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January 1, 2024Jurnal Tanah dan Sumberdaya LahanOpen Access

Pemodelan Prediksi Konversi Penggunaan Lahan Berbasis Ann-Ca Di Wilayah Peri-Urban Kabupaten Sleman

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Authors

TSTiara SarastikaYSYudhistira SaraswatiRTRiska Aprilia Triyadi

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Overview

Predictive spatial modeling reveals persistent agricultural land loss and built-up expansion in peri-urban regions, highlighting urgent needs for sustainable land-use planning.

Key Points

  • Analyze historical land use conversion between 2015 and 2020 and model predictive land use changes over a 20-year horizon from 2025 to 2045.
  • Extracted historical land use classifications from multi-temporal SPOT satellite imagery from 2015 to 2020.
  • Applied an Artificial Neural Network with multiple output neurons coupled with Cellular Automata (ANN-CA) via the MOLUSCE plugin in QGIS Desktop 2.18.11 to determine transition probabilities and simulate 2025–2045 spatial changes.
  • Between 2015 and 2020, agricultural and livestock land decreased by 152.62 ha (2.52%), while built-up land expanded by 148.74 ha (2.46%).
  • Model projections for 2025 to 2045 forecast continued conversion and decline of agricultural, plantation, and livestock areas alongside ongoing increases in land dedicated to buildings and road networks.

Cite This Study

Sarastika et al. (2024) studied this question.

synapsesocial.com/papers/6a1bdda601af05bf0da8f875https://doi.org/10.21776/ub.jtsl.2024.011.1.18
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