analysis to obtain the best alternative land use.
Topographic map Soil Map
SlopeDistance Land Form map
Local Gov Policy Image aerial photo
Suitability for Tourism Suitability for paddy
Suitability for corn Land use
Planning map
Identify conflict Identify tourism
object
Existing Land use map
Socio economic data
Conflict map
Recommended Sustainable Tourism
Zone map
GIS RS
SMCA
Ground check
Analysis
Integrated
Classification Geometric
corrections
MCA
Formulation of policy Alternative map
Assessment criteria
Ranking : best …worst
Evaluation Suitability for
Sand dune formation Water resources
Potential map
The Best Alternative
Land use map
Figure 4.2 Research Steps.
4.2.1 Existing Land-use map
Identification of the existing land use of Parangtritis Village was done by visual interpretation of aerial photograph 2000 and quick bird imagery 2003. The area can be
classified in to tree main group, namely vegetation, non vegetation and open land. The vegetation can be divided in to dense and less dense, then the type of vegetation
identified through situation in wet or dry land. Non vegetation can be settlement, road, river. For acquiring better geometric imagery, the first step prior is to correct error of
geometric by using digital topographic map or ground control point . Georeferencing is a replacing pixel position as true condition. The process uses
28
ground control point GCPs, which are selected transform the geometry of the aerial photographimage, than each pixel corresponds to a position in a real world coordinate
system. Classification boundaries are determined by digitizing on screen using Arc
View. Aerial photographs and satellite images can be classified to identify settlement, forest cover, bare land etc to produce existing land-use map. Figure 4.3 shows the
diagram of land use mapping.
Figure 4.3 Land use mapping diagram. 4.2.2
Ground checking
Ground checking is used to compare between the object samples in the image with the real surface of earth, to ensure the accurate of interpretation result. During
this activity questionnaire were distributed to acquire additional information of the land used and tourist object, and collecting needed data from related institution. The
village monographic and land use planning are collected from Baparda and Bappeda Bantul. Aerial photographs and the previous researches are collected from Gadjah
Mada University.
29
4.2.3 Land Suitability Analysis
Land suitability assessment is concerned with ‘the process of estimating the potential of land for alternative kinds of land use’ Dent and Young, 1981. Land use
could be in the contexts of agriculture, engineering, forestry, or recreation; but agriculture may be the most popular area where land suitability assessment is applied.
In the agricultural context, the evaluation is directed to a specific kind of land utilization FAO, 1976, at specified units of homogeneous delineation.
Land suitability in the research area including land suitability for paddy field, corn and tourism area. The steps of geographic information system analysis are: 1
preparing metric of suitability for paddy field, dry culture and tourism 2 scoring and weighting 3 spatial analysis to obtain suitable area for paddy field, corn and tourism.
Land suitability matrix that is used for tourism is based on criteria developed by Bakosurtanal and matrix that is used for dry culture, paddy field, is based on criteria
developed by Puslitanak. Table 3.1, Table 3.2, and Table 3.3 show the matrices of criteria of land suitability.
Table 4.1 Matrix for suitability of land coastal tourism activities
Categorize and scoring Variable Wei
ghti ng
Highly suitable S1
Score Suitable S2 Score Marginally
Suitable S3 Score Not
suitable N
Score
Type of beach
8 Fine sand
9 Sand small
coral 7 Sand
coral Small steep
5 Mud, mangrove
Coral, very steep
3 water resources
potential 8
High 9 Medium
7 Low 5 Scarce 3
Land cover of beach
6 Coconut Open land
8 Brush small
grass savanna
6 High grass
4 Forest, mangrove
settlement 2
Distance from coastal line
6 500
8 500 - 1000
6 1000-1500
4 1500
2
Source: Bakosurtanal, modification 1996.
30
Table 4.2 Criteria land suitability for paddy field
Class Indicator
Highly suitable S1
Score Suitable S2
Score Marginally suitable S3
Score Not suitable
N Score
Temperature
24- 29 4
22 – 24 29 - 32
3 18
35 2
18 35
1
Water availability
33 - 90 4
30 - 33 3
2 1
Rot zone Drainage
Texture Coarse material
soil depth cm refined –
3 50
4 Medium
3 – 15 40 - 50
3 Coarse
35 25
2 Coarse
35 25
1
Substrate retention nr KTK cmol
Basalt saturated PH H2O
C-Organic 16
50 5,5–8,2
4 = 16
35 – 50 4,5– 5,5
8,2– 8,5 3
2 1
Toxicity xc Salinity dSm
2 4
2 - 4 3
6 2
6 1
Sodastic xn
Alkalinity ESP 20
4 20 - 30
3 40
2 40
1 Sulfides risk xs
Depth sulfides 100
4 75- 100
3 40
2 40
1
Erosion slope
erosion risk 3
Very low 4
3 – 5 low
3 8
High 2
8 High
1
Inundation risk 4
3 2
1
Land preparation Surface Stones
5 4
5 - 15 3
40 2
40 1
Source: Puslittanak Bogor 1994
Table 4.3 Criteria land suitability for corn.
Class Indicator
Highly suitable S1
Score Suitable S2 Score Marginally
suitable S3 Score Not
suitable N Score
Temperature
o
C 20 - 26
4 26 - 30
3 16 – 20
30 - 32 2 16
32 1
Water availability 500- 1200
4 1200-1600
400 - 500 3
1600 300 - 400
2 300
1
Root zone Drainage
Texture Coarse material
soil depth cm Refined
15 60
4 Medium
15 – 35 40 - 60
3 Medium-
roughs 35 – 55
25 - 40 2
Roughs 55
25 1
Substrate retention nr KTK cmol
Basalt saturate PH H2O
C-Organic 16
50 5,8 – 7,8
0,4 4
=16 35 – 50
7,8 – 8,2 = 0,4
3 35
5,5 8,2
2 1
Toxicity xc Salinity dSm
4 4
4 - 6 3
4 - 8 2
8 1
Sodastic xn
Alkalinity ESP 15
4 15- 20
3 20 - 25
2 25
1
Sulfides xs Depth sulfidik cm
100 4
75 - 100 3
40 - 75 2
40 1
Erosion Slope
erosion risk 8
Very low 4
8 – 16 low
3 16 – 30
medium 2
30 high
1
Inundation risk
F0 4 F0
3 F1 2
F2 1
Land preparation Surface Stone
5 4
5 - 15 3
15 - 40 2
40 1
Source: Puslittanak Bogor 1994
31
4.2.3.1 Weighting and scoring
Simple Additive Weighting SAW or Weighted Linear Combination WLC is the most often used technique in multi-criteria decision making Fisher, 1994.
Criteria here may include weighted and factors. Calculating the product of weight and factor at any location, and then summing up all products yields a total overall score.
The score for each alternative A is:
∑
× +
× =
n i
n n
i i
x w
x w
A .....
x
i
= criterion score of factor i, w
i
= weight of factor i,
Suitability area level showed by index overlay value. The class from S1 highly suitable, S2 suitable, S3 marginal suitable, N not suitable are the ranking of
suitable area classes. The suitability index score are 4 for S1, 3 for S3, 2 for S2 and 1 for N. Land has overlay index value from 4 , 3, 2, and 1, which is considered as
random combinations from suitability matrix variable on overlay process. The compiling overlay result into land to get suitability class. The equation used is as
follow:
n S
S
Si
min max
−
=
Where Si: Land suitability class range Smax: Highest overlay index value
Smin: lower overlay index value n: number of class
The example of suitability index calculation based on table 3.1 as follow:
Highest suitability index’s are: 8 x 9 + 8 x 9 + 6 x 8 + 6 x 8 = 240 Lower suitability index’s are: 8 x 3 + 8 x 3 + 6 x 2 + 6 x 2 = 72
32
Land suitability class range: 240 – 72 4 = 42 The suitability class of index X where 198 X
≤ 240 are Highly suitable 156 X
≤ 198 are Suitable 114 X
≤ 156 are Marginal suitable 72 X
≤ 114 are Not suitable 4.2.3.2
Areas of Conflict Geographic Information System GIS technology allows the matching of
recreation potential with the characteristics of the regions. The capability of a GIS on analysis land use planning here, by consideration of sustainable development concept.
Spatial analysis approach is more enhance for measuring wide, area and site selection that are suitable for particularly purpose.
The area conflicts were identified through land suitability analysis and existing land use, which is one area may be suitable for tourism, paddy field, or another
combination. It was identified also by matching of existing land use with land use planning, where often the conservation area uses for other activities that its opposites
each others.
4.2.4 Creating Maps of Alternative
