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A comparison of Sub-Pixel and maximum likelihood classification of Landsat ETM+ images to detect illegal logging in the tropical rain forest of Berau, east Kalimantan, Indonesia
Santosh P. Bhandari and Yousif Ali Hussin
Department of Natural Resources
The International Institute for Geoinformation Science
and Earth Observation (ITC), Hengelosstraat 99, 7500 AA,
Enschede, Netherlands
Fax: (31)53-4874-388
Email: Hussin@itc.nl,
Bhandari@itc.nl
1. Introduction
Forests are one of the world’s most important renewable natural resources that serve various economical, social and environmental functions. Tropical forest, which comprises 47% of the worlds total forest area, has the highest economic and environmental value. Although, tropical forests have high importance due to its values, they are decreasing quantitatively as well as qualitatively because of various problems. Deforestation and forest degradation have been emerging as more and more important issues of the world’s forestry sector. An area of 16.1 million ha of forests was lost every year during the 1990s, of which 15.2 million ha were in the tropics. The continuous depletion of forest resources is not only creating a serious threat to the regular supply of forest products but also resulting in a lot of negative environmental impact e.g. global warming, biodiversity loss etc. However, the world community has already realized the consequences and started to emphasize the sustainability of forest resources. United Nations Conference on Environment and Development (UNCED) held in June 1992 in Rio de Janeiro was the significant milestone in this regard.
Indonesia is rich in its forest resources. About 60% of country’s total land area is covered by forest representing approximately 10% of the world’s total tropical forest area. Timber has been an important source of national income since commercial logging started in the early 1960s. Concession holders carry out most of the management and harvesting activities. Selective Cutting and Planting (TPTI) is the commonly used silvicultural system in natural production forests of Indonesia. A series of activities has been established by the national guidelines for the implementation of the system to achieve the goal of sustainable forest management.
But, there are a lot of problems toward achieving the goal of sustainable forest management in Indonesia. Massive deforestation due to transmigration and illegal felling is one of the big problems. It has been estimated that about 50% of Indonesian total timber production comes from illegal means. The situation is worsening these days due to the change arising from the economic crisis, a decline in law and order, legal change arising from a movement calling for democracy, reform and change (popularly known as reformasi locally) and new decentralization law. The new laws have empowered the district government to issue the small forest concession and even to collect some revenue on their own decision
The importance of remote sensing to generate information for forest management has been widely recognized. It is the only way to acquire repetitive biophysical data for large geographic area at reasonable cost, accuracy and effort
Many studies have been carried out on the use of RS products to detect tropical deforestation. These studies mainly concentrated with land cover change from forest to non-forest etc and have been proved very useful for that purpose. But the possibility of using RS data to detect selective logging is poorly studied. As the selective felling is the adopted silvicultural practice of the Indonesian Forest Management System, only land cover change does not fully support the detection of spatial extent and intensity of such logging. In addition, Illegal loggers, who are only interested with timber quality and easy accessibility, generally carry out the selective logging. Though, it is clear that the selectively logged points become similar to other area in short period of time due to the fast growing nature of tropical forest it should be quite different for some period as felling of single tree creates an average of about 400 m2 of opening in such forest. Therefore, there is a possibility of detecting such newly logged points using medium resolution image data. In addition, integration of some geographic information system (GIS) operation with remote sensing data can strengthen the analysis. For example, the location of road is quite important for planned as well as unplanned, legal or illegal logging. Whatever be the methods, there is no doubt that if such selectively logged points can be identified with known level of error, it will be quite useful to support SFM certification, to monitor illegal logging and to take rehabilitation measures.
The objective of this research was to compare the ability of Sub-pixel Classifier and the traditional Maximum Likelihood Classifier in detecting tropical deforestation in form of selective illegal logging in Labanan Forest, East Kalimantan, Indonesia.
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