22
KSBTU Seksi Konservasi
Wilayah 1 Seksi Konservasi
Wilayah 2 Seksi Konservasi
Wilayah 3 Penyaji Evaluasi
Pelaporan
Penata Kerjasama
Hub. Masyarakat Penata Usaha
Umum Penata Usaha
Perlengkapan Rumah Tangga
Fungsional
Penata Usaha Keuangan
Penata Usaha Kepegawaian
Penelaah Penyusun Data
Perencanaan Penata Bina
Cinta Alam dan Kader Konservasi
Penata Bina Konservasi dan
Perlindungan Penata Promosi,
Informasi, Hub. Masyarakat
Penata Usaha Kepegawaian,
Perlengkapan Rumah Tangga
Penata Rencana Program
Pelaporan Penata Usaha
Umum Keuangan
Penata Bina Wisata Alam dan
Kader Konservasi Penata Bina
Konservasi dan Perlindungan
Kepala TNGHS
Manajer Stasiun Penelitian dan
Perkemahan
Kepala Resort
Figure 4. Organization Structure of GHSNP Based on the Decree of MoF No. 355Menhut-II2004
4.1.1.4. System Requirement Definition
Based on the need and information analysis, the intended system could be simply described into three parts, namely input, process, and output. It is
illustrated by Figure 5.
Figure 5. Conceptual System There are two sources of system input which are input that came from the
user and from storage. The input from user commonly has a purpose to choose an
• Spatial data of species distribution
• Habitat factors of concerned species
• Conservation area boundary
• Habitat suitability map with chart
• Spatial data of species distribution
• Geoprocessed data • Geometric Operation
geoprocessing • Decision Rules
• Classification and summarization
Storage
INPUT PROCESS
OUTPUT
23 available option. The input that from storage is used for further processed. In
determining habitat suitability, some factors that usually considered are species distribution, habitat factors of concerned species e.g.: land cover, slope, rivers,
etc., and the predicted region or area such as protected area. The system can be viewed as matrix of resources, products and activities. It
also highlights how the basic system activities of input, processing, output, storage, and control are accomplished, and how the use of people, hardware, and
software resources to support system activities. Such matrix is called system component matrix is given in the table below.
Table 2. System Component Matrix
Hardware Software Brainware Dataware
Input
- ArcView optional
Technician Vector data format
polygon, line, point, including presence data,
habitat factors, and surface flat polygon
Processing
Minimal CPU 512MB RAM,
64MB VGA. PCA Module, Score
function, basic geo- processing function,
species distribution mapping module
Technician -
Output
Computer Display
MapViewer, Chart Technician,
Manager Suitability Information
Dataset
Storage
Disk Drive -
Technician -
Control
- - Manager -
It is important to determine representation type of data which involves directly into habitat suitability model process i.e.: ecogeographic variables data.
The very well-known spatial data representation is raster tessellation and vector type. One of them has their own primacy over the other, so that the utilization
sometimes different depend on the analysis purpose. Another type of data model is vector-based grid. It is actually a vector data but utilized like a grid data.
This data type is also known as cell-based or vector grid but actually refers to the same thing. The vector-based grid is chosen to represent ecogeographic variable
based on the reasons below: 1
Habitat suitability is formulated using ecogeographic variables. Ecogeographic variable is a spatial property of a unit of area based on the
arrangement of corresponding spatial features that representing habitat factors. It specifies habitat factor into more quantitative representation. It describes
24 the characteristic of certain area based on related habitat factors. These spatial
characteristics are assumed motivates wildlife to behave appropriately in certain land. The arrangement of habitat factor gives indication to the quality
of habitat Morrison et al., 1992. It encourages the species to exploit or stay in certain area. The examples of possible spatial properties and the
corresponded spatial features are given by Table 3 and illustrated by Figure 6. Table 3. Spatial Features and Spatial Properties Relationship
Spatial Features Feature Types Spatial
Properties
Forest type Polygon
The frecuency, area, density of forest, etc. Forest ecosystem
Polygon The frecuency, area, density of forest, etc.
Soil type Polygon
The frecuency of soil type Settlement
Polygon Distance to settlement
Temperature Polygon
The average of temperature Nutrient Polygon
Rate, amount,
etc. River water body
Line Polygon Distance to river, water quality parameter, etc.
Road Line
Distance to road Competitor Predator
Point Number of competitor predator
Mutualist Species Point
Number and or pattern of distribution
Figure 6. Illustration of Spatial Properties Ecogeographical Variable that Influencing Wildlife Response. Each Grid has Its Own
Spatial Characteristic, such like Proximity Distance to Road [represented by black line], River [represented by blue line]
and Content Arrangement the Area of Landcover Contained In, Marked by x and y Letter
x y
25 2
Habitat suitability is estimated by using decision rules method, which its criteria are ecogeographical variables. It is well-known method applied for
raster data type. The spatial operation of vector-based grid is similar to binary raster data type.
3 It is possible to make a compact structure of environment representation
spatial database by using vector-based grid, since this format is built under ESRI Shapefile format. ESRI Shapefile format is used database to maintain
manage the attributes of spatial data spatial properties. System processes are determined based on data input characteristic,
intended output and chosen modeling method. Generally, there are three functionalities required in the system, as illustrated in the Figure 7, namely data
preparation, habitat suitability model and output visualization. Data preparation sub-system has three objectives:
1 It is used to prepare the predicted land in vector-based grid format rasterizing
process. Predicted area is divided into parcels grid, which each parcel size is determined by the user. This process needs a flat surface in polygon format.
2 It is used to generate ecogeographical variable data and embed it as spatial
properties of observed or predicted area. 3
Species distribution data is available in text or tabular format, instead of spatial format. This data is important to determine the weight of the model.
The system supports the creation of species distribution data in spatial format point feature.
For these reasons, several processes that needed in data preparation modules are geoprocessing including dissolving, point buffering, and rasterizing, species
distribution mapping, and data extraction on ecogeographical variable. Habitat suitability model follows one of decision rules method that is Simple
Additive Weighting SAW. It is chosen consider to its simplicity in processing
procedure overlay. The weight of the model is determined by applying Principal Component Analysis
PCA to species distribution data. The spatial properties in the area of which the existence of species is observed, are used as a
cue to determine what eco-geographical variables is important to be considered.
26 The weight is defined as the maximum loading factor of the variable to the
corresponded principal component, which is still interpretable. The last functionality is classification map rendering and summarization.
They are a set of processing used in displaying the result of habitat suitability processing. The method of classification used is linear and incremental division.
The summarization process is a process to summarize the suitability model result into descriptive information text-based and pie chart format.
The functionalities of SUITSTAT are illustrated by the figure below.
Figure 7. Major Functionalities of the SUITSTAT
4.1.2. System Analysis and Design
