Analysis of distance from road and entrance in affecting single tree felling of illegal logging
Analysis of distance from road and entrance in affecting single tree felling of illegal logging
using remote sensing and GIS (A case study in Labanan Concession, East Kalimantan, Indonesia)
ANITA ZAITUNAH
Jurusan Kehutanan Fakultas Pertanian Universitas Sumatera Utara
Abstract
There is a decreasing of forest area and the quality itself worldwide especially in developing and tropical countries. Illegal logging is one of the factors considered in causing this condition. Illegal logging in this research is in a form of single tree felling. This research tried to investigate the physical factors affecting single tree felling of illegal logging using optical remotely sensed data and GIS.
Two sets of Landsat-7 ETM+ data acquired on 16 August 2002 and 31 May 2003 were used in this research. Subpixel Classifier was applied to obtain the classified map showing newly logged points, which is illegal logging spots.
Some physical factors were decided to be analysed to find out their relationship with illegal logging. Two of the factors are distance from roads and entrance. Maps were built representing classes on those factors. Those maps were individually crossed with illegal logging maps of year 2002 and 2003. The relationship between each factor and percentage of illegal logging was analysed using Spearman’s correlation.
The result of overlay between each factors and illegal logging maps shows their relationship in both years. More illegal logging found in the closer distance from roads and closer distance from entrance.
It is concluded that there is a relationship between distance from road and distance from entrance with illegal logging.
By having an increasing and devastating number of illegal logging area, monitoring of newly logged points should be done in a short period of time continuously.
Abbreviations and Acronyms
AAI ACM BFMP DEM FAO FCD FSC GIS
Applied Analysis Inc. Adaptive Collaborative Management Berau Forest Management Project Digital Elevation Model Food and Agriculture Organization Forest Canopy Density Forest Stewardship Council Geographic Information System
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GPS Ha HPHH ILWIS IPK IPPK timber) ITTO IUCN LEI MOI NGO RKL SFM TM TPTI
UNEP
Global Positioning System Hectare Hak Pemungutan Hasil Hutan (License to collect forest products) Integrated Land and Water Information System Izin Pemanfaatan Kayu (License to extract and use timber) Izin Pemungutan dan Pemanfaatan Kayu (License to collect and use
International Tropical Timber Organization international union for conservation of nature and natural resources Lembaga Ekolabel Indonesia (Indonesian Ecolabelling Institute) Material of Interest Non Governmental Organization Rencana Karya Lima Tahun (Five year working plan) Sustainable Forest Management Thematic Mapper Tebang Pilih Tanam Indonesia (selective cutting and planting)
United Nation Environmental Programme
1.1. Background
INTRODUCTION
Forest is a valuable natural resource that should be maintained sustainably. It has many functions to support human’s life. Wood as a result of logging activities is one of its important products. These activities have built the relationship between producer, consumer and the products. Forest functions will be maintained as long as the forest is managed in sustainable ways.
In fact, there is a decreasing of forest area and the quality itself worldwide especially in developing and tropical countries. Of the 15.2 million ha of natural forest lost annually in the tropics, 14.2 million ha were converted to other land uses and 1.0 million ha were converted to forest plantations (FAO, 2001).
Illegal logging is one of the factors considered causing deforestation (Selamat, Mohamed, & Hussin, 2000). It is a logging neglecting the sustainability aspect due to illegal activities. This process will definitely contribute to the rate of deforestation.
The alarming rate of deforestation has brought about people’s awareness to have a better forest management. International Tropical Timber Organization (ITTO) has formulated the definition of sustainable forest management (SFM) as “the process of managing permanent forest land to achieve one or more clearly specified objectives of management with regard to the production of a continuous flow of desired forest products and services without undue reduction of its inherent values and future productivity and without undue undesirable effects on the physical and social environment” (ITTO, 1992).
1.2. Problem Statement
During the 1990s, the loss of natural forests was 16.1 million hectares per year, of which 15.2 million occurred in the tropics. These are corresponding to annual losses of 0.4 percent globally and 0.8 percent in the tropics. There are major causes for the loss mentioned by FAO: conversion to other land uses (mainly agriculture), pests and
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diseases, fire, overexploitation of forest products (industrial wood, fuel wood), poor harvesting practices, overgrazing, air pollution and storms (FAO, 2001).
The deforestation rate of Indonesia between 1985 and 1997 was around 1.8 million hectares/year. Between 1985 and 1998, the ratio of forest area to total land area fell from 62.7 percent to 50.6 percent (FAO, 2000). Furthermore, FAO mentioned that dry lowlands as the most valuable for commercial logging and biodiversity conservation have the most forest cover loss.
Deforestation and forest degradation are mostly caused by illegal activities. These include over-cutting of forests and cutting in unauthorised areas. In Indonesia, there is a smuggling of illegal logs to neighbouring countries. Widespread of illegal logging networks operate at the district level. About 40-60% of the total industrial round wood supply has been estimated come from illegal logging (FAO, 2000).
Figure 1.1. Single tree felling by illegal loggers. Tree was sawn in the spot using chain saw and transported outside the area
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Literature study on forest certification, illegal logging, remote sensing & GIS
Define the research objectives and research question
Study area selection
Training & test data
Image preparation Field data collection
Map layers compilation FCD mapping
Illegal logging maps
Data processing and analysis
Extraction information on factors affecting illegal logging, logging
intensity and forest canopy density
Conclusions
Figure 1.2. Research Approach
In this research, illegal logging is defined as illegal felling of a single tree. It is not in a form of clear cutting or cutting many trees or cluster of trees. The loggers would go inside the forest looking for trees to be cut. They select a big enough and commercial tree and then cut it. The selected tree would then sawn in the spot and transport outside. Illegal logging spots can be seen as in Figure 1.1.
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A serious attention should be given to combat illegal logging. We need to know what is happening in the forest. The knowledge on what do people take into account before they select a tree, cut and sawn the timber in the spot illegally would help combating illegal logging.
1.3. Research Objectives
The objective of this research is to investigate distance from road and distance from entrance in affecting illegal logging in a form of single tree felling using optical remotely sensed data and GIS.
1.4. Hypothesis
Distance from road and distance from entrance affecting illegal logging in a form of single tree felling could be identified using optical remotely sensed data and GIS.
1.5. Research Questions
In order to achieve the objectives of this research, the following questions need to be answered:
1. Are there relationship between distance from road and distance from entrance and illegal logging in a form of single tree felling?
2. How are those factors affecting the illegal logging of single tree felling?
1.6. Research approach
In order to achieve the objectives of this research, the research approach has been conducted as a guideline. The research approach is shown in Figure 1.2.
2. LITERATURE REVIEW
2.1. Definition and scope of illegal logging
Smith (2002) mentioned that illegal logging term refers to timber harvesting-related activities inconsistent with national (or sub-national) laws. The scope of those activities can be the entire industry from wood harvesting until product reaching the market.
The following are different types which considered as illegal logging (Brack & Hayman, 2001):
Logging in violating contractual obligations Obtaining concessions illegally, for example, corrupt means Logging nationally-protected species without explicit permission Logging outside concession boundaries Logging in forbidden or protected areas Removing under or over-sized trees Laundering illegal timber through a concession Use of old log permits or licences to collect illegally felled timber
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2.2. Illegal logging in Indonesia
Illegal logging and other forest crimes have expanded into protected areas of Indonesia. There are more pressure on endangered and endemic species of flora and fauna. A number of high profile species now face a real and ever-present threat of extinction (Wardojo et al., 2001).
Larsen (2002) has mentioned that Indonesia‘s domestic wood supply of 2002 was 20 million cubic meters, while the demand stood at some 60 million cubic meters. This gap was filled by illegal logging and destroy ten million hectares of Indonesia’s forest.
The council had identified the causes and contributory factors to illegal logging (ITTO, 2001). The failure of forest laws, insufficient of management and control in timber production, availability of markets for illegal logs, low risk and high profitability of illegal logging, lack of inter-sector coordination are among factors mentioned by the Council.
Casson & Obidzinski (2002) mentioned a number of factors attributed to the recent boom in illegal logging including changes arising from “reformasi” – a calling for democracy, reform and change – and the new decentralization laws. Central government give the authority to local government to manage their natural resources. Governors and Regents have the authority to issue permits for small forest concessions. Governors were allowed to grant concessions of up to 10,000 ha, and Regents were allowed to grant concessions up to 100 ha.
2.3. Remote Sensing and GIS
Remote sensing is the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation (Lillesand & Kiefer, 1994). Information is derived from the image data, which form a (limited) representation of the real world (Janssen & Huurneman, 2001).
Remote sensing relies on the measurement of electromagnetic energy. Electromagnetic energy can take several forms. Many sensors used in remote sensing measure reflected sunlight. Some sensors, however, detect energy emitted by the Earth itself or provide their own energy (Janssen & Huurneman, 2001).
GIS stands for geographic information system. It is a computerized system that helps in maintaining data on geographic space. In the wider sense, a GIS consists of software, data, people, and an organization in which it functions. A GIS always consists of modules for input, storage, analysis, display and output of spatial data (de By, 2001).
The following are three stages of working with geographic data mentioned by de By (2001):
data preparation and entry; the early stage in which data is collected and prepared to be entered into the system
data analysis; the middle stage in which collected data is carefully reviewed data presentation; the final stage in which the results or earlier analysis are
presented in an appropriate way.
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3. STUDY AREA
The selected study area is located in Berau District. The selection of the study area is important in order to achieve the research objectives and answer research questions. It was based on its condition related to illegal logging activities.
3.1. Location
Labanan forest concession is located in Berau District, East Kalimantan Province, Indonesia. The location is between latitude of 1o49’ N and 2o10’ N and longitude of 116o57’ E and 117o27’ E. It covers an area of 83,240 ha. According to regional land use plan, Labanan area is allocated into three land use types. There are 54,567 ha of Fixed Production Forest, 26,997 ha of Limited Production Forest and 1,676 ha of Non Production Forest. The location of the study area is shown in Figure 3.1.
Figure 3.1. Labanan Forest Concession (BFMP, 2001)
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3.2. Forest Management System
The forest concession was managed by a state owned company, called PT. Inhutani I. It was established in 1974 and has applied selective logging since 1976.
Adaptive Collaborative Management (ACM) was established to have participation from stakeholders in this area. On 4 February 2003, PT Inhutani I and Regional Government of Berau have an agreement on operational cooperation for managing Labanan forest by establishing a share company called PT Hutansanggam Labanan Lestari (BUMNOnline, 2003).
The forest management unit has been divided into seven five-year working plan areas (known as RKL :Rencana Karya Lima tahun) (Table 3.1). The five-year working plan areas are shown in Figure 3.2.
The silvicultural system applied in the study area is called selective cutting and planting (TPTI). According to the national guidelines, an average of 8 trees per hectare are felled at 35-year interval. This management unit is going to enter a second felling cycle by the year 2011.
Figure 3.2. Five-year working Plan area (RKL)
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3.3. Climate and forest type
The study area has a typical tropical climate. The annual rainfall is about 2000 mm and every month receives more than 100 mm rainfall in most years (Cui, 2003).
The forest type of the study area is called lowland mixed dipterocarp forest due to the dominance of the dipterocarpaceae family. The most common genera within this family are Shorea, Dipterocarpus, and Vatica. While common species are Shorea parvifolia, Dipterocarpus acutangulus, Shorea pinanga and Shorea hopeifolia (Dahal, 2002).
3.4. The landscape
The Labanan area consists of undulating to rolling plain with isolated masses of high hills and mountains. It is located in inland of coastal swamps. The elevation of the study area ranges from about 12.5 to 437.5 m above sea level. According to Mantel (1998) mentioned in Bhandari (2003), the Labanan landscapes can be categorized as follows:
- Flat land: the floodplains adjacent to the river Siduung, Kelai and Segah - Sloping land: the dominant landscape of the area, undulating to rolling plain with
hillocks - Steep land: the medium to high gradient hills - Complex landforms: the limestone associated landscapes consisting of
undulating plains with rock outcrops
3.5. Socio-economical condition
There are fifteen villages and settlement including 3 transmigration settlement units surrounding Labanan area. There are 2 transmigration settlement units inside the area. The location of villages can be seen in Figure 3.3.
There are two types of community in the area; the first is a community originated from Java, brought by the government around 10 years ago through transmigration program. They mainly practice permanent lowland agriculture as they did previously in Java. The second is a Dayak Community. They live in some relatively new villages. They practice shifting cultivation and collect non-timber forest product. Not so many of them work as an employee of forest management company or government (Novarina, 2003).
3.6. Accessibility
Labanan area has a very good accessibility. There are main roads passing through the area connecting Tanjung Redeb to Samarinda (the capital city of East Kalimatan Province) and from Tanjung Redeb to some villages in Labanan.
The base camp of Labanan Concession can be reached through Segah River from Tanjung Redeb in approximately 20 minutes upstream by speedboat or by car through a paved provincial road for about 30 km and another 7 km through a logging road. Part of the road between Labanan and Tanjung Redeb is a segment of a main road in the region, which called trans-Kalimantan (Novarina, 2003).
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Figure 3.3. Location of villages in and surrounding Labanan Forest Concession (Novarina, 2003)
4. Methods and Materials
The research methods are divided into 3 stages. The stages are Pre-fieldwork, Fieldwork and Post-fieldwork.
4.1. Pre-Fieldwork Stage
The basic step of this research is literature review. The literature is related to the objective of this research and steps to come to the answers of the research questions. The literature study covers the following subjects:
Forest certification worldwide and in Indonesia Illegal logging activities and impact Remote sensing and GIS
For the fieldwork purposes, the images were prepared. The images were georeferenced. It was printed as hard copies for ground truth, field observation and comparison purposes.
4.2. Fieldwork Stage
The fieldwork was conducted in September 2003 in Labanan Concession, East Kalimantan, Indonesia. A consultation session was arranged before going to the field with the Head of Planning & Inventory of PT. Inhutani I. This session helped in identifying areas in the concession where illegal logging of single trees is taking place.
The following areas had been identified: RKL 1, RKL 4, RKL 5 and protection area. Because RKL 1 has the highest number of single tree felling of illegal logging, the test site for classification is reduced to RKL one.
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Collection of field data
The freshly logged points were purposively found by tracking the freshly used trails by illegal loggers on either side of the road. All points encountered in the forest that seemed to have been logged within one year were recorded.
Coordinates of permanent points such as road junctions were also collected to improve the georeference of the image. These variables were entered in a tally sheet, which was prepared before going into the field.
4.3. Post-Fieldwork Stage
The fieldwork has given the knowledge on what is going on in the spot related to illegal logging. Illegal logging in this research is in a form of single tree felling. Tree was sawn in the spot and transported outside. Spots were found along the main and secondary roads.
Based on the field investigation, information and related references, some factors had been taken into account to be analysed in their relation with illegal logging. Those factors are distance from roads and distance from entrance.
4.3.1. Preparation of factor maps
Figure 4.1 shows the steps on preparation and construction of factor maps. Data needed for these maps were constructed using ILWIS:
Distance maps: road, river, entrance
4.3.2. Construction of factor maps
Classes were determined for each factor. Each class represented the range of values within input map. Each input maps were classified according to their ranges. Those maps were created using ILWIS. At first, domain of each input was created. The domain contains the classes and range of values for the input map. The range of classes was defined with equal interval.
The following are the input maps which were being further classified:
Distance from road There are roads passing through the test site. Findings in the field have shown that illegal logging spots found along the road. The distance from road was divided into 200 m interval. There are 11 classes in 200 m interval. Those classes are 1-200 m (Class 1), 201-400 (Class 2), 401-600 (Class 3), 601-800 (Class 4), 801-1000 (Class 5), and so on until beyond 2000 m (Class 11).
Distance from entrance The entrance to the study area was considered to be important as the entrance for many people, including transmigrant and people from outside of the area. This entrance also leads to the market outside the area. The main entrance was digitised and being rasterized. Using distance calculation from entrance and consider the distance from road, the distance map of entrance was obtained. This map was classified into 1 km interval. The furthest distance from entrance is 26 km. So, there are 26 classes: 1, 2, 3, and so on until 26.
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4.3.3. Analysis of physical factors
Each factor was identified in 2 sources of information: illegal logging map of 2002 and illegal logging map of 2003. Both maps are the result of Subpixel classifier
Each input map was crossed with each illegal logging map. This step gave the evidence which factors have relationship with illegal logging.
4.4. Materials
The research considered certain types of data and information related to the study area. Landsat-7 ETM+ of 31 May 2003 was the input of FCD Mapper. The two maps of illegal logging were the result of subpixel classification of Landsat-7 ETM images; acquired date of 16 August 2002 and 31 May 2003.
Maps were needed to construct input maps: contour, RKL, boundary, river, road and entrance. Data and information related to the study area were also needed. These data came from the forest company and related institutions.
Hardware and software used in this research include computer, ILWIS, FCD Mapper, ERDAS, Microsoft, SPSS, Adobe Photoshop and internet. During fieldwork, global positioning system (GPS) receiver, camera, compass, measuring tapes used to collect field data.
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5. RESULTS AND DISCUSSIONS
This chapter describes the results obtained through data processing following the methods of the research. It will be used to answer the research questions.
2.4 Field knowledge on illegal logging activities
In year 2002, Bhandari (2003) found that the distance of 1 km from road as an effective range of logging. It can be considered logical because if the felling operation takes place far from the road, the operation becomes more expensive. From the field knowledge, he mentioned that nobody enters very deep in the forest to log a tree because all logging are mainly for commercial purpose. Distance factor can be used to refine the information derived from remotely sensed data.
Figure 5.1. Truck loading sawn wood from single tree felling (Bhandari, 2003)
As the time goes by, people become more and more seeing the potential of having income from cutting trees illegally in the form of single tree felling. Based on the fieldwork conducted in year 2003, people can go further than 1 km from the main roads. They use the secondary road that was a logging road and skidding trails of the company in the last felling scheme (period of 1976-1980). They bring the sawn timber to the location where the truck was ready to transport to further destination (Figure 5.1.).
The loggers consist group of people of 6 to 7. They select and cut a single commercial tree and sawn it on the spot. The sawn timber would be brought outside manually and put by the people near the main road. Later, a truck was ready to transport the timber to their destination. So, they will select the trees from a reasonable distance, which should not be far from the main roads.
There was also an important finding inside the area. The illegal loggers would
establish small base camps for their activities and operation inside the forest. By
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Figure 5.2. Base camps found in some location inside the study area
having the place to stay, they can go further inside and store the sawn timber in those camps (Figure 5.2.). Later, they can transport the sawn timber to the main road.
The old logging roads inside the area were established by the company in the logging year of 1976-1980. The length of the road was 2-4 km from main roads to inside the forest. There was no illegal logging found beyond 4 km due to the accessibility. During the fieldwork, the farthest distance where illegal logging spots found was 1.5 km from the main roads. The spots had been revisited by the company and found the farthest distance range of 1-2 km1. In RKL 1, about 60% of the area is within 2 km distance from roads. The condition of the road is not the same in whole area. Some roads are still accessible for the truck to come inside for a short distance. Others are difficult to be accessed by truck due to bad condition and steep slope.
By having the field knowledge and information, the result of the image classification of 2003 was refined with the distance factor. The distance considered as an effective range for the loggers was 2 km from the main road.
5.3. Relationship between physical factors and illegal logging
In order to see the relationship between physical factors and illegal logging, overlay operation was conducted between each factor map and illegal logging map of 2002 and 2003. It was decided to consider the percentage of illegal logging by dividing illegal logging area found in each class with the total area of illegal logging of whole study area.
5.3.1. Distance from road
Distance from road was calculated using distance calculation in ILWIS. This map was further classified into 200 m interval (Figure 5.3). The main road is passing through
1 Personal communication with Ir. Doddy H. W., Inhutani I Labanan
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the study area. This road is a provincial road connected Tanjung Redeb (District capital of Berau) and Samarinda (capital city of East Kalimantan).
Figure 5.3. Distance from road classes
It is clear that illegal logging in this area found mostly in close distance from roads. The trend is the same in 2002 and 2003 (Figure 5.4). In year 2002, 61% of illegal logging area are within 200 m from roads while in year 2003 67% are within 1 km distance. The illegal logging found in 2003 are reaching beyond the range of distance in 2002.
Comparison of illegal logging percentage within distance from road classes (2002,2003)
Illegal logging area (%)
60
40
20 0
1 23 45 67 8
Year 2002 61 20
8
6
5
0
0
0
Year 2003 17 18 13 10
9
8
7
7
Distance from road classes
9 10
00 65
Figure 5.4. Illegal logging area within distance from road classes
(Class 1:1-200, Class 2:201-400, Class 3:401-600, Class 4:601-800, Class 5:801-1000, Class 6:1001-1200, Class 7: 1201-1400, Class 8:1401-1600, Class 9:1601-1800, Class 10:1801-2000)
There was an increasing area being logged in all classes in ha. In terms of
percentage, there was decreasing number of illegal logging in lower classes (200-400
m) and increasing number of illegal logging percentage in classes 3-5 (600-2000 m).
It means more logging in the closer and further distance from the roads.
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In both years, the correlation between percentage of illegal logging area and the distance from road is found very high (rs=-1 (year 2002), rs=-0.988 (year 2003), 0.01 level, 2-tailed). The closer to the road, the more Illegal logging found. It is in accordance with what was found in the field. Good accessibility is the most important factor affecting illegal logging in terms of transporting the illegal sawn timber of single tree felling.
5.3.2. Distance from main entrance of the area
The roads passing through the study area are provincial roads. It is a connection of Berau District and its major city Tanjung Redeb and the capital of the province of East Kalimantan, the city of Samarinda. All main transportation to Samarinda such as buses, trucks and public car pass through the road. People can pass through the area easily. The entrance to the study area is considered to be important as the entrance for many people, including transmigrant and people from outside of the area.
Figure 5.5. Distance from entrance classes
This entrance also leads to the market outside the area. Using distance calculation from entrance, the distance map of entrance was obtained. This map was classified into 1 km interval (Figure 5.5). The logging area within those classes was the result of overlay between this map and illegal logging map.
By looking at Figure 5.6, we can see in year 2002 most of illegal logging area was concentrated in closest distance to the entrance. While in year 2003, people looked after new spots and therefore go further from the entrance.
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Illegal logging area (%)
Comparison of illegal logging percentage within distance from entrance classes (2002,2003)
20.00 10.00
0.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Year 2002 21.8 18.1 20.1 3.69 6.79 3.32 4.25 7.62 5.82 3.69 0.65 0 2.68 1.06 0.23 0.05 0 0 Year 2003 5.0 9.3 7.9 7.5 7.8 7.6 6.2 6.5 8.8 7.3 4.3 3.2 6.2 4.5 3.6 3.2 1.0 0.1
Distanc e from entranc e c lasses
Figure 5.6. Comparison of illegal logging percentage within distance from entrance
Figure 5.6 shows the trend of illegal logging percentage related to the distance from entrance. The most illegal logging area was found in the close distance with the entrance. The further the distance, the lower the percentage of illegal logging. This trend is also in accordance with the correlation analysis. It shows a high correlation (year 2002: rs=-0.859, 0.01 level, 2-tailed; year 2003: rs=-0.788, 0.01 level, 2tailed).
5.4. Analysis of factors affecting illegal logging
The study area covers 6,748.2 ha of production forest. This area has been logged between the year of 1976 and 1980. After 24-28 years being logged, the forest has already recovered from logging. The second felling cycle by the managing company will begin in year 2011.
Logging by the managing company is a planned logging. It follows the rule given by government on forest management. The issue of sustainability is the basic concept to have a good management of the area.
The silvicultural system applied in the study area is called selective cutting and planting (TPTI). According to the national forest management guidelines an average of 8 trees per hectare are felled at 35-years interval.
Monetary crisis and political situation in mid-1997 has affected many sectors in Indonesia, including natural resources management. Because of economical reason, people look for short investment and immediate income. The forest has become vulnerable because of this situation.
In the year 2002, 3 % or 194.9 ha of the area were illegally logged. Illegal logging in this area is in the form of single tree felling. Each tree was selected, cut and sawn on the spot by illegal loggers. They transport this sawn timber to outside the forest until reaching the market.
In less than 1 year, illegal logging was increased significantly in this area. In RKL 1, 30% of the area or 2,040.3 ha of the area was illegally logged. This devastated situation can be seen clearly in the field.
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What is happening in the field can be the base of argument to do immediate actions to stop this situation. The knowledge on relationship between physical factors and percentage of illegal logging can give an idea about how people decided to select and cut the trees.
There are some research on relationship between physical factors and deforestation (Ato, 1996; Selamat et al, 2000; Bavaghar et al, 2003). Those physical factors are including distance from road, slope, distance from settlement, distance from river, elevation, soil, forest cover and aspect.
The result on relationship between physical factors and percentage of illegal logging has shown that the existence of road is the main issue. It is in accordance with the field findings. In tracking the spot of illegal logging, it is very clear that people starting the logging in the closer distance from the road. Continuously they select each tree as they are moving further from the road after having trees cut in the closer distance. This is related also with the cost and time benefit of having the closer distance.
In year 2002, almost 61% of the illegal logging area is concentrated within 200 m distance from roads. While in year 2003, the loggers have move further inside. Almost 67% of illegal logging area in year 2003 is within 1 km from the road. The illegal logging spots found in year 2003 are reaching beyond the range of distance found in year 2002.
Secondary road that is the old logging road of RKL 1 has also become an access to move further (Figure 5.8). Even though, most of these roads are difficult to be accessed. These were abandoned roads and often up and down in terms of slope condition. People can still access this area by foot and transport the sawn timber to the road manually.
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Figure 5.8. Passage found in the side of the main road to go inside the area (1)
The base camps built by the loggers have given so much advantage to these people. They can go to further inside. They have the equipments needed to cover some area. Later, they bring all outside when the truck pick them up. They will not move further unless they have cut a tree in the closer distance. Almost 48% of illegal
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logging were found within 600 m distance from roads. The forest in this distance has become vulnerable to be logged.
The findings on distance from roads and slope found similar in research on deforestation ((Ato, 1996); Bavaghar et al, 2003). More deforested area found in the closer distance from existing roads and in the flat terrain. It is more vulnerable to human disturbance.
Illegal loggers considered the closer distance from roads to be more efficient in terms of cost, time and security. It is in accordance with the field findings that more logging found in the closer distance from roads. The loggers would easily bring the sawn wood to the side of the road, so the truck can bring it later (Figure 5.9).
Figure 5.9. The sawn wood was left in the side of the road, later will be picked up by trucks
The entrance to RKL 1 was considered to be analysed related to illegal logging. There are roads passing through the other part of Labanan Concession, but the area of RKL 1 has shown a prominent condition of illegal logging. This is the only entrance to many people from outside the area.
As mentioned before, the road passing through RKL 1 is a provincial road. It is the connection road of district capital of Berau and capital city of East Kalimantan. Most operating sawmills are located within 10 km radius of the district capital of Tanjung Redeb (Obidzinksi & Suramenggala, 2000). Loggers go inside the area to conduct illegal logging and bring the timber to further destination for selling it.
The correlation has shown that there is a relationship between the entrance and percentage of illegal logging. More illegal logging spots were found in the closer distance from entrance. In year 2002, when there was only 3% of illegal logging found in the area, most of illegal logging was concentrated in the closest distance to entrance. Because the closer to the entrance the closer to escape out of the official border of Labanan Concession. So, the illegal logging will be out of jurisdiction of Inhutani I. Moreover, when illegal loggers are closer to the entrance, it means they are closer to Tanjung Redeb where they deliver the sawn wood. In year 2003, illegal logging has happened in many part of the area. Even though, the trend remains the same.
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6. CONCLUSIONS AND RECOMMENDATIONS
This chapter includes conclusions and recommendations that were drawn based on the findings of this research. The objective of this research is to investigate the physical factors affecting illegal logging in a form of single tree felling using optical remotely sensed data and GIS.
6.1. Conclusions
1. Regarding to research question 1 : “Are there relationship between distance from road and distance from entrance and illegal logging in a form of single tree felling?
Distance from roads and distance from entrance are the physical factors that have strong relationship with illegal logging in a form of single tree felling.
2. Regarding to research question 2: “How are those factors affecting illegal logging in a form of single tree felling?
Based on field knowledge and the analysis of relationship between physical factors and illegal logging area, it is concluded that the physical factors affecting illegal logging are related to accessibility to the area. Good accessibility gives benefit to illegal loggers in terms of cost and time efficiency and minimizing the effort in cutting the tree.
1. Road is the main factor affecting illegal logging, the closer to the road, the more illegal logging occurred.
2. The closer to the entrance, the more illegal logging occurred
6.2. Recommendations
By having an increasing and devastating number of illegal logging area, monitoring of newly logged points should be done in short period of time continuously. The methods of detecting and monitoring illegal logging should be developed. The test and validation of classification result should be further developed in relation with the condition in the field.
References
AAI. (2001). IMAGINE Subpixel ClassifierTM User's Guide Version 8.5 for UNIX and WINDOWS.
Atmopawiro, V. P. (2004). Detection of Single Tree Felling in the Tropical Forest using Optical Satellite Data and Image Classification Techniques (A Case Study in The Labanan Concession, East Kalimantan, Indonesia). Unpublished Thesis. International Institute for Geo-Information Science and Earth Observation, Enschede.
Ato, V. A. (1996). Prediction of deforestation using Area Production Model and GIS, A case study of Phrao, Chiangmai, Thailand. Unpublished Thesis. International Institute of Aerospace Survey and Earth Sicences, Enschede.
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Bavaghar, M. P., Darvishsefat, A. A., & Namiranian, M. (2003). The study of spatial distribution of forest changes in the northern forests of Iran. GISdevelopment.net. Retrieved, 2004, from the World Wide Web: www.gisdevelopment.net
BFMP. (2001). Mapping vegetation and forest types using Landsat TM in the Labanan concession of PT Inhutani I. Berau: BFMP.
Bhandari, S. P. (2003). Remote Sensing for Forest Certification, Detecting and Characterizing Selective Logging in Tropical Forest (A case study in Labanan concession, East Kalimantan, Indonesia). Unpublished Thesis. ITC, Enschede.
Bouriad, L., & Niskanen, A. (2003, 24-27 March 2003). Illegal logging in the context of the sound use of wood. Paper presented at the Strategiesfor the Sound Use of Wood, Romania.
Brack, D., & Hayman, G. (2001). Intergovernmental Actions on Illegal Logging. Paper presented at the Conference on Forest Law Enforcement and Governance, London.
BUMNOnline. (2003). PT. Inhutani I Mengelola Hutan Bersama Pemda Tk. II Berau. BUMN Online. Retrieved 9-2-2002, 2004, from the World Wide Web: bumnri.com
Casson, A., & Obidzinksi, K. (2002). From New Order to Regional Autonomy: Shifting Dynamics of "Illegal" Logging in Kalimantan, Indonesia. World Development, 30, 2133-2151.
Cui, Y. (2003). Remote Sensing and GIS for Supporting Sustainable Forest Management Certification in the Tropics (A case study in Labanan Concession, East Kalimantan, Indonesia). Unpublished Thesis. ITC, Enschede.
Dahal, P. P. (2002). Determination of Forest Status Using Selected Criteria and Indicators of Sustainable Forest Management (A Case study of Labanan concession, East Kalimantan, Indonesia). Unpublished Thesis. ITC, Enschede.
de By, R. A. (Ed.). (2001). Principles of Geographic Information Systems, An introductory textbook (second ed.). Enschede: ITC.
FAO. (2000, 6-03-2001). Legal and institutional framework for SFM. FAO. Retrieved 14-07-2003, 2003, from the World Wide Web: http://www.fao.org/forestry/fo/country/index.jsp?geo_id=82&lang_id=1
FAO. (2001). Deforestation continues at a high rate in tropical areas; FAO calls uppon countries to fight forest crime and corruption. FAO. Retrieved 10-07-2003, 2003, from the World Wide Web: http://www.fao.org/WAICENT/OIS/PRESS_NE/PRESSENG/2001/pren0161.htm
Flanagan, M., & Civco, D. L. (2001). IMAGINE Subpixel Classifier Version 8.4. Photogrammetric Engineering and Remote Sensing, 67(1).
FSC. (2000). FSC Principles and Criteria. FSC. Retrieved 17 June, 2003, from the World Wide Web: http://www.fscoax.org/html/1-2.html
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ITTO. (1992). Criteria for the Measurement of Sustainable Tropical Forest Management; ITTO Policy Development Series No. 3. Yokohama: ITTO.
ITTO. (2001). Annual Report for 2001. Yokohama: International Tropical Timber Organization.
Janssen, L. L. F., & Huurneman, G. C. (Eds.). (2001). Principles of Remote Sensing (2nd ed.). Enschede: ITC.
Larsen, J. (2002). Illegal Logging Threatens Ecological and Economic Stability. Earth Policy Institute. Retrieved June, 2003, from the World Wide Web: www.earthpolicy.org
Lillesand, T. M., & Kiefer, R. W. (1994). Remote Sensing and Image Interpretation (third edition ed.). New York: John Wiley & Sons.
Novarina, D. (2003). GIS and RS in Support of Adaptive Collaborative Management, A Case Study in Labanan Forest Concession Area, Indonesia. Unpublished Thesis. ITC, Enschede.
Obidzinksi, K., & Suramenggala, I. (2000). Informal Timber Sector in Berau, East Kalimantan. Bogor: CIFOR.
Palmer, C. E. (2000). The Extent and Causes of Illegal Logging: An Analysis of A Major Cause of Tropical Deforestation in Indonesia. University College London, London.
Rametsteiner, E., & Simula, M. (2003). Forest Certification -- an instrument to promote sustainable forest management? Journal of Environmental Management, 67(1), 87-98.
Rikimaru, A., & Miyatake, S. (1997, October 1997). Development of Forest Canopy Density Mapping and Monitoring Model using Indices of Vegetation, Bare Soil and Shadow. Paper presented at the 18th of ACRS, Kuala Lumpur, Malaysia.
Selamat, I., Mohamed, A. N., & Hussin, Y. A. (2000). Modelling deforestation using Remote Sensing and GIS: MACRES-ITC.
Smith, W. (2002). The Global problem of illegal logging. ITTO. Retrieved 17 June, 2003, from the World Wide Web: www.itto.or.jp
UNEP. (2002). Agenda 21. UNEP. Retrieved August, 2003, from the World Wide Web:
Wardojo, W., Suhariyanto, & Purnama, B. M. (2001). Law Enforcement and Forest Protection in Indonesia: A Retrospect and Prospect. Paper presented at the Conference on Forest Law Enforcement and Governance, Bali.
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using remote sensing and GIS (A case study in Labanan Concession, East Kalimantan, Indonesia)
ANITA ZAITUNAH
Jurusan Kehutanan Fakultas Pertanian Universitas Sumatera Utara
Abstract
There is a decreasing of forest area and the quality itself worldwide especially in developing and tropical countries. Illegal logging is one of the factors considered in causing this condition. Illegal logging in this research is in a form of single tree felling. This research tried to investigate the physical factors affecting single tree felling of illegal logging using optical remotely sensed data and GIS.
Two sets of Landsat-7 ETM+ data acquired on 16 August 2002 and 31 May 2003 were used in this research. Subpixel Classifier was applied to obtain the classified map showing newly logged points, which is illegal logging spots.
Some physical factors were decided to be analysed to find out their relationship with illegal logging. Two of the factors are distance from roads and entrance. Maps were built representing classes on those factors. Those maps were individually crossed with illegal logging maps of year 2002 and 2003. The relationship between each factor and percentage of illegal logging was analysed using Spearman’s correlation.
The result of overlay between each factors and illegal logging maps shows their relationship in both years. More illegal logging found in the closer distance from roads and closer distance from entrance.
It is concluded that there is a relationship between distance from road and distance from entrance with illegal logging.
By having an increasing and devastating number of illegal logging area, monitoring of newly logged points should be done in a short period of time continuously.
Abbreviations and Acronyms
AAI ACM BFMP DEM FAO FCD FSC GIS
Applied Analysis Inc. Adaptive Collaborative Management Berau Forest Management Project Digital Elevation Model Food and Agriculture Organization Forest Canopy Density Forest Stewardship Council Geographic Information System
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GPS Ha HPHH ILWIS IPK IPPK timber) ITTO IUCN LEI MOI NGO RKL SFM TM TPTI
UNEP
Global Positioning System Hectare Hak Pemungutan Hasil Hutan (License to collect forest products) Integrated Land and Water Information System Izin Pemanfaatan Kayu (License to extract and use timber) Izin Pemungutan dan Pemanfaatan Kayu (License to collect and use
International Tropical Timber Organization international union for conservation of nature and natural resources Lembaga Ekolabel Indonesia (Indonesian Ecolabelling Institute) Material of Interest Non Governmental Organization Rencana Karya Lima Tahun (Five year working plan) Sustainable Forest Management Thematic Mapper Tebang Pilih Tanam Indonesia (selective cutting and planting)
United Nation Environmental Programme
1.1. Background
INTRODUCTION
Forest is a valuable natural resource that should be maintained sustainably. It has many functions to support human’s life. Wood as a result of logging activities is one of its important products. These activities have built the relationship between producer, consumer and the products. Forest functions will be maintained as long as the forest is managed in sustainable ways.
In fact, there is a decreasing of forest area and the quality itself worldwide especially in developing and tropical countries. Of the 15.2 million ha of natural forest lost annually in the tropics, 14.2 million ha were converted to other land uses and 1.0 million ha were converted to forest plantations (FAO, 2001).
Illegal logging is one of the factors considered causing deforestation (Selamat, Mohamed, & Hussin, 2000). It is a logging neglecting the sustainability aspect due to illegal activities. This process will definitely contribute to the rate of deforestation.
The alarming rate of deforestation has brought about people’s awareness to have a better forest management. International Tropical Timber Organization (ITTO) has formulated the definition of sustainable forest management (SFM) as “the process of managing permanent forest land to achieve one or more clearly specified objectives of management with regard to the production of a continuous flow of desired forest products and services without undue reduction of its inherent values and future productivity and without undue undesirable effects on the physical and social environment” (ITTO, 1992).
1.2. Problem Statement
During the 1990s, the loss of natural forests was 16.1 million hectares per year, of which 15.2 million occurred in the tropics. These are corresponding to annual losses of 0.4 percent globally and 0.8 percent in the tropics. There are major causes for the loss mentioned by FAO: conversion to other land uses (mainly agriculture), pests and
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diseases, fire, overexploitation of forest products (industrial wood, fuel wood), poor harvesting practices, overgrazing, air pollution and storms (FAO, 2001).
The deforestation rate of Indonesia between 1985 and 1997 was around 1.8 million hectares/year. Between 1985 and 1998, the ratio of forest area to total land area fell from 62.7 percent to 50.6 percent (FAO, 2000). Furthermore, FAO mentioned that dry lowlands as the most valuable for commercial logging and biodiversity conservation have the most forest cover loss.
Deforestation and forest degradation are mostly caused by illegal activities. These include over-cutting of forests and cutting in unauthorised areas. In Indonesia, there is a smuggling of illegal logs to neighbouring countries. Widespread of illegal logging networks operate at the district level. About 40-60% of the total industrial round wood supply has been estimated come from illegal logging (FAO, 2000).
Figure 1.1. Single tree felling by illegal loggers. Tree was sawn in the spot using chain saw and transported outside the area
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Literature study on forest certification, illegal logging, remote sensing & GIS
Define the research objectives and research question
Study area selection
Training & test data
Image preparation Field data collection
Map layers compilation FCD mapping
Illegal logging maps
Data processing and analysis
Extraction information on factors affecting illegal logging, logging
intensity and forest canopy density
Conclusions
Figure 1.2. Research Approach
In this research, illegal logging is defined as illegal felling of a single tree. It is not in a form of clear cutting or cutting many trees or cluster of trees. The loggers would go inside the forest looking for trees to be cut. They select a big enough and commercial tree and then cut it. The selected tree would then sawn in the spot and transport outside. Illegal logging spots can be seen as in Figure 1.1.
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A serious attention should be given to combat illegal logging. We need to know what is happening in the forest. The knowledge on what do people take into account before they select a tree, cut and sawn the timber in the spot illegally would help combating illegal logging.
1.3. Research Objectives
The objective of this research is to investigate distance from road and distance from entrance in affecting illegal logging in a form of single tree felling using optical remotely sensed data and GIS.
1.4. Hypothesis
Distance from road and distance from entrance affecting illegal logging in a form of single tree felling could be identified using optical remotely sensed data and GIS.
1.5. Research Questions
In order to achieve the objectives of this research, the following questions need to be answered:
1. Are there relationship between distance from road and distance from entrance and illegal logging in a form of single tree felling?
2. How are those factors affecting the illegal logging of single tree felling?
1.6. Research approach
In order to achieve the objectives of this research, the research approach has been conducted as a guideline. The research approach is shown in Figure 1.2.
2. LITERATURE REVIEW
2.1. Definition and scope of illegal logging
Smith (2002) mentioned that illegal logging term refers to timber harvesting-related activities inconsistent with national (or sub-national) laws. The scope of those activities can be the entire industry from wood harvesting until product reaching the market.
The following are different types which considered as illegal logging (Brack & Hayman, 2001):
Logging in violating contractual obligations Obtaining concessions illegally, for example, corrupt means Logging nationally-protected species without explicit permission Logging outside concession boundaries Logging in forbidden or protected areas Removing under or over-sized trees Laundering illegal timber through a concession Use of old log permits or licences to collect illegally felled timber
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2.2. Illegal logging in Indonesia
Illegal logging and other forest crimes have expanded into protected areas of Indonesia. There are more pressure on endangered and endemic species of flora and fauna. A number of high profile species now face a real and ever-present threat of extinction (Wardojo et al., 2001).
Larsen (2002) has mentioned that Indonesia‘s domestic wood supply of 2002 was 20 million cubic meters, while the demand stood at some 60 million cubic meters. This gap was filled by illegal logging and destroy ten million hectares of Indonesia’s forest.
The council had identified the causes and contributory factors to illegal logging (ITTO, 2001). The failure of forest laws, insufficient of management and control in timber production, availability of markets for illegal logs, low risk and high profitability of illegal logging, lack of inter-sector coordination are among factors mentioned by the Council.
Casson & Obidzinski (2002) mentioned a number of factors attributed to the recent boom in illegal logging including changes arising from “reformasi” – a calling for democracy, reform and change – and the new decentralization laws. Central government give the authority to local government to manage their natural resources. Governors and Regents have the authority to issue permits for small forest concessions. Governors were allowed to grant concessions of up to 10,000 ha, and Regents were allowed to grant concessions up to 100 ha.
2.3. Remote Sensing and GIS
Remote sensing is the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation (Lillesand & Kiefer, 1994). Information is derived from the image data, which form a (limited) representation of the real world (Janssen & Huurneman, 2001).
Remote sensing relies on the measurement of electromagnetic energy. Electromagnetic energy can take several forms. Many sensors used in remote sensing measure reflected sunlight. Some sensors, however, detect energy emitted by the Earth itself or provide their own energy (Janssen & Huurneman, 2001).
GIS stands for geographic information system. It is a computerized system that helps in maintaining data on geographic space. In the wider sense, a GIS consists of software, data, people, and an organization in which it functions. A GIS always consists of modules for input, storage, analysis, display and output of spatial data (de By, 2001).
The following are three stages of working with geographic data mentioned by de By (2001):
data preparation and entry; the early stage in which data is collected and prepared to be entered into the system
data analysis; the middle stage in which collected data is carefully reviewed data presentation; the final stage in which the results or earlier analysis are
presented in an appropriate way.
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3. STUDY AREA
The selected study area is located in Berau District. The selection of the study area is important in order to achieve the research objectives and answer research questions. It was based on its condition related to illegal logging activities.
3.1. Location
Labanan forest concession is located in Berau District, East Kalimantan Province, Indonesia. The location is between latitude of 1o49’ N and 2o10’ N and longitude of 116o57’ E and 117o27’ E. It covers an area of 83,240 ha. According to regional land use plan, Labanan area is allocated into three land use types. There are 54,567 ha of Fixed Production Forest, 26,997 ha of Limited Production Forest and 1,676 ha of Non Production Forest. The location of the study area is shown in Figure 3.1.
Figure 3.1. Labanan Forest Concession (BFMP, 2001)
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3.2. Forest Management System
The forest concession was managed by a state owned company, called PT. Inhutani I. It was established in 1974 and has applied selective logging since 1976.
Adaptive Collaborative Management (ACM) was established to have participation from stakeholders in this area. On 4 February 2003, PT Inhutani I and Regional Government of Berau have an agreement on operational cooperation for managing Labanan forest by establishing a share company called PT Hutansanggam Labanan Lestari (BUMNOnline, 2003).
The forest management unit has been divided into seven five-year working plan areas (known as RKL :Rencana Karya Lima tahun) (Table 3.1). The five-year working plan areas are shown in Figure 3.2.
The silvicultural system applied in the study area is called selective cutting and planting (TPTI). According to the national guidelines, an average of 8 trees per hectare are felled at 35-year interval. This management unit is going to enter a second felling cycle by the year 2011.
Figure 3.2. Five-year working Plan area (RKL)
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3.3. Climate and forest type
The study area has a typical tropical climate. The annual rainfall is about 2000 mm and every month receives more than 100 mm rainfall in most years (Cui, 2003).
The forest type of the study area is called lowland mixed dipterocarp forest due to the dominance of the dipterocarpaceae family. The most common genera within this family are Shorea, Dipterocarpus, and Vatica. While common species are Shorea parvifolia, Dipterocarpus acutangulus, Shorea pinanga and Shorea hopeifolia (Dahal, 2002).
3.4. The landscape
The Labanan area consists of undulating to rolling plain with isolated masses of high hills and mountains. It is located in inland of coastal swamps. The elevation of the study area ranges from about 12.5 to 437.5 m above sea level. According to Mantel (1998) mentioned in Bhandari (2003), the Labanan landscapes can be categorized as follows:
- Flat land: the floodplains adjacent to the river Siduung, Kelai and Segah - Sloping land: the dominant landscape of the area, undulating to rolling plain with
hillocks - Steep land: the medium to high gradient hills - Complex landforms: the limestone associated landscapes consisting of
undulating plains with rock outcrops
3.5. Socio-economical condition
There are fifteen villages and settlement including 3 transmigration settlement units surrounding Labanan area. There are 2 transmigration settlement units inside the area. The location of villages can be seen in Figure 3.3.
There are two types of community in the area; the first is a community originated from Java, brought by the government around 10 years ago through transmigration program. They mainly practice permanent lowland agriculture as they did previously in Java. The second is a Dayak Community. They live in some relatively new villages. They practice shifting cultivation and collect non-timber forest product. Not so many of them work as an employee of forest management company or government (Novarina, 2003).
3.6. Accessibility
Labanan area has a very good accessibility. There are main roads passing through the area connecting Tanjung Redeb to Samarinda (the capital city of East Kalimatan Province) and from Tanjung Redeb to some villages in Labanan.
The base camp of Labanan Concession can be reached through Segah River from Tanjung Redeb in approximately 20 minutes upstream by speedboat or by car through a paved provincial road for about 30 km and another 7 km through a logging road. Part of the road between Labanan and Tanjung Redeb is a segment of a main road in the region, which called trans-Kalimantan (Novarina, 2003).
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Figure 3.3. Location of villages in and surrounding Labanan Forest Concession (Novarina, 2003)
4. Methods and Materials
The research methods are divided into 3 stages. The stages are Pre-fieldwork, Fieldwork and Post-fieldwork.
4.1. Pre-Fieldwork Stage
The basic step of this research is literature review. The literature is related to the objective of this research and steps to come to the answers of the research questions. The literature study covers the following subjects:
Forest certification worldwide and in Indonesia Illegal logging activities and impact Remote sensing and GIS
For the fieldwork purposes, the images were prepared. The images were georeferenced. It was printed as hard copies for ground truth, field observation and comparison purposes.
4.2. Fieldwork Stage
The fieldwork was conducted in September 2003 in Labanan Concession, East Kalimantan, Indonesia. A consultation session was arranged before going to the field with the Head of Planning & Inventory of PT. Inhutani I. This session helped in identifying areas in the concession where illegal logging of single trees is taking place.
The following areas had been identified: RKL 1, RKL 4, RKL 5 and protection area. Because RKL 1 has the highest number of single tree felling of illegal logging, the test site for classification is reduced to RKL one.
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Collection of field data
The freshly logged points were purposively found by tracking the freshly used trails by illegal loggers on either side of the road. All points encountered in the forest that seemed to have been logged within one year were recorded.
Coordinates of permanent points such as road junctions were also collected to improve the georeference of the image. These variables were entered in a tally sheet, which was prepared before going into the field.
4.3. Post-Fieldwork Stage
The fieldwork has given the knowledge on what is going on in the spot related to illegal logging. Illegal logging in this research is in a form of single tree felling. Tree was sawn in the spot and transported outside. Spots were found along the main and secondary roads.
Based on the field investigation, information and related references, some factors had been taken into account to be analysed in their relation with illegal logging. Those factors are distance from roads and distance from entrance.
4.3.1. Preparation of factor maps
Figure 4.1 shows the steps on preparation and construction of factor maps. Data needed for these maps were constructed using ILWIS:
Distance maps: road, river, entrance
4.3.2. Construction of factor maps
Classes were determined for each factor. Each class represented the range of values within input map. Each input maps were classified according to their ranges. Those maps were created using ILWIS. At first, domain of each input was created. The domain contains the classes and range of values for the input map. The range of classes was defined with equal interval.
The following are the input maps which were being further classified:
Distance from road There are roads passing through the test site. Findings in the field have shown that illegal logging spots found along the road. The distance from road was divided into 200 m interval. There are 11 classes in 200 m interval. Those classes are 1-200 m (Class 1), 201-400 (Class 2), 401-600 (Class 3), 601-800 (Class 4), 801-1000 (Class 5), and so on until beyond 2000 m (Class 11).
Distance from entrance The entrance to the study area was considered to be important as the entrance for many people, including transmigrant and people from outside of the area. This entrance also leads to the market outside the area. The main entrance was digitised and being rasterized. Using distance calculation from entrance and consider the distance from road, the distance map of entrance was obtained. This map was classified into 1 km interval. The furthest distance from entrance is 26 km. So, there are 26 classes: 1, 2, 3, and so on until 26.
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4.3.3. Analysis of physical factors
Each factor was identified in 2 sources of information: illegal logging map of 2002 and illegal logging map of 2003. Both maps are the result of Subpixel classifier
Each input map was crossed with each illegal logging map. This step gave the evidence which factors have relationship with illegal logging.
4.4. Materials
The research considered certain types of data and information related to the study area. Landsat-7 ETM+ of 31 May 2003 was the input of FCD Mapper. The two maps of illegal logging were the result of subpixel classification of Landsat-7 ETM images; acquired date of 16 August 2002 and 31 May 2003.
Maps were needed to construct input maps: contour, RKL, boundary, river, road and entrance. Data and information related to the study area were also needed. These data came from the forest company and related institutions.
Hardware and software used in this research include computer, ILWIS, FCD Mapper, ERDAS, Microsoft, SPSS, Adobe Photoshop and internet. During fieldwork, global positioning system (GPS) receiver, camera, compass, measuring tapes used to collect field data.
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5. RESULTS AND DISCUSSIONS
This chapter describes the results obtained through data processing following the methods of the research. It will be used to answer the research questions.
2.4 Field knowledge on illegal logging activities
In year 2002, Bhandari (2003) found that the distance of 1 km from road as an effective range of logging. It can be considered logical because if the felling operation takes place far from the road, the operation becomes more expensive. From the field knowledge, he mentioned that nobody enters very deep in the forest to log a tree because all logging are mainly for commercial purpose. Distance factor can be used to refine the information derived from remotely sensed data.
Figure 5.1. Truck loading sawn wood from single tree felling (Bhandari, 2003)
As the time goes by, people become more and more seeing the potential of having income from cutting trees illegally in the form of single tree felling. Based on the fieldwork conducted in year 2003, people can go further than 1 km from the main roads. They use the secondary road that was a logging road and skidding trails of the company in the last felling scheme (period of 1976-1980). They bring the sawn timber to the location where the truck was ready to transport to further destination (Figure 5.1.).
The loggers consist group of people of 6 to 7. They select and cut a single commercial tree and sawn it on the spot. The sawn timber would be brought outside manually and put by the people near the main road. Later, a truck was ready to transport the timber to their destination. So, they will select the trees from a reasonable distance, which should not be far from the main roads.
There was also an important finding inside the area. The illegal loggers would
establish small base camps for their activities and operation inside the forest. By
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Figure 5.2. Base camps found in some location inside the study area
having the place to stay, they can go further inside and store the sawn timber in those camps (Figure 5.2.). Later, they can transport the sawn timber to the main road.
The old logging roads inside the area were established by the company in the logging year of 1976-1980. The length of the road was 2-4 km from main roads to inside the forest. There was no illegal logging found beyond 4 km due to the accessibility. During the fieldwork, the farthest distance where illegal logging spots found was 1.5 km from the main roads. The spots had been revisited by the company and found the farthest distance range of 1-2 km1. In RKL 1, about 60% of the area is within 2 km distance from roads. The condition of the road is not the same in whole area. Some roads are still accessible for the truck to come inside for a short distance. Others are difficult to be accessed by truck due to bad condition and steep slope.
By having the field knowledge and information, the result of the image classification of 2003 was refined with the distance factor. The distance considered as an effective range for the loggers was 2 km from the main road.
5.3. Relationship between physical factors and illegal logging
In order to see the relationship between physical factors and illegal logging, overlay operation was conducted between each factor map and illegal logging map of 2002 and 2003. It was decided to consider the percentage of illegal logging by dividing illegal logging area found in each class with the total area of illegal logging of whole study area.
5.3.1. Distance from road
Distance from road was calculated using distance calculation in ILWIS. This map was further classified into 200 m interval (Figure 5.3). The main road is passing through
1 Personal communication with Ir. Doddy H. W., Inhutani I Labanan
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the study area. This road is a provincial road connected Tanjung Redeb (District capital of Berau) and Samarinda (capital city of East Kalimantan).
Figure 5.3. Distance from road classes
It is clear that illegal logging in this area found mostly in close distance from roads. The trend is the same in 2002 and 2003 (Figure 5.4). In year 2002, 61% of illegal logging area are within 200 m from roads while in year 2003 67% are within 1 km distance. The illegal logging found in 2003 are reaching beyond the range of distance in 2002.
Comparison of illegal logging percentage within distance from road classes (2002,2003)
Illegal logging area (%)
60
40
20 0
1 23 45 67 8
Year 2002 61 20
8
6
5
0
0
0
Year 2003 17 18 13 10
9
8
7
7
Distance from road classes
9 10
00 65
Figure 5.4. Illegal logging area within distance from road classes
(Class 1:1-200, Class 2:201-400, Class 3:401-600, Class 4:601-800, Class 5:801-1000, Class 6:1001-1200, Class 7: 1201-1400, Class 8:1401-1600, Class 9:1601-1800, Class 10:1801-2000)
There was an increasing area being logged in all classes in ha. In terms of
percentage, there was decreasing number of illegal logging in lower classes (200-400
m) and increasing number of illegal logging percentage in classes 3-5 (600-2000 m).
It means more logging in the closer and further distance from the roads.
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In both years, the correlation between percentage of illegal logging area and the distance from road is found very high (rs=-1 (year 2002), rs=-0.988 (year 2003), 0.01 level, 2-tailed). The closer to the road, the more Illegal logging found. It is in accordance with what was found in the field. Good accessibility is the most important factor affecting illegal logging in terms of transporting the illegal sawn timber of single tree felling.
5.3.2. Distance from main entrance of the area
The roads passing through the study area are provincial roads. It is a connection of Berau District and its major city Tanjung Redeb and the capital of the province of East Kalimantan, the city of Samarinda. All main transportation to Samarinda such as buses, trucks and public car pass through the road. People can pass through the area easily. The entrance to the study area is considered to be important as the entrance for many people, including transmigrant and people from outside of the area.
Figure 5.5. Distance from entrance classes
This entrance also leads to the market outside the area. Using distance calculation from entrance, the distance map of entrance was obtained. This map was classified into 1 km interval (Figure 5.5). The logging area within those classes was the result of overlay between this map and illegal logging map.
By looking at Figure 5.6, we can see in year 2002 most of illegal logging area was concentrated in closest distance to the entrance. While in year 2003, people looked after new spots and therefore go further from the entrance.
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Illegal logging area (%)
Comparison of illegal logging percentage within distance from entrance classes (2002,2003)
20.00 10.00
0.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Year 2002 21.8 18.1 20.1 3.69 6.79 3.32 4.25 7.62 5.82 3.69 0.65 0 2.68 1.06 0.23 0.05 0 0 Year 2003 5.0 9.3 7.9 7.5 7.8 7.6 6.2 6.5 8.8 7.3 4.3 3.2 6.2 4.5 3.6 3.2 1.0 0.1
Distanc e from entranc e c lasses
Figure 5.6. Comparison of illegal logging percentage within distance from entrance
Figure 5.6 shows the trend of illegal logging percentage related to the distance from entrance. The most illegal logging area was found in the close distance with the entrance. The further the distance, the lower the percentage of illegal logging. This trend is also in accordance with the correlation analysis. It shows a high correlation (year 2002: rs=-0.859, 0.01 level, 2-tailed; year 2003: rs=-0.788, 0.01 level, 2tailed).
5.4. Analysis of factors affecting illegal logging
The study area covers 6,748.2 ha of production forest. This area has been logged between the year of 1976 and 1980. After 24-28 years being logged, the forest has already recovered from logging. The second felling cycle by the managing company will begin in year 2011.
Logging by the managing company is a planned logging. It follows the rule given by government on forest management. The issue of sustainability is the basic concept to have a good management of the area.
The silvicultural system applied in the study area is called selective cutting and planting (TPTI). According to the national forest management guidelines an average of 8 trees per hectare are felled at 35-years interval.
Monetary crisis and political situation in mid-1997 has affected many sectors in Indonesia, including natural resources management. Because of economical reason, people look for short investment and immediate income. The forest has become vulnerable because of this situation.
In the year 2002, 3 % or 194.9 ha of the area were illegally logged. Illegal logging in this area is in the form of single tree felling. Each tree was selected, cut and sawn on the spot by illegal loggers. They transport this sawn timber to outside the forest until reaching the market.
In less than 1 year, illegal logging was increased significantly in this area. In RKL 1, 30% of the area or 2,040.3 ha of the area was illegally logged. This devastated situation can be seen clearly in the field.
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What is happening in the field can be the base of argument to do immediate actions to stop this situation. The knowledge on relationship between physical factors and percentage of illegal logging can give an idea about how people decided to select and cut the trees.
There are some research on relationship between physical factors and deforestation (Ato, 1996; Selamat et al, 2000; Bavaghar et al, 2003). Those physical factors are including distance from road, slope, distance from settlement, distance from river, elevation, soil, forest cover and aspect.
The result on relationship between physical factors and percentage of illegal logging has shown that the existence of road is the main issue. It is in accordance with the field findings. In tracking the spot of illegal logging, it is very clear that people starting the logging in the closer distance from the road. Continuously they select each tree as they are moving further from the road after having trees cut in the closer distance. This is related also with the cost and time benefit of having the closer distance.
In year 2002, almost 61% of the illegal logging area is concentrated within 200 m distance from roads. While in year 2003, the loggers have move further inside. Almost 67% of illegal logging area in year 2003 is within 1 km from the road. The illegal logging spots found in year 2003 are reaching beyond the range of distance found in year 2002.
Secondary road that is the old logging road of RKL 1 has also become an access to move further (Figure 5.8). Even though, most of these roads are difficult to be accessed. These were abandoned roads and often up and down in terms of slope condition. People can still access this area by foot and transport the sawn timber to the road manually.
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Figure 5.8. Passage found in the side of the main road to go inside the area (1)
The base camps built by the loggers have given so much advantage to these people. They can go to further inside. They have the equipments needed to cover some area. Later, they bring all outside when the truck pick them up. They will not move further unless they have cut a tree in the closer distance. Almost 48% of illegal
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logging were found within 600 m distance from roads. The forest in this distance has become vulnerable to be logged.
The findings on distance from roads and slope found similar in research on deforestation ((Ato, 1996); Bavaghar et al, 2003). More deforested area found in the closer distance from existing roads and in the flat terrain. It is more vulnerable to human disturbance.
Illegal loggers considered the closer distance from roads to be more efficient in terms of cost, time and security. It is in accordance with the field findings that more logging found in the closer distance from roads. The loggers would easily bring the sawn wood to the side of the road, so the truck can bring it later (Figure 5.9).
Figure 5.9. The sawn wood was left in the side of the road, later will be picked up by trucks
The entrance to RKL 1 was considered to be analysed related to illegal logging. There are roads passing through the other part of Labanan Concession, but the area of RKL 1 has shown a prominent condition of illegal logging. This is the only entrance to many people from outside the area.
As mentioned before, the road passing through RKL 1 is a provincial road. It is the connection road of district capital of Berau and capital city of East Kalimantan. Most operating sawmills are located within 10 km radius of the district capital of Tanjung Redeb (Obidzinksi & Suramenggala, 2000). Loggers go inside the area to conduct illegal logging and bring the timber to further destination for selling it.
The correlation has shown that there is a relationship between the entrance and percentage of illegal logging. More illegal logging spots were found in the closer distance from entrance. In year 2002, when there was only 3% of illegal logging found in the area, most of illegal logging was concentrated in the closest distance to entrance. Because the closer to the entrance the closer to escape out of the official border of Labanan Concession. So, the illegal logging will be out of jurisdiction of Inhutani I. Moreover, when illegal loggers are closer to the entrance, it means they are closer to Tanjung Redeb where they deliver the sawn wood. In year 2003, illegal logging has happened in many part of the area. Even though, the trend remains the same.
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6. CONCLUSIONS AND RECOMMENDATIONS
This chapter includes conclusions and recommendations that were drawn based on the findings of this research. The objective of this research is to investigate the physical factors affecting illegal logging in a form of single tree felling using optical remotely sensed data and GIS.
6.1. Conclusions
1. Regarding to research question 1 : “Are there relationship between distance from road and distance from entrance and illegal logging in a form of single tree felling?
Distance from roads and distance from entrance are the physical factors that have strong relationship with illegal logging in a form of single tree felling.
2. Regarding to research question 2: “How are those factors affecting illegal logging in a form of single tree felling?
Based on field knowledge and the analysis of relationship between physical factors and illegal logging area, it is concluded that the physical factors affecting illegal logging are related to accessibility to the area. Good accessibility gives benefit to illegal loggers in terms of cost and time efficiency and minimizing the effort in cutting the tree.
1. Road is the main factor affecting illegal logging, the closer to the road, the more illegal logging occurred.
2. The closer to the entrance, the more illegal logging occurred
6.2. Recommendations
By having an increasing and devastating number of illegal logging area, monitoring of newly logged points should be done in short period of time continuously. The methods of detecting and monitoring illegal logging should be developed. The test and validation of classification result should be further developed in relation with the condition in the field.
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