The dynamics of land use/land cover change modeling and their implication for the flood damage assessment in the Tondano watershed, North Sulawesi, Indonesia

Abstract

The Markov Chain and Cellular Automata (Markov-CA) approach have been applied to create the dynamics of land use/land cover (LULC) change modeling in the Tondano watershed, North Sulawesi, Indonesia. The multi temporal of remotely sensed data, Landsat 5 TM in 1997, Landsat 7 TM in 2002 and Landsat 8 LDCM in 2015 were used to produce the LULC maps. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Map (GDEM) data were used as input for the flood modeling created by the Monte Carlo algorithm. The LULC maps in 1997 and 2002 were used to create predictions and modeling LULC map with the Markov-CA approach in the next few years (for the year 2015, 2025, 2035 and 2050). Meanwhile, the LULC map in 2015 with an accuracy of 80.11 % based on the calculation of the Kappa index has been used as a reference map to determine the accuracy of the Markov-CA approach to produce a model of the LULC map in 2015. The result of the accuracy by using cross-correlation matrix between the LULC model in 2015 with the LULC reference in 2015 is 75.88 %. The dynamics of LULC changes showed that area-class forest, dry land, paddy fields and shrubbery would be expected to experience an area decreases in the extent from the year 2015 to 2050, with the rate of change in average: 10.52, 13.22, 14.49 and 1.15 ha/year, respectively. Meanwhile, the area-class bare soil, plantation, settlement and water body would be expected to experience an area increases, with the rate of change in average: 6.79, 11.14, 11.49 and 9.7 ha/year, respectively. Furthermore, flood damage assessment can be calculated by estimating LULC area affected by the flood, which is determined based on the overlay between LULC maps from the result of Markov-CA with flood maps from the result of Monte Carlo algorithm. Under current conditions, estimated flood damage exposure to extreme flood events with return periods of 100 years for the water level scenario Hc = 3 m and Hc = 5 m is more than €520 and €958 million, respectively.