Data Preparation Land Use Change Model and Significant Variables
61 change in the research site. The natural environment included 8 data layers, the
human environment included 16 data layers, and policy included 4 data layers. Table 13. Data Layers Used in This Research
Data Layer Unit
Period of Data
Source Dependent Variable
Land Use Change 2002 – 2005 chgn0205
categorical 2002 - 2005
Land Use Change Detection
Independent Variables - Natural Environment Distance from existing Forest land
frstdist meters 2002,
2005, 2008
Land Use Classification
Distance from existing Cropland cropdist
meters 2002, 2005,
2008 Land Use
Classification Distance from existing Grassland
grasdist meters 2002,
2005, 2008
Land Use Classification
Distance from existing Wetlands wetdist
meters 2002, 2005,
2008 Land Use
Classification Distance from existing Other lands
othedist meters 2002,
2005, 2008
Land Use Classification
Distance from existing River rivdist meters 2002,
2005, 2008
Land Use Classification
Slope slope percents
2002 - 2008 SRTM-DEM 90m
Altitude alt meters
2002 - 2008 SRTM-DEM 90m
Independent Variables - Human Environment Continued to the next table
Distance from animal husbandry animdist
meters 2002 - 2008
District Government Distance from economic infrastructure
econdist meters
2002 - 2008 District Government
Distance from education infrastructure educdist
meters 2002 - 2008
District Government Distance from environment infrastructure
envidist meters
2002 - 2008 District Government
Distance from fishery infrastructure fishdist
meters 2002 - 2008
District Government Distance from government service
infrastructure govdist meters
2002 - 2008 District Government
Distance from health service infrastructure healtdist
meters 2002 - 2008
District Government Distance from industry inddist
meters 2002 - 2008
District Government Distance from mining area mindist
meters 2002 - 2008
District Government Distance from road roaddist
meters 2002 - 2008
District Government Distance from existing settlement
settledist meters 2002,
2005, 2008
Land Use Classification
Distance from telecommunication infrastructure teledist
meters 2002 - 2008
District Government Distance from transmigration area
transmdist meters
2002 - 2008 District Government
Distance from transportation infrastructure transpdist
meters 2002 - 2008
District Government Distance from public space pubspadist
meters 2002 - 2008
District Government Population density at sub district level
popdens personskm2 2002,
2005, 2008
District Government Continued to next page
62 Table 13. Data Layers Used in This Research Continue
Data Layer Unit
Period of Data
Source Independent Variables - Policy
Sub district Area sdisarea hectares 2008
District Government
Forestry Spatial Plan at National Level kwsid
categorical 2000 - 2008
National Government Spatial Plan at Province Level rtrwpid
categorical 2000 - 2008 Province
Government Forestry and Crop Spatial Plan at
District Level concessid categorical
2002 - 2008 District Government
Note: the period of data which are separated with coma , mean the data are available for each year, whereas the period of data which are separated with dash - mean the data are available as
single data for its period.
The land use change 2002 – 2005 has 26 categories regarding to 26 land use change transitions which happen in Siak District. Each land use transition has
been coded into integer number 1 – 26 which expressed its unique land use transition as illustrated in Table 8 and Figure 17 of this report. The natural
environment theme included distance from existing Forest Land, Cropland, Grassland, Wetlands, Other lands, and river which have been produced by
applying the Euclidean distance measurement into each appropriate layer, and altitude and slope which have been derived from SRTM-DEM 90m data.
Distance from Forest land frstdist Distance from Cropland cropdist
Distance from Grassland grasdist Distance from Wetland wetdist
Figure 24. Data Layers of Independent Variables: Natural Environment Theme
63
Distance from Other lands othedist Distance from River rivdist
Altitude alt Slope slope
Figure 24. Data Layers of Independent Variables: Natural Environment Theme Continue
The human environment theme included distance from animal husbandry, economic infrastructure, education infrastructure, environment infrastructure,
fishery infrastructure, government services infrastructure, health services infrastructure, industry, mining area, road, settlement, telecommunication
infrastructure, transmigration area, transportation infrastructure, and public space, which have been also produced by applying the Euclidean distance from each
layer, and population density at sub district level.
Distance from animal husbandry animdist
Distance from economic infrastructure econdist
Distance from education infrastructure educdist
Distance from environment infrastructure envidist
Figure 25. Data Layers of Independent Variables: Human Environment Theme
64
Distance from fishery infrastructure fishdist Distance from government service govdist
Distance from health service healtdist Distance from industry inddist
Distance from mining area mindist Distance from road roaddist
Distance from settlement settledist Distance from telecommunication
infrastructure teledist
Distance from transmigration area transmdist Distance from transportation infrastructure
transpdist
Distance from public space pubspadist Population density at sub district level
popdens
Figure 25. Data Layers of Independent Variables: Human Environment Theme Continue
65 The policy theme included sub districts area in Siak District and spatial
plan of Siak District in three administrative levels that are Forestry Spatial Plan at National Level, Spatial Plan at Province Level, and Forestry and Crop Spatial
Plan at District Level. In national level, Siak District is divided into 10 categories, whereas in province and district level is divided into 17 categories and 4
categories respectively. The description of the spatial plan category for each level is shown in Appendix 2.
Sub district Area sdisarea Forestry Spatial Plan at National Level kwsid
Spatial Plan at Province Level rtrwpid
Forestry and Crop Spatial Plan at District Level concessid
Figure 26. Data Layers of Independent Variables: Policy Theme After the spatial data layers for MLR modeling have been prepared, the
next to be prepared was the dataset of dependent and independent variables in the form of attribute table which would be analyzed in statistical MLR model
computation. The dataset of dependent and independent variables for MLR modeling have been taken from sampling point data of data layer of dependent
variable which is land use change 2002 – 2005. The sampling point data has been generated by using weighted probability distribution which is provided in Hawths
Tools. Each land use transition would have different number of sampling points which are associated with the values in the raster and the spatial distribution of
each land use transition. The number of sampling points for each land use transition should exceed 30 points in order to fulfill the minimum requirement of
sampling data in statistics computation.
66 Based on the experiment done several times for generating the sampling
points, the number of sampling points which could meet the criteria of minimum 30 points for each land use transition was 10,000 points. With 10,000 sampling
points, the lowest number of points that could be possessed by a land use transition was 31 points, and the highest was 1,999 points. The spatial distribution
of sampling points for each land use transitions can be seen in Figure 27.
Table 14. Number of Sampling Points for Each Land Use Transition
Land Use Transition ID
Number of Pixels
Number of Points
Land Use Transition ID
Number of Pixels
Number of Points
1 3,143,519 524 14
30,101 146 2
562,561 175 15
70,126 186 3
510,340 201 16
143,071 358 4
9,397 37 17
126 40 5 285,611
251 18
957 54
6 262,706 294
19 2,216 55
7 1,877,971 1,999
20 84,064
252 8 719,211
932 21
336 46
9 25,249 154
22 38,065 166
10 130,234 334
23 162,525 548
11 117,739 283
24 90,966 256
12 617,651 1,156
25 7,666
31 13 727,910
1,449 26 25,464
73 Continued to next table
Total 9,645,782 10,000
Figure 27. Spatial Distribution of Sampling Points Furthermore, all spatial data layers which have been prepared in ERDAS
Imagine raster data were spatially joined into the sampling point data which has
67 been generated in order to produce the dataset of dependent and independent
variables. After the spatial join have been done to each data layer, the attribute table of sampling point data would contain land use transition IDs and its related
independent variables. The attribute table of spatially joined sampling point data would be analyzed in MLR model analysis in SPSS software in order to determine
the significant variables driving factors of land use change and also to find the adequate model of land use change in Siak District.
In this research, the land use change model has been developed in two scenarios: 1 using all significant variables determined by the MLR model
analysis and 2 using observed variables determined by the observation of existing condition in the field. Hopefully, these two scenarios may facilitate the
understanding in developing land use change model using MLR model.