Prediction of Bandung District Land Use Change Using Markov Chain Modeling
N. Larson, M. N. Laska, and D. Neumark-Sztainer, “Food insecurity, diet quality, home food availability, and health risk behaviors among emerging adults: Findings from the EAT 2010–2018 study,” American Journal of Public Health, vol. 110, no. 9, pp. 1422–1428, 2020.
T. Hasegawa et al., “Risk of increased food insecurity under stringent global climate change mitigation policy,” Nature Climate Change, vol. 8, no. 8, pp. 699–703, 2018.
H. Temesgen, W. Wu, X. Shi, E. Yirsaw, B. Bekele, and M. Kindu, “Variation in ecosystem service values in an agroforestry dominated landscape in ethiopia: Implications for land use and conservation policy,” Sustainability, vol. 10, no. 4, p. 1126, 2018.
F. Handavu, P. W. C. Chirwa, and S. Syampungani, “Socio-economic factors influencing land-use and land-cover changes in the miombo woodlands of the Copperbelt province in Zambia,” Forest Policy and Economics, vol. 100, pp. 75–94, 2019.
A. P. Durán et al., “A practical approach to measuring the biodiversity impacts of land conversion,” Methods in Ecology and Evolution, vol. 11, no. 8, pp. 910–921, 2020.
A. N. Chaidar, I. Soekarno, A. Wiyono, and J. Nugroho, “Spatial analysis of erosion and land criticality of the upstream citarum watershed,” International Journal of GEOMATE, vol. 13, no. 37, pp. 133–140, 2017, doi: 10.21660//2017.37.34572.
M. I. Onwuka, “Land–use change effects on soil quality at Umudike area, Abia State, South-East Nigeria,” Nigeria Agricultural Journal, vol. 51, no. 1, pp. 109–118, 2020.
F. Raiesi, “A minimum data set and soil quality index to quantify the effect of land use conversion on soil quality and degradation in native rangelands of upland arid and semiarid regions,” Ecological Indicators, vol. 75, pp. 307–320, 2017.
P. Yu, S. Liu, H. Yang, G. Fan, and D. Zhou, “Short-term land use conversions influence the profile distribution of soil salinity and sodicity in northeastern China,” Ecological Indicators, vol. 88, pp. 79–87, 2018.
Ministry of Agriculture, Integrated Land Conservation Development Management Support. Ministry of Agriculture, 2015.
H. Wu et al., “Examining the sensitivity of spatial scale in cellular automata Markov chain simulation of land use change,” International Journal of Geographical Information Science, vol. 33, no. 5, pp. 1040–1061, 2019.
M. Zare, A. A. N. Samani, M. Mohammady, H. Salmani, and J. Bazrafshan, “Investigating effects of land use change scenarios on soil erosion using CLUE-s and RUSLE models,” International journal of environmental science and technology, vol. 14, no. 9, pp. 1905–1918, 2017.
Y. Feng and X. Tong, “Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change,” Environmental monitoring and assessment, vol. 189, no. 10, p. 515, 2017.
M. G. Munthali, S. Mustak, A. Adeola, J. Botai, S. K. Singh, and N. Davis, “Modeling land use and land cover dynamics of Dedza district of Malawi using hybrid Cellular Automata and Markov model,” Remote Sensing Applications: Society and Environment, vol. 17, p. 100276, 2020.
B. Rimal, L. Zhang, H. Keshtkar, B. N. Haack, S. Rijal, and P. Zhang, “Land use/land cover dynamics and modeling of urban land expansion by the integration of cellular automata and markov chain,” ISPRS International Journal of Geo-Information, vol. 7, no. 4, p. 154, 2018.
V. Nasiri, A. A. Darvishsefat, R. Rafiee, A. Shirvany, and M. A. Hemat, “Land use change modeling through an integrated multi-layer perceptron neural network and Markov chain analysis (case study: Arasbaran region, Iran),” Journal of Forestry Research, vol. 30, no. 3, pp. 943–957, 2019.
C. J. Geyer, “Practical markov chain monte carlo,” Statistical Science, pp. 473–483, 1992.
J. Groeneveld et al., “Theoretical foundations of human decision-making in agent-based land use models–A review,” Environmental Modeling & software, vol. 87, pp. 39–48, 2017.
M. Samardžić-Petrović, M. Kovačević, B. Bajat, and S. Dragićević, “Machine learning techniques for modeling short term land-use change,” ISPRS International Journal of Geo-Information, vol. 6, no. 12, p. 387, 2017.
C. Liping, S. Yujun, and S. Saeed, “Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China,” PloS One, vol. 13, no. 7, p. e0200493, 2018.
M. Wang, L. Cai, H. Xu, and S. Zhao, “Predicting land use changes in northern China using logistic regression, cellular automata, and a Markov model,” Arabian Journal of Geosciences, vol. 12, no. 24, p. 790, 2019.
E. Yirsaw, W. Wu, X. Shi, H. Temesgen, and B. Bekele, “Land use/land cover change modeling and the prediction of subsequent changes in ecosystem service values in a coastal area of China, the Su-Xi-Chang Region,” Sustainability, vol. 9, no. 7, p. 1204, 2017.
C. Wang, Y. Wang, R. Wang, and P. Zheng, “Modeling and evaluating land-use/land-cover change for urban planning and sustainability: a case study of Dongying city, China,” Journal of Cleaner Production, vol. 172, pp. 1529–1534, 2018.
K. Islam, M. F. Rahman, and M. Jashimuddin, “Modeling land use change using cellular automata and artificial neural network: the case of Chunati Wildlife Sanctuary, Bangladesh,” Ecological Indicators, vol. 88, pp. 439–453, 2018.
C. Hyandye and L. W. Martz, “A Markovian and cellular automata land-use change predictive model of the Usangu Catchment,” International Journal of Remote Sensing, vol. 38, no. 1, pp. 64–81, 2017.
A. K. Hua, “Application of Ca-Markov model and land use/land cover changes in Malacca River Watershed, Malaysia,” Applied Ecology and Environmental Research, vol. 15, no. 4, pp. 605–622, 2017.
E. Zadbagher, K. Becek, and S. Berberoglu, “Modeling land use/land cover change using remote sensing and geographic information systems: case study of the Seyhan Basin, Turkey,” Environmental Monitoring and Assessment, vol. 190, no. 8, p. 494, 2018.
E. Gidey, O. Dikinya, R. Sebego, E. Segosebe, and A. Zenebe, “Cellular automata and Markov Chain (CA_Markov) model-based predictions of future land use and land cover scenarios (2015–2033) in Raya, northern Ethiopia,” Modeling Earth Systems and Environment, vol. 3, no. 4, pp. 1245–1262, 2017.
Y. Trisurat, H. Shirakawa, and J. M. Johnston, “Land-use/land-cover change from socio-economic drivers and their impact on biodiversity in Nan Province, Thailand,” Sustainability, vol. 11, no. 3, p. 649, 2019.
A. M. Y. Hakim, S. Baja, D. A. Rampisela, and S. Arif, “Modeling land use/land cover changes prediction using multi-layer perceptron neural network (MLPNN): a case study in Makassar City, Indonesia,” International Journal of Environmental Studies, pp. 1–18, 2020.
E. Kusratmoko and S. D. Y. Albertus, “Modeling land use/cover changes with markov-cellular automata in Komering Watershed, South Sumatera,” in IOP Conference Series: Earth and Environmental Science, 2017, vol. 54, no. 1, p. 12103.
F. Yulianto, T. Maulana, and M. R. Khomarudin, “Analysis of the dynamics of land use change and its prediction based on the integration of remotely sensed data and CA-Markov model, in the upstream Citarum Watershed, West Java, Indonesia,” International Journal of Digital Earth, vol. 12, no. 10, pp. 1151–1176, 2019.
F. Yulianto, I. Prasasti, J. M. Pasaribu, H. L. Fitriana, N. S. Haryani, and P. Sofan, “The dynamics of land use/land cover change modeling and their implication for the flood damage assessment in the Tondano watershed, North Sulawesi, Indonesia,” Modeling Earth Systems and Environment, vol. 2, no. 1, p. 47, 2016.
M. H. Saputra and H. S. Lee, “Prediction of land use and land cover changes for north sumatra, indonesia, using an artificial-neural-network-based cellular automaton,” Sustainability, vol. 11, no. 11, p. 3024, 2019.
Central Bureau of Statistics, Bandung District in 2017. 2018.
Research Center for Development of Agricultural Land Resources, “Bintan island semi-detailed soil map at 1: 50,000 scale. Center for Agricultural Land Resources, Ministry of Agriculture, Bogor.,” 2017.
P. G. USGS, “Landsat Climate Data Record (CDR) Surface Reflectance,” US Geological Survey, version, vol. 3.
Geospasial Information Agency, “Toponym map of Bandung district scale 1:25.000,” Jakarta: Permendagri, 2015.
D. G. Altman, “Mathematics for kappa,” Practical statistics for medical research, vol. 1991, pp. 406–407, 1991.
R. G. Pontius, D. Huffaker, and K. Denman, “Useful techniques of validation for spatially explicit land-change models,” Ecological Modeling, vol. 179, no. 4, pp. 445–461, 2004.
R. Nuraeni, S. R. P. Sitorus, and D. R. Panuju, “Analisis perubahan penggunaan lahan dan arahan penggunaan lahan wilayah di Kabupaten Bandung,” Buletin Tanah dan Lahan, vol. 1, no. 1, pp. 79–85, 2017.
J. Han, Y. Hayashi, X. Cao, and H. Imura, “Evaluating land-use change in rapidly urbanizing China: Case study of Shanghai,” Journal of Urban Planning and Development, vol. 135, no. 4, pp. 166–171, 2009.
B. Susilo, “Pemodelan Spasial Probabilistik Integrasi Markov Chain dan Cellular Automata untuk Kajian Perubahan Penggunaan Lahan Skala Regional di Provinsi Daerah Istimewa Yogyakarta,” Jurnal Geografi Gea, vol. 11, no. 2, 2011.
B.-J. Fu et al., “Temporal change in land use and its relationship to slope degree and soil type in a small catchment on the Loess Plateau of China,” Catena, vol. 65, no. 1, pp. 41–48, 2006.
A. Ruswandi, E. Rustiadi, and K. Mudikdjo, “Dampak konversi lahan pertanian terhadap kesejahteraan petani dan perkembangan wilayah: studi kasus di daerah Bandung Utara,” Jurnal Agro Ekonomi, vol. 25, no. 2, pp. 207–219, 2016.
E. F. Lambin and P. Meyfroidt, “Land use transitions: Socio-ecological feedback versus socio-economic change,” Land Use Policy, vol. 27, no. 2, pp. 108–118, 2010.
T. Yuan, X. Yiping, Z. Lei, and L. Danqing, “Land use and cover change simulation and prediction in Hangzhou city based on CA-Markov model,” International Proceedings of Chemical. Biol. Environ. Eng, vol. 90, pp. 108–113, 2015.
- There are currently no refbacks.
Published by INSIGHT - Indonesian Society for Knowledge and Human Development