Prediction and Simulation of Land Use and Land Cover Changes Using Open Source QGIS. A Case Study of Purwokerto, Central Java, Indonesia

https://doi.org/10.22146/ijg.68702

Gian Felix Ramadhan(1), Iswari Nur Hidayati(2*)

(1) Department of Geographic Information Science, Faculty of Geography, Universitas Gadjah Mada, Bulaksumur, Yogyakarta
(2) Department of Geographic Information Science, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta
(*) Corresponding Author

Abstract


Population size multiplies along with the increasing need for residential space. As often occurs in developing cities like Purwokerto, population growth is associated with land use/land cover (LULC) change to accommodate housing demand both in the present and future. Therefore, this study was intended to map LULC changes in three different years: 2008, 2013, and 2018, and predict the change in 2023. For LULC data extraction, a pixel-based digital classification with a maximum likelihood algorithm was applied to Landsat images. In addition, the LULC change prediction was modeled with Modules for Land Use Change Simulations (MOLUSCE) from the QGIS plugins. It used two algorithms: artificial neural network (ANN) with a multilayer perceptron (MLP) and cellular automata (CA). The LULC classifications for 2008, 2013, and 2018 were 88%, 86%, and 88% accurate, while the prediction was 75.26% accurate, with a kappa of 0.634. Predictions and simulations indicate fluctuations in LULC change in the City of Purwokerto periodically, especially for built-up land, showing growth that continues to increase significantly.


Keywords


LULC Change; Maximum Likelihood; LULC Prediction

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References

Al-Rubkhi, ANM. (2017). ‘Land Use Change Analysis and Modeling Using Open Source (QGIS) Case Study: Boasher Wilayat. Dissertation. Department of Geography. Sultan Qaboos University Oman.

Anderson, J. R. (1971). Land Use Classification Schemes Used in Selected Recent Geographic Applications of Remote Sensing. Photogrammetric Engineering, 37(4), 379 - 387.

Banyumas Regency Regional Regulation Number 10 of 2013 concerning the Medium-Term Regional Development Plan (RPJMD) of Banyumas Regency 2013-2018.

Banyumas Regency Regional Regulation Number 24 of 2009 concerning the Medium-Term Regional Development Plan (RPJMD) of Banyumas Regency for 2008-2013.

Banyumas Regency Regional Regulation Number 7 of 2009 concering the Long-Term Regional Development Plan (RPJP) of Banyumas Regency for 2005-2025.

Badan Pusat Statistik (BPS) Kabupaten Banyumas. (2009). Kabupaten Banyumas dalam Angka 2008. Purwokerto: Badan Pusat Statistik Kabupaten Banyumas.

Badan Pusat Statistik (BPS) Kabupaten Banyumas. (2019). Kabupaten Banyumas dalam Angka 2018. Purwokerto: Badan Pusat Statistik Kabupaten Banyumas.

Cohen, J. (1960). A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement, 60, 27-46.

Danoedoro, P. (2012). Pengantar Penginderaan Jauh Digital. Yogyakarta: C. V. ANDI OFFSET.

Hakim, A. Y., Baja, S., Rampisela, D. A., & Arif, S. (2019). Spatial dynamic prediction of landuse / landcover change (case study: Tamalanrea Sub-District, Makassar City). The 4th International Conference of Indonesian Society for Remote Sensing, 1-8.

Halefom, A., Teshome, A., Sisay, E., & Ahmad, I. (2018). Dynamics of land use and land cover change using remote sensing and GIS: a case study of Debre Tabor Town, South Gondar, Ethiopia. Journal of Geographic Information System, 10(02), 165.

Hoffer, R. M. (1984). The Role of Terrestrial Vegetation in the Global Carbon Cycle: Measurement by Remote Sensing, Chapter 5: Remote Sensing to Measure the Distribution and Structure of Vegetation (131-159). New York: John Wiley & Sons Ltd.

Indonesian National Standard (SNI) of the National Standardization Agency (BSN) Number 7645-1:2014 Regarding Classification of Small and Medium Scale Land Covers.

Jensen, John R. (2015). Introductory Digital Image Processing a Remote Sensing Perspective 4 Edition. South Carolina: Pearson Education.

Kafy, A. A., Rahman, M. S., Faisal, A. A., Hasan, M. M., & Islam, M. (2020). Modelling future land use land cover changes and their impacts on land surface temperatures in Rajshahi, Bangladesh. Remote Sensing Applications: Society and Environment, 1-18.

Kaswanto, R. L., Aurora, R. M., Yusri, D., & Sjaf, S. (2021). Analisis Faktor Pendorong Perubahan Tutupan Lahan selama Satu Dekade di Kabupaten Labuhanbatu Utara. Journal Ilmu Lingkungan, 19(1), 107-116.

Liu, C., Li, W., Zhu, G., Zhou, H., Yan, H., & Xue, P. (2020). Land use/land cover changes and their driving factors in the Northeastern Tibetan Plateau based on Geographical Detectors and Google Earth Engine: A case study in Gannan Prefecture. Remote Sensing, 12(19), 3139.

Manson, M. S. (2001). Integrated Assessment and Projection of Landuse/ Landcover Change in the Southern Yucatan Peninsular of Mexico. Report and Review of an International Workshop, 56-88.

Muhammad, R., Zhang, W., Abbas, Z., Guo, F., & Gwiazdzinski, L. (2022). Spatiotemporal Change Analysis and Prediction of Future Land Use and Land Cover Changes Using QGIS MOLUSCE Plugin and Remote Sensing Big Data: A Case Study of Linyi, China. Land, 11(3), 419.

Munggiarti, A., & Buchori, I. (2015). Pengaruh Keberadaan Perguruan Tinggi terhadap Perubahan Morfologi Kawasan Sekitarnya. Journal of Geomatics and Planning, Vol 2, No. 1. 51-68.

Radar Banyumas. (2020). Accessed on December 24, 2020. https://radarbanyumas.co.id/plan-pemekaran-kabupaten-banyumas-kota-purwokerto-kabupaten-banyumas-dan-kabupaten-banyumas-barat/.

Ramadhani, F., & Susilo, B. (2016). Integration of Remote Sensing and Geographic Information Systems for Prioritizing Evacuation Route Improvements in Merapi Eruption Prone Areas (Pakem and Cangkringan Sub-districts). Jurnal Bumi Indonesia, 5(4)

Regional Infrastructure Development Agency. (2017). Accessed on July 1, 2022. http://perkotaan.bpiw.pu.go.id/n/sistem-perkotaan-nasional/kota-autonom.

Saputra, R. (2020). Object and Pixel-Based Land Cover Study in the Mangrove Area of Dompak Island, Riau Archipelago Province. Doctoral Dissertation, IPB University

U. S. Geological Survey. (2019). Landsat 8 (L8) Data Users Handbook. South Dakota: EROS.

Wibowo, A. (2014). Study on Urban Structure and Transportation System in Purwokerto City in 2013. Geoedukasi Volume III Nomor 1, 68-76.



DOI: https://doi.org/10.22146/ijg.68702

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