Email this article PREDIKSI PERUBAHAN TUTUPAN LAHAN DENGAN MODEL MARKOV CHAIN DAN ANN-MARKOV DI DAS KRUENG ACEH (Land cover change prediction using Markov Chain and ANN-Markov Model in Krueng Aceh Watershed)
Abstract
ABSTRACT
Prediction of land cover change will be a consideration in determining the development strategy in the future. There are many methods for predicting land cover change. It depends on data availability, model algorithms and output needed. The objective of this reasearch was to predict land cover change from 2007 to 2020 in the Krueng Aceh watershed. The method used remote sensing and GIS. The Markov Chain (MC) and Artificial Neural Network-Markov (ANN-M) models were used to understand the spatio-temporal dynamics of land cover. The accuracy of the classified imagery was obtained from on-screen digitation using medium resolution landsat-8 OLI image in 2020 with Kappa Accuracy around 84%. Both prediction algorithms used year 2007 (T1) and year 2017 (T2) land cover data to calculated the probability of land cover change prediction in year 2020 (T3). The Kappa Accuracy of both models shows a strong correlation between the simulated land cover maps and the results of visual interpretation (ANN=87.81% and MC=88.69%), this proves high accuracy of both models.
Key words: model; ANN-Markov; landcover change prediction; Markov Chain
ABSTRAK
Prediksi perubahan tutupan lahan yang baik akan menjadi pertimbangan dalam menentukan strategi pembangunan di masa depan. Terdapat banyak metode dalam melakukan prediksi perubahan tutupan lahan yang tergantung pada kebutuhan data, algoritma pemodelan yang dilakukan dan output apa saja yang diperlukan. Penelitian ini dilakukan untuk mengkaji model prediksi perubahan tutupan lahan dari tahun 2007 hingga 2020 di DAS Krueng Aceh. Pendekatan yang dilakukan menggunakan penginderaan jauh dan SIG. Model Markov Chain (MC) dan Artificial Neural Network-Markov (ANN-MC) digunakan untuk memahami dinamika spatio-temporal tutupan lahan. Akurasi dari citra penginderaan jauh yang diklasifikasikan diperoleh dari hasil interpretasi visual pada citra resolusi sedang Landsat OLI tahun 2020 dengan nilai Kappa Accuracy sebesar 84%. Kedua model prediksi menggunakan data tutupan lahan tahun 2007 (T1) dan 2017 (T2) untuk membuat probabilitas perubahan yang digunakan dalam memprediksi tutupan lahan pada tahun 2020 (T3). Validasi kedua algoritma menunjukkan korelasi yang kuat dengan peta tutupan lahan 2020, hal tersebut membuktikan kehandalan model kedua simulasi (ANN=87,81% dan MC=88,69%).
Kata kunci: model; ANN-Markov; prediksi tutupan lahan; Rantai Markov
Keywords
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DOI: https://doi.org/10.20886/jppdas.2021.5.2.185-206
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