Widiatmaka, Wiwin Ambarwulan, Irman Firmansyah, Chandrasa E. Sjamsudin and Cecep Kusmana
Proceedings of the 36th Asian Conference on Remote Sensing 2015
Publication year: 2015


The pressure on forests in Indonesia increases as population growth continues, together with the rise of higher demand for land for development purposes. This study was conducted in South Kalimantan Province, Indonesia. The objectives of the study are: (i) to analyze changes in land use and land cover in forest areas, (ii) to model changes in land use and land cover, focusing on production forests, the area of forest where land cover should be maintained, and (iii) to formulate policy recommendations based on the two previous objectives. Changes in land use and land cover were analyzed using a series of Landsat imageries from 2000, 2003, 2006, 2009, 2011 and 2014. The supervised classification imagery analysis was performed using image interpretation software. The results of the image analysis were then overlaid with the Forest Area Status map , which outlined a delineation of production forest in the forest area. The results of the quantitative data were used as inputs for dynamic system modeling, which was performed using Powersim Constructor 8.1. Descriptive policy recommendations were compiled based on interviews with experts which then analyzed using interpretative structural modeling. The result showed an increasing shift trend inside production forest, from forest land cover towards non-forest land use and land cover. An analysis using dynamic system models can predict a decrease in forest cover if land use policies in forest area are functioning under the assumption of business-as-usual. The main factors causing pressure on production forest areas are minimal law enforcement, high intensity of illegal loggings and the high number of development permits given to mining and plantation sectors. Several recommendations can be made according to the study results.


  • Dynamic system model
  • forest area
  • forestry land use planning
  • interpretative structural model