Journal of Multidisciplinary Applied Natural Science
##plugins.themes.gdThemes.journalSlogan##
Scopus CiteScore 2025
2.1
Calculated on 05 May, 2025
SJR 2025
0.25
Powered by scimagojr.com
##plugins.themes.gdThemes.journalSlogan##
2.1
Calculated on 05 May, 2025
0.25
Powered by scimagojr.com
https://doi.org/10.47352/jmans.2774-3047.447
Katawut Waiyasusri
Nanthaporn Usaard
Dolreucha Suwanmajo
Ao Nang, a coastal tourist city in Krabi Province, has been developing its area to support both Thai and foreign tourists since 1983. This research selected Landsat 1 satellite imagery from 1973, which was before tourism development, to conduct this research. The objective of this research is to analyze the changes in land use patterns between 1973 and 2025, and to model future land use using the CA-Markov model in Ao Nang. The results found that in 1973, the city, town, and commercial areas covered an area of 9.38 km2 (7.82% of the total area), and in 2025, the area increased to 21.95 km2 (18.31% of the total area). Urban expansion has affected other types of land use, such as evergreen forest and various agricultural areas, such as para rubber and mixed orchard. During 1973–2025, urbanization has occurred in important beach areas, such as Nopparat Thara Beach, Ao Nang Beach, Railay Beach, Tubkaek Beach, and Khlong Muang Beach; and important highways along the line, such as 4201, 4203, 4034, and 6024. The results of the Cellular Automata Markov Model (CA-Markov Model) show the simulation of future land use, which occurs in 2050. The CA-Markov model predicts that urban and built-up areas will expand significantly to 40.32 km2 by 2050, representing an 83.7% increase from the baseline. Conversely, forest cover and agricultural land are projected to decline by 18.78% and 12.72%, respectively. The results show that in the next 25 years, the city, town, and commercial areas will expand the most, followed by shrimp farms. If land use changes occur without control, it may affect the use of such land to increase rapidly. However, the research results this time have shown land use data in spatial form that is useful for planning land use development in the coastal tourist city of Ao Nang effectively. Furthermore, this information will support decision-making in preparing for spatial development for sustainable tourism.
[1] Y. Yu, Y. Shen, J. Wang, Y. Wei, L. Nong, and H. Deng. (2021). "Assessing the Response of Vegetation Change to Drought During 2009-2018 in Yunnan Province, China". Environmental Science and Pollution Research. 28 : 47066-47082. 10.1007/s11356-021-13835-4.
DOI: https://doi.org/10.1007/s11356-021-13835-4[2] J. Ma, J. Wang, S. He, J. Zhang, L. Liu, and X. Zhong. (2024). "Direct and Indirect Effects of Urbanization on Vegetation: A Survey of Yunnan Central Urban Economic Circle, China". Ecological Indicators. 166 : 112536. 10.1016/j.ecolind.2024.112536.
DOI: https://doi.org/10.1016/j.ecolind.2024.112536[3] Y. Liu, Y. Xue, H. Zhao, H. Yao, X. Zhan, S. Suk, L. Wang, and Y. Yuan. (2025). "Coupling Coordination and Spatiotemporal Dynamic Evolution Between Culture and Tourism Industry in Japan". Scientific Reports. 15 (1): 7777. 10.1038/s41598-025-88515-1.
DOI: https://doi.org/10.1038/s41598-025-88515-1[4] A. Ansari and M. H. Golabi. (2019). "Prediction of Spatial Land Use Changes Based on LCM in a GIS Environment for Desert Wetlands: A Case Study of Meighan Wetland, Iran". International Soil and Water Conservation Research. 7 (1): 64-70. 10.1016/j.iswcr.2018.10.001.
DOI: https://doi.org/10.1016/j.iswcr.2018.10.001[5] B. S. Wiwoho, N. McIntyre, and S. Phinn. (2024). "Assessing Future Land Uses Under Planning Scenarios: A Case Study of the Brantas River Basin, Indonesia". Environmental Challenges. 15 : 100873. 10.1016/j.envc.2024.100873.
DOI: https://doi.org/10.1016/j.envc.2024.100873[6] D. Mustelier and C. Henríquez. (2024). "Modeling Land Use Change of Mid-Sized Cities in the Process of Metropolization: Case Study La Serena-Coquimbo Conurbation, Chile". Geography, Environment, Sustainability. 17 (2): 106-118. 10.24057/2071-9388-2024-2984.
DOI: https://doi.org/10.24057/2071-9388-2024-2984[7] Y. Huang and Q. Xue. (2024). "Spatio-Temporal Distribution Characteristics and Driving Factors of Traditional Villages in the Yellow River Basin". PLOS ONE. 19 (5): e0303396. 10.1371/journal.pone.0303396.
DOI: https://doi.org/10.1371/journal.pone.0303396[8] K. Waiyasusri, R. Vangpaisal, and S. Chotpantarat. (2024). "Climate and Land Use Change Impacts on Groundwater Recharge in Prachinburi-Sakaeo Groundwater Basin by Integrating the CA-Markov Model with the WetSpass Model". Earth Systems and Environment. 8 (4): 1179-1206. 10.1007/s41748-024-00436-7.
DOI: https://doi.org/10.1007/s41748-024-00436-7[9] N. A. Veridiano-de Castro, K. J. Almadrones-Reyes, J. C. Redeña-Santos, J. E. Limbo-Dizon, and N. H. A. Dagamac. (2024). "Applying Geomatic Analyses Using Landsat Imagery: Implications for Ecosystem Management in Occidental Mindoro, Philippines". GeoJournal. 89 (5): 229. 10.1007/s10708-024-11215-2.
DOI: https://doi.org/10.1007/s10708-024-11215-2[10] N. Z. Zhensikbayeva, G. Abiyeva, B. T. Sabyrbayeva, G. A. Avgusthanova, N. K. Kabdrakhmanova, and N. Amangeldy. (2024). "Studying the Development Potential of Tourism Industries in the South Altai by Hydrological, Climatic, Geomorphological Way and Visualization Using GIS". GeoJournal of Tourism and Geosites. 53 (2): 528-537. 10.30892/gtg.53216-1228.
DOI: https://doi.org/10.30892/gtg.53216-1228[11] H. Nguyen-Quoc, H. H. Thi-Viet, and P. Phan-Van. (2025). "Monitoring Forest Changes in Lowland Hilly Terrain of the Central Highlands of Vietnam Using Landsat Satellite Imagery: A Case Study in Dak Nong Province". Ecological Engineering and Environmental Technology. 26 (4). 10.12912/27197050/201330.
DOI: https://doi.org/10.12912/27197050/201330[12] B. B. Thien, V. T. Phuong, and A. R. Ioshpa. (2025). "Assessing the Environmental Destruction in Forest Cover Using Landscape Metrics and Spatial Analysis in Quang Nam Province, Vietnam". Environmental Earth Sciences. 84 (13): 1-22. 10.1007/s12665-025-12377-z.
DOI: https://doi.org/10.1007/s12665-025-12377-z[13] Y. An, J. Y. Tsou, K. Wong, Y. Zhang, D. Liu, and Y. Li. (2018). "Detecting Land Use Changes in a Rapidly Developing City During 1990-2017 Using Satellite Imagery: A Case Study in Hangzhou Urban Area, China". Sustainability. 10 (9): 3303. 10.3390/su10093303.
DOI: https://doi.org/10.3390/su10093303[14] M. Yılmaz and F. Terzi. (2020). "Characteristics of Spatio-Temporal Urban Growth Patterns Due to the Driving Forces of Urbanization: The Coastal City of Antalya, Turkey". International Review for Spatial Planning and Sustainable Development. 8 (3): 16-33. 10.14246/irspsd.8.3_16.
DOI: https://doi.org/10.14246/irspsd.8.3_16[15] M. Ranagalage, T. Morimoto, M. Simwanda, and Y. Murayama. (2021). "Spatial Analysis of Urbanization Patterns in Four Rapidly Growing South Asian Cities Using Sentinel-2 Data". Remote Sensing. 13 (8): 1531. 10.3390/rs13081531.
DOI: https://doi.org/10.3390/rs13081531[16] A. Lagarias and A. Stratigea. (2023). "Coastalization Patterns in the Mediterranean: A Spatiotemporal Analysis of Coastal Urban Sprawl in Tourism Destination Areas". GeoJournal. 88 (3): 2529-2552. 10.1007/s10708-022-10756-8.
DOI: https://doi.org/10.1007/s10708-022-10756-8[17] Y. Huang, T. Chen, D. Hu, T. Lin, W. Zhu, G. Zhang, and X. Xue. (2023). "Spatiotemporal Patterns and Influencing Factors of Urban Ecological Space Availability in Coastal Cities of China During Rapid Urbanization". Ecological Indicators. 154 : 110757. 10.1016/j.ecolind.2023.110757.
DOI: https://doi.org/10.1016/j.ecolind.2023.110757[18] B. Dahy, M. Al-Memari, A. Al-Gergawi, and J. A. Burt. (2024). "Remote Sensing of 50 Years of Coastal Urbanization and Environmental Change in the Arabian Gulf: A Systematic Review". Frontiers in Remote Sensing. 5 : 1422910. 10.3389/frsen.2024.1422910.
DOI: https://doi.org/10.3389/frsen.2024.1422910[19] S. Saadani, R. Laajaj, M. Maanan, H. Rhinane, and A. Aaroud. (2020). "Simulating Spatial-Temporal Urban Growth of a Moroccan Metropolitan Using CA-Markov Model". Spatial Information Research. 28 : 609-621. 10.1007/s41324-020-00322-0.
DOI: https://doi.org/10.1007/s41324-020-00322-0[20] L. Zhu, R. Song, S. Sun, Y. Li, and K. Hu. (2022). "Land Use/Land Cover Change and Its Impact on Ecosystem Carbon Storage in Coastal Areas of China from 1980 to 2050". Ecological Indicators. 142 : 109178. 10.1016/j.ecolind.2022.109178.
DOI: https://doi.org/10.1016/j.ecolind.2022.109178[21] L. Lu, S. Qureshi, Q. Li, F. Chen, and L. Shu. (2022). "Monitoring and Projecting Sustainable Transitions in Urban Land Use Using Remote Sensing and Scenario-Based Modelling in a Coastal Megacity". Ocean and Coastal Management. 224 : 106201. 10.1016/j.ocecoaman.2022.106201.
DOI: https://doi.org/10.1016/j.ocecoaman.2022.106201[22] C. E. Dumdumaya and J. S. Cabrera. (2023). "Determination of Future Land Use Changes Using Remote Sensing Imagery and Artificial Neural Network Algorithm: A Case Study of Davao City, Philippines". Artificial Intelligence in Geosciences. 4 : 111-118. 10.1016/j.aiig.2023.08.002.
DOI: https://doi.org/10.1016/j.aiig.2023.08.002[23] P. Pongsakornrungsilp and S. Pongsakornrungsilp. (2023). "Mindful Tourism: Nothing Left Behind-Creating a Circular Economy Society for the Tourism Industry of Krabi, Thailand". Journal of Tourism Futures. 9 (3): 366-380. 10.1108/JTF-01-2021-0001.
DOI: https://doi.org/10.1108/JTF-01-2021-0001[24] P. Pongsakornrungsilp, S. Pongsakornrungsilp, A. Jansom, and S. Chinchanachokchai. (2022). "Rethinking Sustainable Tourism Management: Learning from the COVID-19 Pandemic to Co-Create the Future of Krabi Tourism, Thailand". Sustainability. 14 (18): 11375. 10.3390/su141811375.
DOI: https://doi.org/10.3390/su141811375[25] F. Koch and K. Krellenberg. (2018). "How to Contextualize SDG 11? Looking at Indicators for Sustainable Urban Development in Germany". ISPRS International Journal of Geo-Information. 7 (12): 464. 10.3390/ijgi7120464.
DOI: https://doi.org/10.3390/ijgi7120464[26] M. Al-Raeei. (2024). "Artificial Intelligence for Climate Resilience: Advancing Sustainable Goals in SDGs 11 and 13 and Its Relationship to Pandemics". Discover Sustainability. 5 (1): 513. 10.1007/s43621-024-00775-5.
DOI: https://doi.org/10.1007/s43621-024-00775-5[27] S. Liu, J. Bai, and J. Chen. (2019). "Measuring SDG 15 at the County Scale: Localization and Practice of SDGs Indicators Based on Geospatial Information". ISPRS International Journal of Geo-Information. 8 (11): 515. 10.3390/ijgi8110515.
DOI: https://doi.org/10.3390/ijgi8110515[28] K. Peng, W. Jiang, Z. Ling, P. Hou, and Y. Deng. (2021). "Evaluating the Potential Impacts of Land Use Changes on Ecosystem Service Value Under Multiple Scenarios in Support of SDG Reporting: A Case Study of the Wuhan Urban Agglomeration". Journal of Cleaner Production. 307 : 127321. 10.1016/j.jclepro.2021.127321.
DOI: https://doi.org/10.1016/j.jclepro.2021.127321[29] G. Zhang, T. Yao, H. Xie, K. Zhang, and F. Zhu. (2014). "Lakes' State and Abundance Across the Tibetan Plateau". Chinese Science Bulletin. 59 : 3010-3021. 10.1007/s11434-014-0258-x.
DOI: https://doi.org/10.1007/s11434-014-0258-x[30] T. D. H. Le and L. T. Vinh. (2025). "Applying Random Forest and Support Vector Machine for Land-Use Classification in Phu Giao District, Vietnam". Applied Environmental Research. 47 (2): 016. 10.35762/AER.2025016.
[31] V. F. Sales, D. C. Zanotta, A. Marques Jr, G. Racolte, M. Muller, C. L. Cazarin, D. Ibanez, L. Gonzaga Jr, and M. R. Veronez. (2023). "An Adaptive Spectral Index for Carbonate Rocks Using OLI Landsat-8 Imagery". Geocarto International. 38 (1): 2179671. 10.1080/10106049.2023.2179671.
DOI: https://doi.org/10.1080/10106049.2023.2179671[32] Y. Du, P. M. Teillet, and J. Cihlar. (2002). "Radiometric Normalization of Multitemporal High-Resolution Satellite Images with Quality Control for Land Cover Change Detection". Remote Sensing of Environment. 82 (1): 123-134. 10.1016/S0034-4257(02)00029-9.
DOI: https://doi.org/10.1016/S0034-4257(02)00029-9[33] S. Hantson and E. Chuvieco. (2011). "Evaluation of Different Topographic Correction Methods for Landsat Imagery". International Journal of Applied Earth Observation and Geoinformation. 13 (5): 691-700. 10.1016/j.jag.2011.05.001.
DOI: https://doi.org/10.1016/j.jag.2011.05.001[34] K. Phinzi, N. S. Ngetar, Q. B. Pham, G. G. Chakilu, and S. Szabó. (2023). "Understanding the Role of Training Sample Size in the Uncertainty of High-Resolution LULC Mapping Using Random Forest". Earth Science Informatics. 16 (4): 3667-3677. 10.1007/s12145-023-01117-1.
DOI: https://doi.org/10.1007/s12145-023-01117-1[35] V. F. Rodriguez-Galiano, B. Ghimire, J. Rogan, M. Chica-Olmo, and J. P. Rigol-Sanchez. (2012). "An Assessment of the Effectiveness of a Random Forest Classifier for Land-Cover Classification". ISPRS Journal of Photogrammetry and Remote Sensing. 67 : 93-104. 10.1016/j.isprsjprs.2011.11.002.
DOI: https://doi.org/10.1016/j.isprsjprs.2011.11.002[36] C. Avci, M. Budak, N. Yağmur, and F. Balçık. (2023). "Comparison Between Random Forest and Support Vector Machine Algorithms for LULC Classification". International Journal of Engineering and Geosciences. 8 (1): 1-10. 10.26833/ijeg.987605.
DOI: https://doi.org/10.26833/ijeg.987605[37] A. A. Jamali, A. Behnam, S. A. Almodaresi, S. He, and A. Jaafari. (2024). "Exploring Factors Influencing Urban Sprawl and Land-Use Changes Analysis Using Systematic Points and Random Forest Classification". Environment, Development and Sustainability. 26 (5): 13557-13576. 10.1007/s10668-023-03633-y.
DOI: https://doi.org/10.1007/s10668-023-03633-y[38] G. M. Foody. (2020). "Explaining the Unsuitability of the Kappa Coefficient in the Assessment and Comparison of the Accuracy of Thematic Maps Obtained by Image Classification". Remote Sensing of Environment. 239 : 111630. 10.1016/j.rse.2019.111630.
DOI: https://doi.org/10.1016/j.rse.2019.111630[39] F. Chaaban, J. El Khattabi, and H. Darwishe. (2022). "Accuracy Assessment of ESA WorldCover 2020 and ESRI 2020 Land Cover Maps for a Region in Syria". Journal of Geovisualization and Spatial Analysis. 6 (2): 31. 10.1007/s41651-022-00126-w.
DOI: https://doi.org/10.1007/s41651-022-00126-w[40] K. Jia, S. Liang, L. Zhang, X. Wei, Y. Yao, and X. Xie. (2014). "Forest Cover Classification Using Landsat ETM+ Data and Time Series MODIS NDVI Data". International Journal of Applied Earth Observation and Geoinformation. 33 : 32-38. 10.1016/j.jag.2014.04.015.
DOI: https://doi.org/10.1016/j.jag.2014.04.015[41] D. Guan, H. Li, T. Inohae, W. Su, T. Nagaie, and K. Hokao. (2011). "Modeling Urban Land Use Change by the Integration of Cellular Automaton and Markov Model". Ecological Modelling. 222 (20-22): 3761-3772. 10.1016/j.ecolmodel.2011.09.009.
DOI: https://doi.org/10.1016/j.ecolmodel.2011.09.009[42] M. Jafari, H. Majedi, S. M. Monavari, A. A. Alesheikh, and M. K. Zarkesh. (2016). "Dynamic Simulation of Urban Expansion Through a CA-Markov Model: Case Study of the Hyrcanian Region, Gilan, Iran". European Journal of Remote Sensing. 49 (1): 513-529. 10.5721/EuJRS20164927.
DOI: https://doi.org/10.5721/EuJRS20164927[43] C. Xu, X. Hu, Z. Liu, X. Wang, J. Tian, and Z. Zhao. (2023). "Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA-Markov Model in an Arid Region of Northwest China". Sustainability. 15 (2): 1269. 10.3390/su15021269.
DOI: https://doi.org/10.3390/su15021269[44] S. Adhikari and J. Southworth. (2012). "Simulating Forest Cover Changes of Bannerghatta National Park Based on a CA-Markov Model: A Remote Sensing Approach". Remote Sensing. 4 (10): 3215-3243. 10.3390/rs4103215.
DOI: https://doi.org/10.3390/rs4103215[45] A. Butt, R. Shabbir, S. S. Ahmad, and N. Aziz. (2015). "Land Use Change Mapping and Analysis Using Remote Sensing and GIS: A Case Study of Simly Watershed, Islamabad, Pakistan". The Egyptian Journal of Remote Sensing and Space Science. 18 (2): 251-259. 10.1016/j.ejrs.2015.07.003.
DOI: https://doi.org/10.1016/j.ejrs.2015.07.003[46] M. Mohajane, A. Essahlaoui, F. Oudija, E. Hafyani, A. Hmaidi, E. A. Ouali, G. Randazzo, and A. C. Teodoro. (2018). "Land Use/Land Cover (LULC) Using Landsat Data Series (MSS, TM, ETM+, and OLI) in Azrou Forest, in the Central Middle Atlas of Morocco". Environments. 5 (12): 131. 10.3390/environments5120131.
DOI: https://doi.org/10.3390/environments5120131[47] C. Qian, H. Qiang, C. Qin, Z. Wang, and M. Li. (2022). "Spatiotemporal Evolution Analysis and Future Scenario Prediction of Rocky Desertification in a Subtropical Karst Region". Remote Sensing. 14 (2): 292. 10.3390/rs14020292.
DOI: https://doi.org/10.3390/rs14020292[48] Z. Zhang, B. Hu, W. Jiang, and H. Qiu. (2021). "Identification and Scenario Prediction of Degree of Wetland Damage in Guangxi Based on the CA-Markov Model". Ecological Indicators. 127 : 107764. 10.1016/j.ecolind.2021.107764.
DOI: https://doi.org/10.1016/j.ecolind.2021.107764[49] B. Matlhodi, P. K. Kenabatho, B. P. Parida, and J. G. Maphanyane. (2021). "Analysis of Future Land Use Land Cover Changes in the Gaborone Dam Catchment Using CA-Markov Model: Implications on Water Resources". Remote Sensing. 13 (13): 2427. 10.3390/rs13132427.
DOI: https://doi.org/10.3390/rs13132427[50] F. Fu, S. Deng, D. Wu, W. Liu, and Z. Bai. (2022). "Research on the Spatiotemporal Evolution of Land Use Landscape Pattern in a County Area Based on CA-Markov Model". Sustainable Cities and Society. 80 : 103760. 10.1016/j.scs.2022.103760.
DOI: https://doi.org/10.1016/j.scs.2022.103760[51] I. Atef, W. Ahmed, and R. H. Abdel-Maguid. (2024). "Future Land Use Land Cover Changes in El-Fayoum Governorate: A Simulation Study Using Satellite Data and CA-Markov Model". Stochastic Environmental Research and Risk Assessment. 38 (2): 651-664. 10.1007/s00477-023-02592-0.
DOI: https://doi.org/10.1007/s00477-023-02592-0[52] Y. Cui, R. Zhao, L. Jiang, X. Duan, M. Xiao, Z. Liu, L. Wang, X. Duan, and S. Teerarojanarat. (2025). "What Drives Nighttime Tourism Intensity in Thailand? Evidence from Thai Attractions Based on Satellite Observations". IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18 : 6086-6095. 10.1109/JSTARS.2025.3535790.
DOI: https://doi.org/10.1109/JSTARS.2025.3535790[53] N. Kaswiset, P. Panklang, P. Thaler, G. Le Maire, and A. Thoumazeau. (2026). "Oil Palm Spreads, but Rubber Still There—Mapping the Continuous but Slow Changes of Plantation Areas in Southern Thailand". Regional Environmental Change. 26 : 24. 10.1007/s10113-026-02524-y.
DOI: https://doi.org/10.1007/s10113-026-02524-y