Calibration interval scenario approach in spatial modeling of land cover change in East Kalimantan from 2016 to 2036

Abstract

Spatial modeling can be used to predict future land cover changes based on past and present conditions. However, it is not yet known to what extent this model can be used to predict the future with reliable accuracy. Therefore, by using multi-temporal land cover data, this study aims to build an optimal model based on the calibration interval scenario. The optimal model is then used to predict and analyze changes in land cover in East Kalimantan in 2016–2036. 11 classified multi-temporal land cover maps from the Landsat Time Series using Random Forest in Google Earth Engine are used to model 14 calibration interval scenarios. A land Change Modeler is used to model and predict land cover change with 14 driving variables. The results of the classification of multi-temporal land cover maps show a good level of accuracy, with an Overall Accuracy value of 71.43–85.14% and a Kappa value of 0.667–0.827. Then 2016–2021 is one of the best scenarios with 5-year intervals where the accuracy of future predictions can still be relied upon for up to three prediction iterations. The calibration interval scenario approach in spatial modeling in East Kalimantan can be relied upon to show a decrease in forest cover from 2016 to 2021, with a deforestation rate of 651 km2/year. The prediction of land cover in 2036 estimates that the remaining forest cover area in East Kalimantan is 69.203 km2. It is believed that topography is the most influential variable driving land cover change in East Kalimantan.