DOI QR코드

DOI QR Code

West seacoast wetland monitoring using KOMPSAT series imageries in high spatial resolution

고해상도 KOMPSAT 시리즈 이미지를 활용한 서해연안 습지 변화 모니터링

  • Sunwoo, Wooyeon (Graduate School of Water Resources, Sungkyunkwan University) ;
  • Kim, Daeun (Graduate School of Water Resources, Sungkyunkwan University) ;
  • Kim, Seongkyun (Graduate School of Water Resources, Sungkyunkwan University) ;
  • Choi, Minha (Graduate School of Water Resources, Sungkyunkwan University)
  • 선우우연 (성균관대학교 수자원전문대학원) ;
  • 김다은 (성균관대학교 수자원전문대학원) ;
  • 김성균 (성균관대학교 수자원전문대학원) ;
  • 최민하 (성균관대학교 수자원전문대학원)
  • Received : 2017.02.28
  • Accepted : 2017.05.18
  • Published : 2017.06.30

Abstract

A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images were analyzed to detect the geographical changes in four different tidal flats in the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from the satellite images, which were used as the input of the temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps extracted from the KOMPSAT images indicate that these multispectral high-resolution satellite data is highly applicable to generate good quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the tidal flat area of Gyeonggi and Jeollabuk provinces was estimated to have changed due to tidal effects, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in Jeollanam province revealed that the social and environmental policies can effectively protect coastal wetlands from degradation. Therefore, monitoring for wetland change using high resolution KOMPSAT is expected to be useful to coastal environment management and policy making.

대한민국 서해안의 4개 갯벌에 대한 변화 탐지를 위해 다중분광 고해상도 다목적 위성인 KOMPSAT 시리즈 영상 자료를 분석하였다. 무감독 분류법을 이용하여 고해상도 위성 이미지에서 생성된 토지이용 및 토피피복 지도의 활용성과 연안 습지 변화의 경향을 결정할 때 시간 궤적 분석과 통합된 변화 탐지 방법론을 평가했다. 자연 현상과 인위적 활동에 대한 토지이용 및 토지피복 변화 분석을 통해 갯벌면적을 추출하고, 양질의 주제지도를 제공하기 위한 고해상도 KOMPSAT 데이터의 실질적인 적용 가능성을 확인하였다. 경기도와 전라북도의 갯벌 지역은 조석 차에 영향으로 면적 변화가 나타난 것으로 추정되었으며, 새만금 지역의 갯벌지역은 대규모 매립 및 도시화로 인한 인위적 활동에 따른 것으로 나타났다. 또한 전라남도 증도 갯벌지역의 경우 연안습지보호지역으로 지정되어 연안 갯벌 보전에 대한 사회적, 환경적 정책의 효과를 확인하였다. 따라서 고해상도 KOMPSAT를 이용한 습지변화 모니터링은 연안환경 관리 및 정책결정을 위해서 유용할 것으로 기대된다.

Keywords

References

  1. Adam, E., Mutanga, O., Odindi, J., and Abdel-Rahman, E. M. (2014). "Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector machines classifiers." International Journal of Remote Sensing, Vol. 35, No. 10, pp. 3440-3458. https://doi.org/10.1080/01431161.2014.903435
  2. Alrababah, M. A., and Alhamad, M. N. (2006). "Land use/cover classification of arid and semi-arid Mediterranean landscapes using Landsat ETM." International Journal of Remote Sensing, Vol. 27, No. 13, pp. 2703-2718. https://doi.org/10.1080/01431160500522700
  3. Anderson, J. R., Hardy, E. E., Roach, J. T., and Witmer, R. E. (1976). A land use and land cover classification system for use with remote sensor data. Geological Survey Professional Paper, 964.
  4. Bahadur, K. C. K. (2009). "Improving Landsat and IRS image classification: evaluation of unsupervised and supervised classification through band ratios and DEM in a mountainous landscape in Nepal." Remote Sensing, Vol. 1, No. 4, pp. 1257-1272. https://doi.org/10.3390/rs1041257
  5. Baker, C., Lawrence, R. L., Montagne, C., and Patten, D. (2007). "Change detection of wetland ecosystems using Landsat imagery and change vector analysis." Wetlands, Vol. 27, No. 3, pp. 610-619. https://doi.org/10.1672/0277-5212(2007)27[610:CDOWEU]2.0.CO;2
  6. Baker, C., Lawrence, R., Montagne, C., and Patten, D. (2006). "Mapping wetlands and riparian areas using Landsat ETM+ imagery and decision-tree-based models. Wetlands, Vol. 26, pp. 465-474. https://doi.org/10.1672/0277-5212(2006)26[465:MWARAU]2.0.CO;2
  7. Ball, G. H., and Hall, D. J. (1965). ISODATA, a novel method of data analysis and pattern classification. Technical Report.
  8. Cho, J. Y., Son, J. G., Song, C. H., Hwang, S. A., Lee, Y. M., Jeong, S. Y., and Chung, B. Y. (2008). "Integrated nutrient management for environmental-friendly rice production in salt-affected paddy fields of Saemangeum reclaimed land of South Korea." Paddy Water Environment, Vol. 6, No. 263-273. https://doi.org/10.1007/s10333-008-0124-z
  9. Choi, M., and Han, S. (2013). "Remote sensing imageries for land cover and water quality dynamics on the west coast of Korea." Environmental Monitoring and Assessment, Vol. 185, pp. 9111-9124. https://doi.org/10.1007/s10661-013-3240-1
  10. Cohen, W. B., Spies, T. A., Alig, R. J., Oetter, D. R., Maiersperger, T. K., and Fiorella, M. (2002). "Characterizing 23 years (1972-95) of stand replacement disturbance in Western Oregon forests with Landsat imagery." Ecosystems, Vol. 5, No. 2, pp. 122-137. https://doi.org/10.1007/s10021-001-0060-X
  11. Congalton, R. G. (1991). "A review of assessing the accuracy of classifications of remotely sensed data." Remote Sensing of Environment, Vol. 37, pp. 35-46. https://doi.org/10.1016/0034-4257(91)90048-B
  12. Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., and Lambin, E. (2004). "Digital change detection methods in ecosystem monitoring: a review. International Journal of Remote Sensing, Vol. 25, No. 9, pp. 1565-1596. https://doi.org/10.1080/0143116031000101675
  13. Davrache, A., Lefebvre, G., and Poulin, B. (2010). "Wetland monitoring using classification trees and SPOT-5 seasonal time series." Remote Sensing of Environment, Vol. 114, pp. 552-562. https://doi.org/10.1016/j.rse.2009.10.009
  14. Dechka, J. A., Franklin, S. E., Watmough, M. D., Bennett, R. P., and Ingstrup, D. W. (2002). "Classification of wetland habitat and vegetation communities using multitemporal IKONOS imagery in southern Saskatchewan." Canadian Journal of Remote Sensing, Vol. 28, No. 5, pp. 679-685. https://doi.org/10.5589/m02-064
  15. Deng, J. S., Wang, K., Deng, Y. H., and Qi, G. J. (2008). "PCA-based land-use change detection and analysis using multitemporal and multisensor satellite data." International Journal of Remote Sensing, Vol. 29, No. 16, pp. 4823-4838. https://doi.org/10.1080/01431160801950162
  16. Foody, G. M. (2000). "Estimation of sub-pixel land cover composition in the presence of untrained classes." Computers and Geosciences, Vol. 26, pp. 469-478. https://doi.org/10.1016/S0098-3004(99)00125-9
  17. Funkenberg, T., Binh, T. T., Moder, F., and Dech, S. (2014). "The Ha Tien Plain - wetland monitoring using remote sensing techniques." International Journal of Remote Sensing, Vol. 35, No. 8, pp. 2893-2909. https://doi.org/10.1080/01431161.2014.890306
  18. Hahm, H., Jeong, S., Jeong, M., and Park, S. (2014). "Cultural resources and management in the coastal regions along the Korean tidal flat." Ocean and Coastal Management, Vol. 102, pp. 506-521. https://doi.org/10.1016/j.ocecoaman.2014.07.011
  19. Jang, D. H., Kim, C., and Park, J. H. (2010). "Assessment of flood risk under rise of sea level in chungnam coastal area using multi-temporal satellite imagery data." Journal of Photo Geography, Vol. 20, pp. 71-83.
  20. Jang, H. J., and Lee, G. G. (2013). "A study on national wetland evaluation for the selection of priority control target wetlands in South Korea." Journal of Civil Engineering, KSCE, Vol. 17, No. 7, pp. 1603-1613.
  21. Kim, S. G. (2010). "The evolution of coastal wetland policy in developed countries and Korea." Ocean and Coastal Management, Vol. 53, pp. 562-569. https://doi.org/10.1016/j.ocecoaman.2010.06.017
  22. Koh, C. H., Jin, D., and Ha, S. R. (2008). "An analysis of suitable site of constructed wetland using high resolution satellite image and GIS in Kyoung-An stream." Journal of Korean Wetlands Society, Vol. 10, pp. 115-128.
  23. Lee, H. J., and Ryu, S. O. (2007). "Role of the giant Saemangeum dyke in sedimentation at the mouth of an estuarine complex." Marine Geology, Vol. 239, pp. 173-188. https://doi.org/10.1016/j.margeo.2007.02.002
  24. Lee, Y. K., Ryu, J. H., Choi, J. K., Lee, S., and Woo, H. J. (2015). "Satellite-based observations of the unexpected coastal change due to the Saemangeum Dyke construction, Korea." Marine Pollution Bulletin, Vol. 97, pp. 150-159. https://doi.org/10.1016/j.marpolbul.2015.06.023
  25. Lie, H. J., Cho, C. H., Lee, S., Kim, E. S., Koo, B. J., Noh, J. H. (2008). "Change in marine environment by a large coastal development of the Saemangeum reclamation project in Korea." Ocean and Polar Research, Vol. 30, No. 4, pp. 475-484. https://doi.org/10.4217/OPR.2008.30.4.475
  26. Liu, H., and Zhou, Q. (2005). "Developing urban growth predictions from spatial indicators based on multi-temporal images." Environment and Urban Systems, Computer, Vol. 29, pp. 580-594. https://doi.org/10.1016/j.compenvurbsys.2005.01.004
  27. Lu, D., Mausel, P., Brondizio, E., and Moran, E. (2004). "Change detection techniques." International Journal of Remote Sensing, Vol. 25, No. 12, pp. 2365-2401. https://doi.org/10.1080/0143116031000139863
  28. Mertens, B., and Lambin, E. F. (2000). "Land cover change trajectories in Southern Cameroon." Annals of the Association of the American Geographers, Vol. 90, pp. 467-494. https://doi.org/10.1111/0004-5608.00205
  29. Michishita, R., Jiang, Z., Gong, P., and Xu, B. (2012). "Bi-scale analysis of multitemporal land cover fractions for wetland vegetation mapping." ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 72, pp. 1-15. https://doi.org/10.1016/j.isprsjprs.2012.04.006
  30. Monteys, X., Harris, P., Caloca, S., and Cahalane, C. (2015). "Spatial prediction of coastal bathymetry based on multispectral satellite imagery and multibeam data." Remote Sensing, Vol. 7, No. 10, pp. 13782-13806. https://doi.org/10.3390/rs71013782
  31. Munyati, C. (2000). "Wetland change detection on the Kafue Flats, Zambia, by classification of a multitemporal remote sensing image dataset." International Journal of Remote Sensing, Vol. 21, No. 9, pp. 1787-1806. https://doi.org/10.1080/014311600209742
  32. Nam, J. H., Ryu, J. S., Fluharty, D., Koh, C. H., Dyson, K., Chang, W. K., Choi, H. J., Kang, D. S., Khim, J. S., and Lee, C. H. (2010). "Designation processes for marine protected areas in the coastal wetlands of South Korea." Ocean and Coastal Management, Vol. 53, pp. 703-710. https://doi.org/10.1016/j.ocecoaman.2010.10.002
  33. Nielsen, E. M., Prince, S. D., and Koeln, G. T. (2008). "Wetland change mapping for the U.S. mid-Atlantic region using an outlier detection technique." Remote Sensing of Environment, Vol. 112, pp. 4061-4074. https://doi.org/10.1016/j.rse.2008.04.017
  34. Nyarko, B. K., Diekkruger, B., Giesen, N. C. V. D., and Vlek, P. L. G. (2015). "Floodplain wetland mapping in the White Volta river basin of Ghana." GIScience and Remote Sensing, Vol. 52, No. 3, pp. 374-395. https://doi.org/10.1080/15481603.2015.1026555
  35. Ordoyne, C., and Friedl, M. A. (2008). "Using MODIS data to characterize seasonal inundation patterns in the Florida Everglades." Remote Sensing of Environment, Vol. 112, No. 11, pp. 4107-4119. https://doi.org/10.1016/j.rse.2007.08.027
  36. Ozesmi, S. L., and Bauer, M. E. (2002). "Satellite remote sensing of wetlands." Wetlands Ecology and Management, Vol. 10, No. 5, pp. 381-402. https://doi.org/10.1023/A:1020908432489
  37. Parihar, S. M., Sarkar, S., Dutta, A., Sharma, S., and Dutta, T. (2013). "Characterizing wetland dynamics: a post-classification change detection analysis of the East Kolkata Wetlands using open source satellite data." Geocarto International, Vol. 28, No. 3, pp. 273-287. https://doi.org/10.1080/10106049.2012.705337
  38. Pavri, F., and Aber, J. S. (2004). "Characterizing wetland landscapes: a spatiotemporal analysis of remotely sensed data at Cheyenne Bottoms, Kansas." Physical Geography, Vol. 25, pp. 86-104. https://doi.org/10.2747/0272-3646.25.1.86
  39. Peacock, R. (2014). Accuracy assessment of supervised and unsupervised classification using Landsat imagery of Little Rock, Arkansas. Dissertation, Northwest Missouri State University.
  40. Petit, C., Scudder, T., and Lambin, E. (2001). "Quantifying processes of land cover change by remote sensing: resettlement and rapid land cover changes in south eastern Zambia." International Journal of Remote Sensing, Vol. 22, No. 17, pp. 3435-3456. https://doi.org/10.1080/01431160010006881
  41. Ramsey III, E. W., Chappell, D. K., Jacobs, D. M., Sapkota, S. K., and Baldwin, D. G. (1998). "Resource management of forested wetlands: hurricane impact and recovery mapped by combining Landsat TM and NOAA AVHRR data." Photogrammetric Engineering and Remote Sensing, Vol. 64, No. 7, pp. 733-738.
  42. Rundquist, D. C., Narumalani, S., and Narayanan, R. M. (2001). "A review of wetlands remote sensing and defining new considerations." Remote Sensing Reviews, Vol. 20, pp. 207-226. https://doi.org/10.1080/02757250109532435
  43. Ryu, J. H., Won, J. S., and Min, K. D. (2002). "Waterline extraction from Landsat TM data in a tidal flat: a case study in Gomso Bay, Korea." Remote Sensing of Environment, Vol. 83, pp. 442-456. https://doi.org/10.1016/S0034-4257(02)00059-7
  44. Sawaya, K. E., Olmanson, L. G., Heinert, N. J., Brezonik, P. L., and Bauer, M. E. (2003). "Extending satellite remote sensing to local scales: land and water resource monitoring using highresolution imagery." Remote Sensing of Environment, Vol. 88, No. 1-2, pp. 144-156. https://doi.org/10.1016/j.rse.2003.04.006
  45. Singh, A. (1989). "Digital change detection techniques using remotely sensed data." International Journal of Remote Sensing, Vol. 10, No. 6, pp. 989-1003. https://doi.org/10.1080/01431168908903939
  46. Sohn, Y., and Rebello, N. S. (2002). "Supervised and unsupervised spectral angle classifiers." Photogrammetric engineering and remote sensing, Vol. 68, No. 12, pp. 1271-1282.
  47. Syphard, A. D., and Garcia, M. W. (2001). "Human and beaver induced wetland changes in the Chickahominy River watershed from 1953 to 1994." Wetlands, Vol. 21, pp. 342-353. https://doi.org/10.1672/0277-5212(2001)021[0342:HABIWC]2.0.CO;2
  48. Trisurat Y., Eiumnoh, A., Murai, S., Hussain, M. Z., and Shrestha, R. P. (2000). "Improvement of tropical vegetation mapping using a remote sensing technique: a case of Khao Yai National Park, Thailand." International Journal of Remote Sensing, Vol. 21, No. 10, pp. 2031-2042. https://doi.org/10.1080/01431160050021277
  49. Wilson, E. H., and Sader, S. A. (2002). "Detection of forest harvest type using multiple dates of Landsat TM imagery." Remote Sensing of Environment, Vol. 80, No. 3, pp. 385-396. https://doi.org/10.1016/S0034-4257(01)00318-2
  50. Zhao, B., Yan, Y., Guo, H., He, M., Gu, Y., and Li, B. (2009). "Monitoring rapid vegetation succession in estuarine wetland using time series MODIS-based indicators: an application in the Yangtze River Delta area." Ecological Indicators, Vol. 9, pp. 346-356. https://doi.org/10.1016/j.ecolind.2008.05.009
  51. Zhou, H., Jiang, H., Zhou, G., Song, X., Yu, S., Chang, J., Liu, S., Jiang, Z., and Jiang, B. (2010). "Monitoring the change of urban wetland using high spatial resolution remote sensing data." International Journal of Remote Sensing, Vol. 31, No. 7, pp. 1717-1731. https://doi.org/10.1080/01431160902926608
  52. Zhou, Q., Li, B., and Kurban, A. (2008). "Trajectory analysis of land cover change in arid environment of China." International Journal of Remote Sensing, Vol. 29, No. 4, pp. 1093-1107. https://doi.org/10.1080/01431160701355256