extracted for selected layers, including road, facilities and public service distribution, and central of economic. All layer data have been digitalized, infrastructure and facilities, road, river, public services and industries location. Data sets used in this study can be seen in the following table. Table 2. Topographic Data Sets Used in Analysis Land Use Change and Scenario Development Data Set Year and Scale Class Source Collection Method Data Use Land use map 1991, and 2009; Scale 1:50.000 5 classes See Table 4 for detailed land use classification Interpretation from Landsat TM and ALOS- AVNIR images Interpretation using supervised classification Land uses data are used for land use change analysis and trends extrapolation and land demand input in CLUE-S Road 2003; Scale 1:25.000 Classified as main road, appropriate with study area Rupa Bumi Indonesia RBI, 2003 Derived from topographic map RBI Road map used as driving factors influencing land use change and pattern, it will be processed by using distance analysis to obtain classes of distance from road Elevation Data 2005, Scale 30m Continuous USGS Derived from SRTM-Level 2 Interpolation and rasterizing to obtain digital elevation data and image classification to obtain elevation class Facilities and public service distribution 2003; Scale 1:25.000 All of facilities education, health and public service facilities Rupa Bumi Indonesia RBI, 2003 Derived from topographic map RBI Facilities and public service are processed by using proximity analysis to obtain distance classes of facilities Central of Economic 2003; Scale 1:25.000 Business center Rupa Bumi Indonesia, 2003 Derived from topographic map COEs are processed by using proximity analysis Forest Designation Map 2009, Scale 1:250.000 Forest Area, Non Forest Area Directorate General of Forest Planology, Ministry of Forestry Re-delineate in GIS environment Forest designation map will be used as spatial policy in the model. Socio-economic data Statistical data in this study consist of population data in village level year 2007. Other data socio-economic are total education and health facility unit for each village in the study area year 2007.