Abstract
AbstractSpatial 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.
Publisher
Springer Science and Business Media LLC
Subject
Computers in Earth Sciences,Statistics, Probability and Uncertainty,General Agricultural and Biological Sciences,General Environmental Science
Reference51 articles.
1. Achmad A, Fadhly N, Deli A, Ramli I, Hadi R (2021) Model prediction and scenario of urban land use and land cover changes for sustainable spatial planning in Lhokseumawe, Aceh, Indonesia. IOP Conf Ser 847:12022
2. Aksoy H, Kaptan S (2021) Monitoring of land use/land cover changes using GIS and CA-Markov modeling techniques: a study in northern Turkey. Environ Monit Assess 193:1–21
3. Angi EM, Wiati CB (2017) Political economy study of deforestation and forest and land degradation in paser district, East Kalimantan. J Dipterocarp Ecosyst Res 3:63–80
4. Angriani P, Sumarmi RIN, Bachri S (2018) River management: the importance of the roles of the public sector and community in river preservation in Banjarmasin (a case study of the Kuin River, Banjarmasin, South Kalimantan – Indonesia). Sustaina Cities Soc 43:11–20
5. Arthayani NMNR (2020) Analysis of changes in forest cover area due to deforestation rates for calculation of carbon emissions (case study: Bukit Soeharto Grand forest Park, East Kalimantan Province). Malang National Institute of Technology
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