Land Change Analysis from 2000 to 2004 in Peatland of Central Kalimantan, Indonesia Using GIS and an Extended Transition Matrix
This chapter analyzes the land cover transitions for a tropical peatland in Central Kalimantan, Indonesia. We constructed a transition matrix using land cover maps derived from classified Landsat images obtained from the years 2000 to 2004, and analyzed the transitions among Forest, Bare land, and Grass land. The results give insights of interpretations of land cover transitions and intensity analysis. Forest is involved in most of the changes; however, it is the only dormant category. The systematically avoiding transitions were from Forest to Bare land and from Bare land to Forest, in spite of the fact that the largest transition was from Forest to Bare Land. The systematically targeting transitions were from Bare land to Grass land and from Grass land to Bare land. In order to develop a deeper understanding of land cover transition, it is recommended to combine this method of analyzing the patterns of change with other types of research concerning the processes of change.
KeywordsDeforestation Transition matrix Central Kalimantan
Results shown in this paper were mainly obtained from SATREPS (Science and Technology Research Partnership for Sustainable Development) project entitled as “Wild fire and carbon management in peat-forest in Indonesia” founded by JST (Japan Science and Technology Agency) and JICA (Japan International Cooperation Agency).
- Barber CV, Schweithelm J (2000) Trial by fire-forest fire and forestry policy in Indonesia’s era of crisis and reform. World Resources Institute, Washington, DC, pp 6–11Google Scholar
- Eiden G, Vidal C, Georgieva N (2002) In: Gallego J (ed) Building agro-environmental indicators-focusing on the European area frame survey LUCAS, vol 1. European Commission, Ispra, pp 55–74, Chapter 4Google Scholar
- Hecker JH (2005) Promoting environmental security and poverty alleviation in the peat swamps of Central Kalimantan, Indonesia. Institute for Environmental Security, The Hague, pp 10–11, Version 1Google Scholar
- Lo CP, Yang XJ (2002) Drivers of land-use/land-cover changes and dynamic modeling for the Atlanta, Georgia Metropolitan Area. Photogramm Eng Remote Sens 68:1073–1082Google Scholar
- Osaki M, Hirano T, Inoue G, Honma T, Takahashi H, Takeuchi W, Kobayashi N, Evri M, Kohyama T, Ito A, Setiadi B, Sekine H, Hirose K (2010) In: Shin-ichi N et al (eds) The biodiversity observation network in the Asia-Pacific region: toward further development of monitoring. Springer, Japan, p 350, Chapter 2Google Scholar
- Ramankutty N, Graumlich L, Achard F, Alves D, Chhabra A, DeFries RS, Foley JA, Geist H, Houghton RA, Goldewijk KK, Lambin EF, Millington A, Rasmussen K, Reid RS, Turner BL (2006) In: Lambin EF, Geist HJ (eds) land-use and land-cover change: local process and global impacts. Springer, BerlinGoogle Scholar