Simulating Future Forest Cover Changes in Pakxeng District, Lao People’s Democratic Republic (PDR): Implications for Sustainable Forest Management

Courage Kamusoko, Yukio Wada, Toru Furuya, Shunsuke Tomimura, Mitsuru Nasu and Khamma Homsysavath
Additional contact information
Courage Kamusoko: Asia Air Survey Co., Ltd, Kawasaki City, Kanagawa 215-0004, Japan
Yukio Wada: Asia Air Survey Co., Ltd, Kawasaki City, Kanagawa 215-0004, Japan
Toru Furuya: Asia Air Survey Co., Ltd, Kawasaki City, Kanagawa 215-0004, Japan
Shunsuke Tomimura: Asia Air Survey Co., Ltd, Kawasaki City, Kanagawa 215-0004, Japan
Mitsuru Nasu: Asia Air Survey Co., Ltd, Kawasaki City, Kanagawa 215-0004, Japan
Khamma Homsysavath: Forestry Inventory and Planning Division (FIPD), Ministry of Agriculture and Forestry, Laos

Land, 2013, vol. 2, issue 1, 1-19

Abstract: Future forest cover changes were simulated under the business-as-usual (BAU), pessimistic and optimistic scenarios using the Markov-cellular automata (MCA) model in Pakxeng district, Lao People’s Democratic Republic (PDR). The Markov chain analysis was used to compute transition probabilities from satellite-derived forest cover maps (1993, 1996, 2000 and 2004), while the “weights of evidence” procedure was used to generate transition potential (suitability) maps. Dynamic adjustments of transition probabilities and transition potential maps were implemented in a cellular automata (CA) model in order to simulate forest cover changes. The validation results revealed that unstocked forest and current forest classes were relatively well simulated, while the non-forest class was slightly underpredicted. The MCA simulations under the BAU and pessimistic scenarios indicated that current forest areas would decrease, whereas unstocked forest areas would increase in the future. In contrast, the MCA model projected that current forest areas would increase under the optimistic scenario if forestry laws are strictly enforced in the study area. The simulation scenarios observed in this study can be possibly used to understand implications of future forest cover changes on sustainable forest management in Pakxeng district.

Keywords: Markov chains; “weights of evidence”; Markov-cellular automata model; simulation scenarios; Lao PDR (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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