Abstract
Coastlines mapping techniques or the coastline automated analyses have been sought after. In practice, various sorts of seacoasts, for example, biological, silty, arenaceous, artificial, and bedrock coasts, have their own attributes, which force various degrees of intricacy on coastline mapping. As an extraordinary kind of complex artificial coast, aquaculture coast is shaped by the farming of aquatic organisms on silt tidal flats. With the rapid growth of coastal aquaculture in recent years, aquaculture coasts have increased in some developing countries. It has been estimated that aquaculture coasts constitute about 30% of all coastlines in mainland China. In order to identify, monitor, model, and manage the vast expanse of coastal aquaculture, effective methods of extracting aquaculture coastlines from remotely sensed imagery are desired. Secondly, with the rapid economic development in coastal areas, the development of coastal zone resources is also increasing day by day, which benefits the development of island coastal zone. Using oneself has become an important link in the development of marine economy. Due to the limited coastal resources and low environmental carrying capacity, the overexploitation and utilization of coastal resources will lead to a series of problems, such as coastal erosion, coastal migration and accumulation, island area reduction, etc., Both man-made activities and natural factors will lead to coastline changes, which will lead to corresponding changes in coastal ecological environment, thus affecting the coordinated development of coastal economy and the survival of coastal residents. Therefore, efficient, accurate and timely acquisition of coastline information and research on the spatial-temporal changes of coastline are of great significance to the protection of the living environment of coastal residents, the effective development of island and coastal resources, the coordination of sustainable economic development in coastal areas and the mitigation of marine disasters. This paper presents a review of those papers reporting coastline extraction and land use and land cover (LULC) change analysis using remote sensing (RS) and geographic information system (GIS) technology.
Research funding: None declared.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interests: None declared.
Informed consent: Not Applicable.
Ethical approval: Not Applicable.
References
1. GIS.com. What is GIS?. ESRI; 2011. Available from: https://www.gis.com/content/whatgis [access date: 28.09.2019].Search in Google Scholar
2. Şeker, DZ, Tanık, A, Öztürk, İ. Application of GIS for the watershed management studies. Ankara: TMMBO Coğrafi Bilgi Sistemleri Kongresi; 2009.Search in Google Scholar
3. Erturk, A, Ekdal, A, Gurel, M, Yuceil, K, Tanik, A. Use of mathematical models to estimate the effect of nutrient loadings on small streams. Fresenius Environ Bull 2004;13:1350–9.Search in Google Scholar
4. Lillesand, T, Kiefer, RW, Chipman, J. Remote sensing and image interpretation. Hoboken, New Jersey: John Wiley & Sons; 2015.Search in Google Scholar
5. Durduran, SS. Coastline change assessment on water reservoirs located in the Konya Basin Area, Turkey, using multitemporal landsat imagery. Environ Monit Assess 2010;164:453–61. https://doi.org/10.1007/s10661-009-0906-9.Search in Google Scholar PubMed
6. Clarke, KC. Getting started with geographical information systems, 5th ed. England: Pearson. 2011.Search in Google Scholar
7. Howarth, PJ, Wickware, GM. Procedures for change detection using Landsat digital data. Int J Rem Sens 1981;2:277–91. https://doi.org/10.1080/01431168108948362.Search in Google Scholar
8. Dellepiane, S, De Laurentiis, R, Giordano, F. Coastline extraction from SAR images and a method for the evaluation of the coastline precision. Pattern Recogn Lett 2004;25:1461–70. https://doi.org/10.1016/j.patrec.2004.05.022.Search in Google Scholar
9. Kuleli, T. Quantitative analysis of shoreline changes at the Mediterranean Coast in Turkey. Environ Monit Assess 2010;167:387–97. https://doi.org/10.1007/s10661-009-1057-8.Search in Google Scholar PubMed
10. Winarso, G, Budhiman, S. The potential application of remote sensing data for coastal study. In: Proceeding 22nd. Asian conference on remote sensing, National University of Singapore, Singapore; 2001.Search in Google Scholar
11. Klein, M, Lichter, M. Monitoring changes in shoreline position adjacent to the Hadera power station, Israel. Appl Geogr 2006;26:210–26. https://doi.org/10.1016/j.apgeog.2006.01.001.Search in Google Scholar
12. Chopra, R, Verma, VK, Sharma, PK. Mapping, monitoring and conservation of Harike wetland ecosystem, Punjab, India, through remote sensing. Int J Rem Sens 2001;22:89–98. https://doi.org/10.1080/014311601750038866.Search in Google Scholar
13. Gens, R. Remote sensing of coastlines: detection, extraction and monitoring. Int J Rem Sens 2010;31:1819–36. https://doi.org/10.1080/01431160902926673.Search in Google Scholar
14. Alesheikh, AA, Sadeghi Naeeni, F, Talebzade, A. Improving classification accuracy using external knowledge. GIM Int 2003;17:12–5.Search in Google Scholar
15. Kurt, S, Karaburun, A, Demirci, A. Coastline changes in Istanbul between 1987 and 2007. Sci Res Essays 2010;5:3009–17.Search in Google Scholar
16. Di, K, Ma, R, Wang, J, Li, R. Coastal mapping and change detection using high-resolution IKONOS satellite imagery. In: Proceedings of the 2003 annual national conference on digital government research, Digital Government Society of North America, Montréal; 2003.Search in Google Scholar
17. Ekercin, S. Multitemporal change detection on the Salt Lake and its vicinity by integration remote sensing and geographical information systems [Doctoral dissertation, PhD thesis]. ITU: Geneva, Switzerland; 2007.Search in Google Scholar
18. Xie, MH, Zhang, YF, Fu, K. Algorithm of detection coastline from SAR images based on seeds growing. J Grad Sch Chin Acad Sci 2007;24:93–8.Search in Google Scholar
19. Briney, A. GIS. An overview of geographical information systems; 2008. Available from: http://geography.about.com/od/geographyinter/a/gisoverview.htm [accessed on 5/2/2018].Search in Google Scholar
20. Wilkie, DS, Finn, JT, Finn, J. Remote sensing imagery for natural resources monitoring: a guide for first-time users. New York: Columbia University Press; 1996.Search in Google Scholar
21. Matsa, M, Muringaniza, K. An assessment of the land use and land cover changes in Shurugwi district Zimbabwe. EJESM 2011;4. https://doi.org/10.4314/ejesm.v4i2.10.Search in Google Scholar
22. Rawat, JS, Kumar, M. Monitoring land use/cover change using remote sensing and GIS techniques: a case study of Hawalbagh block, district Almora, Uttarakhand, India. EJRS 2015;18:77–84. https://doi.org/10.1016/j.ejrs.2015.02.002.Search in Google Scholar
23. Ellis, E, Pontius, R. Land-use and land-cover change. Encycl Earth 2007:1–4.Search in Google Scholar
24. Yuan, X, Wang, P, Zhang, Y, Ren, L, Zhai, L. Research on automatic coastline extraction based on edge detection [J]. Beijing Surv Map 2019;33:148–52.Search in Google Scholar
25. Liu, F, Chen, SH, Liu, QB, Fan, XJ, Tang, F, Liu, DW, Zhao, GQ. Rapid proliferation of bone marrow mesenchymal stem cells enhanced by xanthosine. Chin J Pathophysiol 2010;26:2389–93. https://doi.org/10.3969/j.issn.1000-4718.2010.12.020.Search in Google Scholar
26. Jianyong, F. Remote sensing monitoring of coastline dynamic changes in Qingdao and its surrounding areas[D]. China: Graduate School of Chinese Academy of Sciences (Institute of Oceanography); 2005.Search in Google Scholar
27. Wang, Z, He, SX. An adaptive edge-detection method based on canny algorithm [J]. Journal of Image and Graphics 2004;8:957–62.Search in Google Scholar
28. Fan, F, Weng, Q, Wang, Y. Land use and land cover change in Guangzhou, China, from 1998 to 2003, based on Landsat TM/ETM+ imagery. Sensors 2007;7:1323–42. https://doi.org/10.3390/s7071323.Search in Google Scholar
29. Hegazy, IR, Kaloop, MR. Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. Int J 2015;4:117–24. https://doi.org/10.1016/j.ijsbe.2015.02.005.Search in Google Scholar
30. Sankhala, S, Singh, B. Evaluation of urban sprawl and land use land cover change using remote sensing and GIS techniques: a case study of Jaipur City, India. Int J Emerging Technol Adv Eng 2014;4:66–72.Search in Google Scholar
31. Alves, DS, Skole, DL. Characterizing land cover dynamics using multi-temporal imagery. Int J Rem Sens 1996;17:835–9. https://doi.org/10.1080/01431169608949049.Search in Google Scholar
32. Muttitanon, W, Tripathi, NK. Land use/land cover changes in the coastal zone of Ban Don Bay, Thailand using Landsat 5 TM data. Int J Rem Sens 2005;26:2311–23. https://doi.org/10.1080/0143116051233132666.Search in Google Scholar
33. Prenzel, B. Remote sensing-based quantification of land-cover and land-use change for planning. Prog Plann 2004;4:281–99. https://doi.org/10.1016/S0305-9006(03)00065-5.Search in Google Scholar
34. Vitousek, PM. Global environmental change: an introduction. Annu Rev Ecol Evol Syst 1992;23:1–4. https://doi.org/10.1146/annurev.es.23.110192.000245.Search in Google Scholar
35. Houghton, RA. The worldwide extent of land-use change. J Biosci 1994;44:305–13. https://doi.org/10.2307/1312380.10.2307/1312380Search in Google Scholar
36. Myers, N. Tropical forests: the main deforestation fronts. Environ Conserv 1993;20:9–16. https://doi.org/10.1017/S0376892900037176.Search in Google Scholar
37. Turner, BL. Toward integrated land-change science: advances in 1.5 decades of sustained international research on land-use and land-cover change. In: Challenges of a changing earth. Berlin, Heidelberg: Springer; 2002.10.1007/978-3-642-19016-2_3Search in Google Scholar
38. Verburg, PH, Chen, Y, Soepboer, W, Veldkamp, A. GIS-based modeling of human-environment interactions for natural resource management In: Proceeding of the 4th international conference on integrating GIS and environmental modeling: problems, prospects en research needs. Canada: GIS; 2000.Search in Google Scholar
39. Anil, NC, Sankar, GJ, Rao, MJ, Prasad, IV, Sailaja, U. Studies on land use/land cover and change detection from parts of south west godavari district, AP–Using remote sensing and GIS techniques. J Ind Geophys Union 2011;15:187–94.Search in Google Scholar
40. Singh, P, Khanduri, K. Land use and land cover change detection through remote sensing & GIS technology: case study of Pathankot and Dhar Kalan Tehsils, Punjab IJGAGS 2011;1:839–46.Search in Google Scholar
41. Alphan, H. Land‐use change and urbanization of Adana, Turkey. Land Degrad Dev 2003;14:575–86. https://doi.org/10.1002/Idr.581.Search in Google Scholar
42. Giri, C, Zhu, Z, Reed, B. A comparative analysis of the global land cover 2000 and MODIS land cover data sets. Remote Sens Environ 2005;94:123–32. https://doi.org/10.1016/j.rse.2004.09.005.Search in Google Scholar
43. Diallo, Y, Hu, G, Wen, X. Applications of remote sensing in land use/land cover change detection in Puer and Simao Counties, Yunnan Province. Am J Sci 2009;5:157–66.Search in Google Scholar
44. Sidle, RC, Ziegler, AD, Vogler, JB. Contemporary changes in open water surface area of Lake Inle, Myanmar. Sustain Sci.2007;2:55–65. https://doi.org/10.1007/s11625-006-0020-7.Search in Google Scholar
45. Liangzhao, L, Zengdi, P, Kang, X, Na, Y. The Coastline extraction for fujian province based on long time series of remote sensing image In: 2013 the international conference on remote sensing, environment and transportation engineering (RSETE 2013), Atlantis Press, Paris; 2013.10.2991/rsete.2013.16Search in Google Scholar
46. Dwivedi, RS, Sreenivas, K, Ramana, KV. Cover: land‐use/land‐cover change analysis in part of Ethiopia using Landsat Thematic Mapper data. Int J Rem Sens 2005;26:1285–7. https://doi.org/10.1080/01431160512331337763.Search in Google Scholar
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