19 To achieve the validity of land use change estimation, the model should be
supported by the procedure to identify the driving factors that are statistically independent and to determine the significance of driving factors. One of methods
to identify the driving factors that have significant contribution to land use pattern is the stepwise procedure. In the stepwise procedure, all of driving factors are
involved in one step and eliminated according to their significance values. A driving factor that has a lower value than the significant threshold will be excluded from
the analysis. In forward procedure, the analysis starts with one factor and continues to other factors respectively.
ROC Relative Operating Characteristics is a method to measure the goodness of the statistical model. The probability of each land use resulted from
logistic regression is compared to the real land use map to calculate the equal category of each grid cell between those maps. According to Pontius and Schneider
2001, this method will depict the capability of regression equation to represent land use characteristics. The range of ROC value is between 0
– 1, where ROC value below 0,5 is categorized in low or completely random, 0,5
– 0,6 is good, 0,6 – 0.99 is very good and 1.0 is fitperfect. The goodness of the logistic regression
equation to represent land use condition indicates the suitability of driving factors as determinant of land use change.
2.3.3.4. Land Use Type Specific Conversion
Conversion setting for specific land use type is addressed to determine the temporal dynamic of the simulation by using reversibility of land use changes. This
method will be implemented by using three different decision rules that represent the situation of study area:
1. Some land use types are unlikely to be converted into another land use type
after first conversion. 2.
Other land use types are converted more easily. Forest and grassland are more likely to be converted into another land-use type soon after their initial
conversion without any restrictions.
20 3.
Other remains land use types operate in between those settings, where the conversion will occur in specific condition. An example is grassland will be
converted to estate area if estate area is more profitable.
Table 6. Land use conversion matrix for study area
Land Use Future
Water Grassland
Estate Settlement
Forest
P re
sent
Water 1
Grassland 1
1 1
1 Estate
1 1
1 1
Settlement 1
Forest 1
1 1
1 likely to conversion; 0 unlikely to conversion
This method is one of specific setting to determine temporal dynamic of land use simulation. Land use with high investment will not easily be converted to other
uses. Moreover, because of the differences of conversion behavior, dimensionless factor is added to each land use type. This factor represents elasticity conversion,
ranging from 0 easy conversion to 1 irreversible change. Water area and settlement area is an example of this rule, where the elasticity value for urban built
up area is set 1 that shows urban built up area is hard to be converted to another type of land use. Grassland and forest area are more easily to be converted and the
value is 0.4. Estate is set to more difficult to be converted, so the elasticity value is 0.6. The justification of the elasticity values of land uses in this study is based on
field observation and local knowledge and adjustment for the model. The range of values can be seen in following table.
Table 7. Settings of conversion elasticity in the study area
Land Use Type Conversion Elasticity
Water 1
Grassland 0.4
Estate 0.6
Settlement 1
Forest 0.4
Source: Observation and analysis, 2011
