50
Figure 14 Rasterization processes in analyzing population pressure to the conservation areas
Figure 15 Spatial distributions pressure of population density to PCAs per village
4.2.2 Household Forests Activities
In order to characterize the pressure that might occur to conservation areas by household’s activities in gathering forests products, two layers raster datasets
Raster-1
Raster-2 Convert raster to features
Convert features to raster Convert features to raster
PCAs Raster cells values:
0.33333 0.66666
1.00000
RASTER SUM
Natural Break Reclasses 1 to 5
INTERSECT Village Boundary
Population Density Pressure to PCAs
PCAs- Population
Density Raster cells
values: 0.701439
1.032191 1.367737
1.593031 1.928577
Population Density Raster cells values:
0.368106 0.597687
0.664339 0.691494
1.000000
OUTPUT PROCESS
INPUT
51 were combined. First is the village characteristic in gathering forests products and
second is the distribution of priorities conservation areas that form zonation within each village area. Combination done by summed the given weight of each
raster layer using default weighted given is 1. This process would overlays both raster multiplying each by their given weight and summing them together and this
would produce new raster dataset as aggregation of population density values and priorities conservation areas values.
Household forests activity pressure to each zones of is presented in Table 32 and Figure 17 below, while the data processing is showing in figure 16. The
first raster is PCAs layer, consists of PCA-1, Non PCA-1 and Non PCA. Through normalization weight 0-1 then the PCA raster has normalized based on its
attributes. PCA-1 the raster values is 1.0000, Non PCA-1 raster values is 0.66666 and Non PCA raster values is 0.33333. This layer is the same layer that using in
population density analysis. The second raster is household forests activities, which is have cells values 0.555 very low, 0.638438 low, 0.709707 medium,
0.808789 high and 1.0000 very high. These values were generated through normalized the values of population
density of each village. The sum weighted processes done using ArcGIS tools by multiplying each other by their given weighted using default weighted given is
1. The cells values of weighted sum results of PCAs-Population density thence re-classes into five level, such as 1.040319
very low, 1.218359 low, 1.474564 medium, 1.709056 high and 2.0000 very high.
In raster processes, the first output is in floating data format. Required next step is by reclassify the number of classes thence saved it as integer data format.
Method of re-classified is using natural break method called also Jenks. Number of re-classes using here is five classes same as scoring basis that used in
characterization of social economic values as stated in methodology of this research. New raster that produced as output of weighted processes thence
converted into vector format for vectorization processes such as calculating distribution areas per PCA of each village.
52
Figure 16 Rasterization processes in analyzing the household forests activities pressure to the conservation areas
Figure 17 Spatial distributions the pressure of household forests activities to PCAs per village Table 32 Household forests activities score scored in each village per zone
Convert raster to features HH Forests
Activities Raster cells values:
0.555 0.638438
0.709707 0.808789
1.000000
Convert features to raster Convert features to raster
RASTER SUM
New Raster-Reclasses INTERSECT
Village Boundary HH Forests Activities
Pressure to PCAs PCAs-HH
Forests Activities
Raster values: 1.040319
1.218359 1.474564
1.709056 2.000000
OUTPUT PROCESS
INPUT Raster-1
PCAs raster cells values:
0.33333 0.66666
1.00000
Raster-2
53
PCAVillage Bauro Com Lore I Tutuala Mehara Muapitine
PCA1 -
- 5
5 5
4 Non PCA1
5 2
5 5
4 3
Non PCAs 4
1 4
4 3
2
Notes: 1: very low, 2: low, 3: medium, 4: high and 5: very high
4.2.3 Traditional Land Claim
