Academic journal article The Indonesian Journal of Geography

Indonesia's Forest Resource Monitoring

Academic journal article The Indonesian Journal of Geography

Indonesia's Forest Resource Monitoring

Article excerpt

1.Introduction

Indonesia is home to the world's third largest tropical forest with tremendously high biodiversity values. It's unfortunate that for years the remarkable forest has been reported in experiencing second and even highest deforestation [e.g. FAO 2001, 2006, Hansen et al 2008b, 2009, Margono et al 2014a]. A fact that obviously made the forest plays an important role in both increasing greenhouse gas emissions and loss of biodiversity. As consequence, monitoring spatio-temporal Indonesia's forest dynamic is highly demanded. How this monitoring works in the country and how long it has been developed and operationally implemented, remain key questions to answer. This paper elaborates such questions.

At first, the Ministry of Forestry of Indonesia (MoF) developed forest resource monitoring through National Forest Inventory (NFI) project of Indonesia, established in 1989. The NFI project was executed for years under collaboration of the Government of Indonesia (GOI) and Food and Agriculture Organization (FAO). The use of satellite imagery to produce land cover map, which was pre-dominantly Landsat data, was introduced during the periods of NFI [Revilla and Liang 1989, 1992]. After termination of the NFI project at around 1997/1998, tasks for operationally mapping land cover were transferred into the Forestry Planning Agency/ Directorate General (DG) of Forestry Planning of the Ministry of Forestry. Under the DG of Forestry Planning, the more systematic monitoring approach was at first established in 2000. The system is now named National Forest Monitoring System (NFMS), which is based on a regular production of land cover map of Indonesia generated in three years interval, and provided in 23 land cover classes including class of cloud cover and no-data [MoF 2003a, 2003b, 2005, 2008, 2011, 2012, SNI 7645-2010]. Example of the Indonesia's land cover map is in figure 1, and the National Forest Monitoring System is available online at migrate to http://geoportal. menlhk.go.id/arcgis/home/for data display, viewing and simple analysis.

2.The Methods

Data

Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) have been used as main data source since early 1990s, of which some were combined with Système Pour l'Observation de la Terre (SPOT) 4 due to limitation on Landsat less- cloud data availability. Other data sets such as SPOT Vegetation 1.000 meter [Nugroho, 2005] and Moderate Resolution Imaging Spectroradiometer (MODIS) 500 meters [Hansen et al, 2006; 2008b] were also used for alternative. In the tropic such like Indonesia, clouds and haze are major problems of using optical remotely sensed data, including Landsat [Hoekman 1997; Hansen et al, 2008a; 2009]. Unluckily, unlike Brazil, Indonesia has no seasonal cloud-free window that offering opportunity to capture clouds-free images [Broich et al 2011]. The limited cloud-free image coverage and budget constraint restrict data availability for the system. However since 2008, given the change in Landsat data policy, the United States Geological Survey (USGS) has made Landsat data freely available over the internet [Wulder et al, 2012, Roy et al 2010]. Although most of data are available online at around 2009, the policy significantly gives Indonesia a chance and benefit to increase data available for the system. In 2013, MoF started using the newly launched Landsat 8 (Landsat Data Continuity Mission-LDCM) Operational Land Imager (OLI) to monitor Indonesian land cover condition and placed the Landsat 7 ETM+ as a substitution for cloud elimination.

Within early system development up to around 2008/2009, with all existing restrictions, the Ministry of Forestry only able to compile Landsat data for the entire country in three years interval (triennially). The three years interval was selected with time-allocation: first-year on data selection, second-year on obtaining the data including additional scene selection, and thirdyear for classification and mapping process. …

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