Quantitative Approach for Complementary Analysis of a Touristic Coastal Landscape: The Case of Erdemli (Mersin), Turkey

Abstract

Abstract: Coastal landscapes face increasing demands for space and the resources that they support. These demands generally conflict with each other and with the functioning of landscape systems. Owing to the fact that landscapes of interest on the coast are complex, multifaceted quantitative analysis is highly necessary to understand biophysical variations in space and time resulting from natural and/or human-induced processes. This complexity of landscape systems requires analytical procedures that involve utilization of state-of-the-art tools and methodologies to collect and combine landscape-level environmental information for use in landscape planning, design and management. In this respect, five consecutive steps may be described for complementary analysis of landscapes: (1) dataset selection (2) land cover mapping, (3) analysis of patterns, (4) analysis of processes and (5) future projections. Recently completed research project in a coastal region on Turkish Mediterranean coast (TUBITAK Grant No: 111Y253) provided a framework for comprehensive analysis of coastal landscapes. This paper provides a brief summary of the outcomes from this project. Quantitative analysis procedures were highlighted and discussions were made in the light of analysis results. Abstract: Kıyı peyzajları, yer ve kaynaklar üzerindeki artan taleplerle karşı karşıyadır. Bu talepler genellikle birbiriyle ve peyzaj sistemlerinin işleyişi ile çelişmektedir. Kıyıdaki peyzajlar karmaşık olduğundan, insan kaynaklı ve doğal süreçlerden kaynaklanan, mekansal ve zamansal biyofiziksel değişkenliğin anlaşılması için çok yönlü sayısal analizler son derece gereklidir. Peyzaj sistemlerinin bu karmaşıklığı, peyzaj planlaması, tasarımı ve yönetiminde kullanılacak peyzaj düzeyindeki çevresel bilginin toplanması ve birleştirilmesi için en yeni araç ve yöntemlerin kullanımını içeren çözümlemeli süreçlere gereksinim duyar. Bu kapsamda peyzajların tamamlayıcı analizi için birbirini izleyen beş aşama: (1) veri seçimi, (2) araz, örtüsü haritalama, (3) patern analizleri, (4) süreç analizleri ve (5) gelecek kestirimleri olarak tanımlanabilir. Türkiye’nin Akdeniz kıyı bölgesinde yakın zamanda tamamlanmış olan bir araştırma projesi (TÜBİTAK Destek No: 111Y253) kıyı peyzajlarının bütüncül analizi için bütüncül bir çerçeve sunmuştur. Bu makale, sözkonusu projenin çıktılarının bir özetini içermektedir. Sayısal analize vurgu yapılmış ve araştırma sonuçları ışığında tartışmalar yapılmıştır. Anahtar Kelimeler: Peyzaj, kıyı zonu, Türkiye, Akdeniz, sayısal analiz

Keywords

• Landscape,coastal zone,Turkey,Mediterranean,Quantitative analysis

References

1. Aburas, M. M., Ho, Y. M., Ramli, M. F., & Ash'aari, Z. H. (2017). Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio. International Journal of Applied Earth Observation and Geoinformation, 59, 65-78.
2. Adhikari, S., & Southworth, J. (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.
3. Aguejdad, R., Doukari, O., Houet, T., Avner, P., & Viguie, V. (2016). Urban sprawl and geoprospective : advantages and drawbacks of spatial models. Application to the SLEUTH, LCM and NEDUM-2D models. Cybergeo-European Journal of Geography.
4. Aguilar, J. A. P., Ano, C., Valera, A., & Sanchez, J. (2006). Urban growth dynamics (1956-1998) in Mediterranean coastal regions: The case of Alicante, Spain. Desertification in the Mediterranean Region. A Security Issue, 3, 325-+.
5. Akin, A., Berberoglu, S., Erdogan, M. A., & Donmez, C. (2012). Modelling Land-Use Change Dynamics in a Mediterranean Coastal Wetland Using Ca-Markov Chain Analysis. Fresenius Environmental Bulletin, 21(2a), 386-396.
6. Al-Ruzouq, R., & Shanableh, A. (2014). Multi-Temporal Satellite Imagery for Urban Expansion Assessment at Sharjah City/UAE. 7th Igrsm International Remote Sensing & Gis Conference and Exhibition, 20.
7. Al-sharif, A. A. A., & Pradhan, B. (2014). Monitoring and predicting land use change in Tripoli Metropolitan City using an integrated Markov chain and cellular automata models in GIS. Arabian Journal of Geosciences, 7(10), 4291-4301.
8. Alexakis, D. D., Koutroulis, A., Gryllakis, M., Agapiou, A., Themistocleous, K., Tsanis, I., & Hadjimitsis, D. G. (2013). Using spatio - temporal Markov model for flood mapping: the case study of Yialias river in Cyprus. Remote Sensing for Agriculture, Ecosystems, and Hydrology Xv, 8887.

9. Aliani, H., Malmir, M., Sourodi, M., & Kafaky, S. B. (2019). Change detection and prediction of urban land use changes by CA-Markov model (case study: Talesh County). Environmental Earth Sciences, 78(17).
10. Alphan, H. (2003). Land-use change and urbanization of Adana, Turkey. Land Degradation & Development, 14(6), 575-586.
11. Alphan, H. (2005). Perceptions of coastline changes in river deltas: southeast Mediterranean coast of Turkey. International Journal of Environment and Pollution, 23(1), 92-102.
12. Alphan, H. (2011). Comparing the utility of image algebra operations for characterizing landscape changes: The case of the Mediterranean coast. Journal of Environmental Management, 92(11), 2961-2971.
13. Alphan, H. (2013). Bi-Temporal Analysis of Landscape Changes in the Easternmost Mediterranean Deltas Using Binary and Classified Change Information. Environmental Management, 51(3), 541-554.
14. Alphan, H. (2017). Analysis of landscape changes as an indicator for environmental monitoring. Environmental Monitoring and Assessment, 189(1).
15. Alphan, H., & Celik, N. (2016). Monitoring changes in landscape pattern: use of Ikonos and Quickbird images. Environmental Monitoring and Assessment, 188(2).
16. Alphan, H., & Derse, M. A. (2013). Change Detection in Southern Turkey Using Normalized Difference Vegetation Index (Ndvi). Journal of Environmental Engineering and Landscape Management, 21(1), 12-18.
17. Alphan, H., Doygun, H., & Unlukaplan, Y. I. (2009). Post-classification comparison of land cover using multitemporal Landsat and ASTER imagery: the case of Kahramanmara angstrom, Turkey. Environmental Monitoring and Assessment, 151(1-4), 327-336.
18. Alphan, H., & Guvensoy, L. (2016). Detecting Coastal Urbanization and Land Use Change in Southern Turkey. Journal of Environmental Engineering and Landscape Management, 24(2), 97-107.
19. Alphan, H., & Yilmaz, K. T. (2005). Monitoring environmental changes in the Mediterranean coastal landscape: The case of Cukurova, Turkey. Environmental Management, 35(5), 607-619.
20. Arsanjani, J. J., Helbich, M., Kainz, W., & Boloorani, A. D. (2013). Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. International Journal of Applied Earth Observation and Geoinformation, 21, 265-275.
21. Ayad, Y. A. (2005). Remote sensing and GIS in modeling visual landscape change: a case study of the northwestern and coast of Egypt. Landscape and Urban Planning, 73(4), 307-325.
22. Ayazli, I. E., & Bilen, O. (2019). Using Exploratory Factor Analysis to Improve the Calibration of Sleuth Urban Growth Models. Fresenius Environmental Bulletin, 28(2), 975-979.
23. Azizi, A., Malakmohamadi, B., & Jafari, H. R. (2016). Land use and land cover spatiotemporal dynamic pattern and predicting changes using integrated CA-Markov model. Global Journal of Environmental Science and Management-Gjesm, 2(3), 223-234.
24. Bajracharya, P., Lippitt, C. D., & Sultana, S. (2019). Modeling Urban Growth and Land Cover Change in Albuquerque Using SLEUTH. Professional Geographer.
25. Barros, K. D., Ribeiro, C. A. A. S., Marcatti, G. E., Lorenzon, A. S., de Castro, N. L. M., Domingues, G. F., . . . dos Santos, A. R. (2018). Markov chains and cellular automata to predict environments subject to desertification. Journal of Environmental Management, 225, 160-167.
26. Basnou, C., Alvarez, E., Bagaria, G., Guardiola, M., Isern, R., Vicente, P., & Pino, J. (2013). Spatial Patterns of Land Use Changes Across a Mediterranean Metropolitan Landscape: Implications for Biodiversity Management. Environmental Management, 52(4), 971-980.
27. Bihamta, N., Soffianian, A., Fakheran, S., & Gholamalifard, M. (2015). Using the SLEUTH Urban Growth Model to Simulate Future Urban Expansion of the Isfahan Metropolitan Area, Iran. Journal of the Indian Society of Remote Sensing, 43(2), 407-414.
28. Cao, K., Suo, A. N., & Sun, Y. G. (2017). Spatial-Temporal Dynamics Analysis of Coastal Landscape Pattern on Driving Force of Human Activities: A Case in South Yingkou, China. Applied Ecology and Environmental Research, 15(3), 923-937.
29. Chaudhuri, G., & Clarke, K. C. (2019). Modeling an Indian megalopolis- A case study on adapting SLEUTH urban growth model. Computers Environment and Urban Systems, 77.
30. Choi, M., & Han, S. (2013). Remote sensing imageries for land cover and water quality dynamics on the west coast of Korea. Environmental Monitoring and Assessment, 185(11), 9111-9124.
31. Chotchaiwong, P., & Wijitkosum, S. (2019). Predicting Urban Expansion and Urban Land Use Changes in Nakhon Ratchasima City Using a CA-Markov Model under Two Different Scenarios. Land, 8(9). Cohen, W. B., Spies, T. A., Alig, R. J., Oetter, D. R., Maiersperger, T. K., & Fiorella, M. (2002). Characterizing 23 years (1972-95) of stand replacement disturbance in western Oregon forests with Landsat imagery. Ecosystems, 5(2), 122-137. Dodd, C. K., Barichivich, W. J., Johnson, S. A., & Staiger, J. S. (2007). Changes in a northwestern Florida gulf coast herpetofaunal community over a 28-y period. American Midland Naturalist, 158(1), 29-48. Durmusoglu, Z. O., & Tanriover, A. A. (2017). Modelling land use/cover change in Lake Mogan and surroundings using CA-Markov Chain Analysis. Journal of Environmental Biology, 38(5), 981-989. Esbah, H., Kara, B., Deniz, B., & Kesgin, B. (2010). Changing Land Cover Characteristics of a Developing Coastal Town: A Case Study of Didim, Turkey. Journal of Coastal Research, 26(2), 274-282. Esmail, M., Ali, M., & Negm, A. (2016). Monitoring Land Use/Land Cover Changes Around Damietta Promontory, Egypt, Using RS/GIS. 12th International Conference on Hydroinformatics (Hic 2016) - Smart Water for the Future, 154, 936-942. Fasona, M., & Omojola, A. (2009). Land cover change and land degradation in parts of the southwest coast of Nigeria. African Journal of Ecology, 47, 30-38. Fraser, R. H., Olthof, I., Kokelj, S. V., Lantz, T. C., Lacelle, D., Brooker, A., . . . Schwarz, S. (2014). Detecting Landscape Changes in High Latitude Environments Using Landsat Trend Analysis: 1. Visualization. Remote Sensing, 6(11), 11533-11557. Fu, X., Wang, X. H., & Yang, Y. J. (2018). Deriving suitability factors for CA-Markov land use simulation model based on local historical data. Journal of Environmental Management, 206, 10-19. Gai, A. H., Di, L. P., Tang, J. M., Guo, L. Y., Qian, Y. L., Zhou, D. M., . . . Cen, G. Z. (2018). Landscape Pattern Analysis and Prediction in Qingyang City Based on CA-Markov Model. 2018 7th International Conference on Agro-Geoinformatics (Agro-Geoinformatics), 47-52. Garcia, M., & Ustin, S. L. (2001). Detection of interannual vegetation responses to climatic variability using AVIRIS data in a coastal savanna in California. Ieee Transactions on Geoscience and Remote Sensing, 39(7), 1480-1490.
32. Gidey, E., Dikinya, O., Sebego, R., Segosebe, E., & Zenebe, A. (2017). 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, 3(4), 1245-1262.
33. Guan, D. J., Zhao, Z. L., & Tan, J. (2019). Dynamic simulation of land use change based on logistic-CA-Markov and WLC-CA-Markov models: a case study in three gorges reservoir area of Chongqing, China. Environmental Science and Pollution Research, 26(20), 20669-20688.
34. Hamad, R., Balzter, H., & Kolo, K. (2018). Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios. Sustainability, 10(10).
35. Hasani, M., Sakieh, Y., Dezhkam, S., Ardakani, T., & Salmanmahiny, A. (2017). Environmental monitoring and assessment of landscape dynamics in southern coast of the Caspian Sea through intensity analysis and imprecise land-use data. Environmental Monitoring and Assessment, 189(4).
36. Heathfield, D. K., & Walker, I. J. (2015). Evolution of a foredune and backshore river complex on a high-energy, drift-aligned beach. Geomorphology, 248, 440-451.
37. Hossen, H., & Negm, A. (2016). Change detection in the water bodies of Burullus Lake, Northern Nile Delta, Egypt, using RS/GIS. 12th International Conference on Hydroinformatics (Hic 2016) - Smart Water for the Future, 154, 951-958.
38. Jantz, C. A., Goetz, S. J., Donato, D., & Claggett, P. (2010). Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model. Computers Environment and Urban Systems, 34(1), 1-16.
39. Jantz, C. A., Goetz, S. J., & Shelley, M. K. (2004). Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on urban land use in the Baltimore-Washington metropolitan area. Environment and Planning B-Planning & Design, 31(2), 251-271.
40. Jia, M. M., Wang, Z. M., Liu, D. W., Ren, C. Y., Tang, X. G., & Dong, Z. Y. (2015). Monitoring Loss and Recovery of Salt Marshes in the Liao River Delta, China. Journal of Coastal Research, 31(2), 371-377.
41. Jones, B. M., Stoker, J. M., Gibbs, A. E., Grosse, G., Romanovsky, V. E., Douglas, T. A., . . . Richmond, B. M. (2013). Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR. Environmental Research Letters, 8(4).
42. Kang, Y. Y., Ding, X. R., Xu, F., Zhang, C. K., & Ge, X. P. (2017). Topographic mapping on large-scale tidal flats with an iterative approach on the waterline method. Estuarine Coastal and Shelf Science, 190, 11-22.
43. Kayhko, N., Fagerholm, N., Asseid, B. S., & Mzee, A. J. (2011). Dynamic land use and land cover changes and their effect on forest resources in a coastal village of Matemwe, Zanzibar, Tanzania. Land Use Policy, 28(1), 26-37.
44. Kotilainen, A. T., & Kaskela, A. M. (2017). Comparison of airborne LiDAR and shipboard acoustic data in complex shallow water environments: Filling in the white ribbon zone. Marine Geology, 385, 250-259.
45. Li, N., Yang, W., Xu, L. Q., Jia, X. B., An, S. Q., & Fang, S. B. (2017). Two comparative approaches to identify the conservation priority areas impacted by heavy metals on Yellow Sea coasts. Journal of Coastal Conservation, 21(1), 177-188.
46. Mahiny, A. S., & Clarke, K. C. (2012). Guiding SLEUTH land-use/land-cover change modeling using multicriteria evaluation: towards dynamic sustainable land-use planning. Environment and Planning B-Planning & Design, 39(5), 925-944.
47. Mahiny, A. S., & Clarke, K. C. (2013). Simulating Hydrologic Impacts of Urban Growth Using SLEUTH, Multi Criteria Evaluation and Runoff Modeling. Journal of Environmental Informatics, 22(1), 27-38.
48. Marzialetti, F., Giulio, S., Malavasi, M., Sperandii, M. G., Acosta, A. T. R., & Carranza, M. L. (2019). Capturing Coastal Dune Natural Vegetation Types Using a Phenology-Based Mapping Approach: The Potential of Sentinel-2. Remote Sensing, 11(12).
49. Meng, F., Yu, M. Y., Liu, Y. C., & Cui, J. (2011). Wetlands Dynamics in Nansi Lake, Shandong, China. Advances in Civil Engineering, Pts 1-4, 90-93, 3283-+.
50. Meng, X. Q., & Chen, Y. J. (2013). The Analysis and Evaluation of Land Cover Change in Xining City Based on CA-Markov Model. Sustainable Development of Urban Infrastructure, Pts 1-3, 253-255, 207-210.
51. Menon, S., & Bawa, K. S. (1997). Applications of geographic information systems, remote-sensing, and a landscape ecology approach to biodiversity conservation in the Western Ghats. Current Science, 73(2), 134-145.
52. Mialhe, F., Gunnell, Y., Mering, C., Gaillard, J. C., Coloma, J. G., & Dabbadie, L. (2016). The development of aquaculture on the northern coast of Manila Bay (Philippines): an analysis of long-term land-use changes and their causes. Journal of Land Use Science, 11(2), 236-256.
53. Misra, A., Murali, R. M., & Vethamony, P. (2015). Assessment of the land use/land cover (LU/LC) and mangrove changes along the Mandovi-Zuari estuarine complex of Goa, India. Arabian Journal of Geosciences, 8(1), 267-279.
54. Moghadam, H. S., & Helbich, M. (2013). Spatiotemporal urbanization processes in the megacity of Mumbai, India: A Markov chains-cellular automata urban growth model. Applied Geography, 40, 140-149.
55. Mohamed, A. H., Holechek, J. L., Bailey, D. W., Campbell, C. L., & DeMers, M. N. (2011). Mesquite encroachment impact on southern New Mexico rangelands: remote sensing and geographic information systems approach. Journal of Applied Remote Sensing, 5.
56. Mondal, P., Trzaska, S., & de Sherbinin, A. (2018). Landsat-Derived Estimates of Mangrove Extents in the Sierra Leone Coastal Landscape Complex during 1990-2016. Sensors, 18(1).
57. Munroe, D. K., Nagendra, H., & Southworth, J. (2007). Monitoring landscape fragmentation in an inaccessible mountain area: Celaque National Park, Western Honduras. Landscape and Urban Planning, 83(2-3), 154-167.
58. Nagendra, H., & Utkarsh, G. (2003). Landscape ecological planning through a multi-scale characterization of pattern: Studies in the Western Ghats, south India. Environmental Monitoring and Assessment, 87(3), 215-233.
59. Oguz, H. (2012). Simulating future urban growth in the city of Kahramanmaras, Turkey from 2009 to 2040. Journal of Environmental Biology, 33(2), 381-386.
60. Oguz, H., & Bozali, N. (2014). Prediction of Land Use/Land Cover Change in the City of Gaziantep until the Year 2040. Journal of Agricultural Sciences-Tarim Bilimleri Dergisi, 20(1), 83-101.
61. Omar, N. Q., Sanusi, S. A. M., Hussin, W. M. W., Samat, N., & Mohammed, K. S. (2014). Markov-CA model using analytical hierarchy process and multi-regression technique. 7th Igrsm International Remote Sensing & Gis Conference and Exhibition, 20.
62. Parcerisas, L., Marull, J., Pino, J., Tello, E., Coll, F., & Basnou, C. (2012). Land use changes, landscape ecology and their socioeconomic driving forces in the Spanish Mediterranean coast (El Maresme County, 1850-2005). Environmental Science & Policy, 23, 120-132.
63. Pourebrahim, S., Hadipour, M., & Bin Mokhtar, M. (2015). Impact assessment of rapid development on land use changes in coastal areas; case of Kuala Langat district, Malaysia. Environment Development and Sustainability, 17(5), 1003-1016.
64. Rabehi, W., Guerfi, M., Mahi, H., & Rojas-Garcia, E. (2019). Spatiotemporal Monitoring of Coastal Urbanization Dynamics: Case Study of Algiers' Bay, Algeria. Journal of the Indian Society of Remote Sensing, 47(11), 1917-1936.
65. Rienow, A., & Goetzke, R. (2015). Supporting SLEUTH - Enhancing a cellular automaton with support vector machines for urban growth modeling. Computers Environment and Urban Systems, 49, 66-81.
66. Roy, S., Mahapatra, M., & Chakraborty, A. (2019). Mapping and monitoring of mangrove along the Odisha coast based on remote sensing and GIS techniques. Modeling Earth Systems and Environment, 5(1), 217-226.
67. Sakieh, Y., Amiri, B., Danekar, A., Feghhi, J., & Dezhkam, S. (2015). Simulating urban expansion and scenario prediction using a cellular automata urban growth model, SLEUTH, through a case study of Karaj City, Iran. Journal of Housing and the Built Environment, 30(4), 591-611.
68. Sangawongse, S., Sun, C. H., & Tsai, B. W. (2005). Urban Growth and Land Cover Change In Chiang Mai and Taipei: Results From The SLEUTH Model. Modsim 2005: International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, 2622-2628.
69. Schwarz, N., & Manceur, A. M. (2015). Analyzing the Influence of Urban Forms on Surface Urban Heat Islands in Europe. Journal of Urban Planning and Development, 141(3).
70. Serasinghe Pathiranage, I. S., Kantakumar, L. N., & Sundaramoorthy, S. (2018). Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning. Chinese Geographical Science, 28(2), 274-286.
71. Sertel, E., Findik, N., Kaya, S., Seker, D. Z., & Samsunlu, A. (2008). Assessment of landscape changes in the Kizilirmak Delta, Turkey, using remotely sensed data and GIS. Environmental Engineering Science, 25(3), 353-361.
72. Shi, Y. S., Wu, J., & Shi, S. Z. (2017). Study of the Simulated Expansion Boundary of Construction Land in Shanghai Based on a SLEUTH Model. Sustainability, 9(6).
73. Sinha, P., & Kumar, L. (2013). Markov Land Cover Change Modeling Using Pairs of Time-Series Satellite Images. Photogrammetric Engineering and Remote Sensing, 79(11), 1037-1051.
74. Stoops, C. A., Gionar, Y. R., Shinta, Sismadi, P., Rachmat, A., Elyazar, I. F., & Sukowati, S. (2008). Remotely-sensed land use patterns and the presence of Anopheles larvae (Diptera : Culicidae) in Sukabumi, West Java, Indonesia. Journal of Vector Ecology, 33(1), 30-39.
75. Su, L., Zhu, J. H., Zeng, L., & Liu, M. (2012). Landscape pattern change prediction of Jinhu coastal area based on CA-Markov model. 2012 World Automation Congress (Wac).
76. Turner, D. P., Guzy, M., Lefsky, M. A., Ritts, W. D., VAN Tuyl, S., & Law, B. E. (2004). Monitoring forest carbon sequestration with remote sensing and carbon cycle modeling. Environmental Management, 33(4), 457-466.
77. Ustaoglu, B. (2012). Spatiotemporal analysis of land cover change patterns in western part of the Sakarya River Delta and its surroundings in Turkey. Energy Education Science and Technology Part a-Energy Science and Research, 29(2), 721-730.
78. White, R. A., Piraino, K., Shortridge, A., & Arbogast, A. F. (2019). Measurement of Vegetation Change in Critical Dune Sites along the Eastern Shores of Lake Michigan from 1938 to 2014 with Object-Based Image Analysis. Journal of Coastal Research, 35(4), 842-851.
79. Yan, N., & Baas, A. C. W. (2018). Transformation of parabolic dunes into mobile barchans triggered by environmental change and anthropogenic disturbance. Earth Surface Processes and Landforms, 43(5), 1001-1018.
80. Yang, Y. C., Liao, L. P., Yan, L. B., Hu, X. C., Huang, H. B., & Xiao, S. (2016). The big data analysis of land use evolution and its ecological security responses in Silver Beach of China by the clustering of spatial patterns. Cluster Computing-the Journal of Networks Software Tools and Applications, 19(4), 1907-1924.
81. Yi, W., & He, B. (2009). Applying SLEUTH for Simulating Urban Expansion of Beijing. 2009 International Forum on Information Technology and Applications, Vol 2, Proceedings, 652-656.
82. Yilmaz, R. (2010). Monitoring land use/land cover changes using CORINE land cover data: a case study of Silivri coastal zone in Metropolitan Istanbul. Environmental Monitoring and Assessment, 165(1-4), 603-615.
83. Yin, H. W., Kong, F. H., Hu, Y. M., James, P., Xu, F., & Yu, L. J. (2016). Assessing Growth Scenarios for Their Landscape Ecological Security Impact Using the SLEUTH Urban Growth Model. Journal of Urban Planning and Development, 142(2).
84. Zald, H. S. J. (2009). Extent and spatial patterns of grass bald land cover change (1948-2000), Oregon Coast Range, USA. Plant Ecology, 201(2), 517-529.
85. Zhang, K. Q., Thapa, B., Ross, M., & Gann, D. (2016). Remote sensing of seasonal changes and disturbances in mangrove forest: a case study from South Florida. Ecosphere, 7(6).
86. Zheng, L., Zhang, D. Y., Zhou, Y. Y., Zhang, X. Y., Shi, R. H., & Chen, M. S. (2018). Simulation of land use / cover change in Shanghai based on SLEUTH model. Remote Sensing and Modeling of Ecosystems for Sustainability Xv, 10767.
87. Zitti, M., Ferrara, C., Perini, L., Carlucci, M., & Salvati, L. (2015). Long-Term Urban Growth and Land Use Efficiency in Southern Europe: Implications for Sustainable Land Management. Sustainability, 7(3), 3359-3385.