Suitability Analysis for Seaweed Farming in Tarakan, Indonesia

Suitability Analysis for Seaweed Farming in Tarakan, Indonesia


Gatot H. Pramono

Ratna Sari Dewi


Mone Iye C.
Bakosurtanal (National Coordinating Agency for Surveys and Mapping)
Jl. Raya Jakarta – Bogor KM. 46 – Cibinong 16911 Indonesia
Phone/Fax: +62-21-875-7636
[email protected]

Seaweed farming becomes one of the coastal and marine prospects for improving the national economy. Identification coastal areas suitable for this aqua culture is highly needed. This paper explains the process of performing suitability analysis in Tarakan, east Kalimantan, Indonesia. The analysis is based on the physical properties of coastal water which was directly surveyed such as water depth, dissolved oxygen, salinity, temperature, clarity and pH.

The Geographic Information System (GIS) is used to do the analysis. The comparison of matching and scoring approaches shows relatively similar results. However, scoring method predicts wider areas which are suitable for weed farming.

1. Introduction
In this section, the background and objective of the study are explained. The description of Tarakan in East Kalimantan, Indonesia as the study area is also given.

1.1. Background
Indonesia is the biggest archipelago in the world with more than 17,500 islands. The length of coastline is more than 81,000 km. The area of Indonesian ocean is about 3.1 million km2 (Dahuri et al., 1996). Indonesian ocean holds significant economic values. Indonesia is one of ten countries in the world with the highest fishery productions. The coastal side is also a productive area such as coral reefs, sea grasses, estuaries and mangroves.

One important commodity that can be farmed is seaweed. Seaweeds are algae that liven in the sea or in brackish water (Guiry, 2007). It is also known as “benthic marine algae”, which means algae that live in the sea bottom. It is found in the seashore biome. Two specific environmental conditions for the growth of seaweed are the presence of sea-water and light sufficient for photosynthesis (Wikipedia, 2007). Seaweeds are extensively used as food for coastal people. The extraction of seaweeds can be in form of agar (for confectionery and desserts) and carrageenan (for salad dressings and sauces). In the pharmaceutical industries, alginates (extracted from seaweeds) are used in wound dressings and dental moulds. In microbiology research, agar is extensively used as culture medium.

Referring to wide variety of seaweed uses, the farming of seaweeds is an important aspect for economic benefits. The extract of seaweeds can be used for domestic and international needs. Because the seaweed growth depends largely on the specific environment, the triggering question is where are the most suitable coastal areas for seaweed farming? The answer to this question will be very useful for local government and investors to do the aqua culture.

1.2. Objective
The main objective of this study is to identify the most suitable coastal areas for seaweed farming. The suitability maps will be the main result of this study. The area and distribution of suitable areas will be assessed.

1.3. Study Area
The area for this study is in Tarakan island, east Kalimantan province, Indonesia (Figure 1). The reasons of choosing this location are the needs to enhance the aqua culture and the data availability from Marine and Coastal Resources Management Project (MCRMP)

Tarakan island is located between 3°14.5′-3°25.0′ North and 117°31.8”-117°38.0” East. The land area is 251 km2 and ocean area is 407 km2. It is divided into four districts: East, Center, West and North Tarakan. The topography is between 0 and 110 meter from the mean sea level. The area is mostly forest including mangrove (more than 14,000 hectares). The climate in this area is classified as wet tropical climate or tropical rain forest climate with annual precipitation of 287 mm and average temperature of 27.3°C.

The total population of this island was 155,208 people in 2004 with annual population growth rate of 3.5% (Bappeda and BPS Tarakan, 2004). The population density is about 614 people/km2. Most people work in the agricultural, trading and transportation sectors.

From the coastal and marine resources, the fishing production is 8,020 tons/year: 5,000 tons from ocean, 3,000 tons from coastal ponds and 30 tons from inland farming. The total number of fishermen is 1,977 people in 2004. The aqua culture production is not yet recorded although some efforts have been carried out.

2. Methodology
The approach to carry out this research is divided into three stages: data collection, suitability analysis and data processing. The explanation of each step is as follows.

2.1. Data Collection
The spatial data used for this work are topographic maps in 1:50,000 scale from Bakosurtanal and coastal and marine data from Marine and Coastal Resources Management Project (MCRMP).

The field survey was carried out from May 29 to June 5, 2005. The purpose is to obtain the physical properties of coastal areas such as sea temperature, depth, pH, salinity, dissolved oxygen, turbidity and conductivity. Fifty observation points was acquired by four surveyors and two people from local government. The survey devices are digital water checker, dissolved oxygen meter, secchi disk and global positioning system (GPS). For each observation point, the measurement was conducted and the coordinate position was recorded. Table 1 shows the range of seven parameters acquired from the field survey. These values will be used for perform suitability analysis.

2.2. Suitability Analysis
Wiradisastra (2004) mentioned the parameters used for suitability of aqua culture for Kerapu fish, seaweed, coral reefs and pearls. Table 2 shows six parameters considered for seaweed farming: depth, dissolved oxygen, salinity, temperature and pH. There are four levels of suitability:

  1. Highly suitable (S1)
  2. Suitable (S2)
  3. Conditionally suitable (S3)
  4. Not suitable (N)

The range of suitability is mentioned in Table 2. For example, the highly suitable area is characterized with the flow depth 1-5m, dissolved oxygen more than 6 mg/l, salinity of 28-36 ppm and so on.

Each parameter has different significance in deciding the most suitable area. The weight is applied differently for each parameter and written near parameter name in Table 2. The most influencing parameter is flow depth with the weight of 35. The total weight of all parameters are 100. In first row of Table 2, the value near the suitability level is the value limit of suitability. For example, the minimum value of 80 is needed to achieve level S1 (highly suitable).

The above parameters can be calculated using two available methods: matching and scoring. Matching approach considers the minimum suitability level of a parameter as the final suitability. For example, if one of the parameter results in N (not suitable) class, the final suitability will be N, although other parameters gives S1 (highly suitable). According to Wiradisastra, etc (2004), matching method is safer in determining the suitability, but lack of the assumption that each parameter has specific effect on the growth of the seaweed.

The second approach is scoring. This method considers the weight and limit of analysis as mentioned in Table 2. This method could result in higher suitability level than the result of matching approach. Both methods will be applied in this research to observe the similarity and discrepancy.

2.3. Data Processing
The data is processed using geographic information system (GIS). GIS is capable of performing multicriteria analysis by modeling parameters as separate layers. There are three main steps in data processing:

  1. Data preparation: The data is prepared to be able to be used for overlay operation. Since the data was collected as observation points, it has to be converted in polygon format. First, the values in points are interpolated using inverse distance weighted (IDW) method. IDW approach is appropriate for this study because it results in realistic values (Pramono, 2004). Next, the resulted grid is classified into suitability levels (S1, S2, S3 or N) which later is converted to vector in polygon format. This process is performed on all surveyed data.
  2. Overlay: All layers are then overlayed. Since this process can be executed between two layers, the overlay is carried out five times. The result is polygons with suitability from all parameters.
  3. Matching and scoring: The suitable areas are determined using matching and scoring method. A script is written to automate the computation using both methods. Polygons with the same suitability level is then dissolved to obtain the final result.

3. Results
The maps of seaweed suitability using matching and scoring methods are shown in Figure 2 and 3. The distribution of suitable areas are relatively similar when applying both methods. Most of marine areas are not suitable (N) for seaweed farming. The suitable areas are found around Sekatak gulf in the south of Tarakan island. In this area, matching method predicts conditionally suitable (S3) while scoring method gives suitable (S2). Another discrepancy is found in the east coast of Tarakan which is conditionally suitable (S3) based on the scoring method.