DOI QR코드

DOI QR Code

Improvement of MODIS land cover classification over the Asia-Oceania region

아시아-오세아니아 지역의 MODIS 지면피복분류 개선

  • Park, Ji-Yeol (Department of Atmospheric Sciences, Kongju National University) ;
  • Suh, Myoung-Seok (Department of Atmospheric Sciences, Kongju National University)
  • Received : 2015.01.05
  • Accepted : 2015.02.03
  • Published : 2015.04.30

Abstract

We improved the MODerate resolution Imaging Spectroradiometer (MODIS) land cover map over the Asia-Oceania region through the reclassification of the misclassified pixels. The misclassified pixels are defined where the number of land cover types are greater than 3 from the 12 years of MODIS land cover map. The ratio of misclassified pixels in this region amounts to 17.53%. The MODIS Normalized Difference Vegetation Index (NDVI) time series over the correctly classified pixels showed that continuous variation with time without noises. However, there are so many unreasonable fluctuations in the NDVI time series for the misclassified pixels. To improve the quality of input data for the reclassification, we corrected the MODIS NDVI using Correction based on Spatial and Temporal Continuity (CSaTC) developed by Cho and Suh (2013). Iterative Self-Organizing Data Analysis (ISODATA) was used for the clustering of NDVI data over the misclassified pixels and land cover types was determined based on the seasonal variation pattern of NDVI. The final land cover map was generated through the merging of correctly classified MODIS land cover map and reclassified land cover map. The validation results using the 138 ground truth data showed that the overall accuracy of classification is improved from 68% of original MODIS land cover map to 74% of reclassified land cover map.

본 연구에서는 MODerate resolution Imaging Spectroradiometer (MODIS) 지면피복 분류자료(MCD12Q1)에서 분류오류로 판단되는 화소들을 재분류함으로써 분류 정확도를 개선하였다. 최근 12년(2001-2012)간의 MODIS 지면피복 분류자료에서 지면피복 유형이 3개 이상으로 분류된 화소는 분류상에 오류가 있다고 판단하여 지면피복 재분류 화소로 선정하였다. 지면피복 재분류를 위해 공간해상도는 1 km이고 시간주기는 8일인 MODIS Normalized Difference Vegetation Index (NDVI) 자료를 이용하였다. NDVI 자료 중 구름 등으로 오염된 화소를 보정하기 위해 시 공간 연속성을 이용한 보정기법인 Correction based on Spatial and Temporal Continuity (CSaTC) 기법을 이용하였다. 보정된 NDVI 자료를 1개월 주기로 합성한 후 분류 오류로 판단된 화소들에 대해 Iterative Self-Organizing Data Analysis (ISODATA) 기법으로 군집화를 수행하였다. 각 군집별 식생 계절변동 특성을 고려하여 지면피복을 분류한 후 정상으로 판정된 MODIS 지면피복과 합성하여 최종 지면피복 재분류 자료를 산출하였다. 분류 정확도는 GPS를 이용한 현장관측 자료와 유럽우주국의 지상검증참조자료 등 총 138개 지상 관측자료를 이용하여 검증을 수행하였다. 2012년 MODIS 지면피복 분류자료의 정확도는 약 68%이었으나 본 연구에서 재분류한 지면피복자료의 정확도는 약 74%로 나타나 일부 화소들에서 분류 정확도가 개선되었다.

Keywords

References

  1. Anderson, J.R., E.E. Hardy, J.T. Roach, and R.E. Witmer, 1976. A land use and land cover classification system for use with remote sensor data, U.S. Geological Survey Professional Paper, 964.
  2. Bontemps, S., P. Defourny, E.V. Bogaert, O. Arino, V. Kalogirou, and J.R. Perez, 2011. GLOBCOVER 2009-Products description and validation report, European Space Agency.
  3. Brown, D.G., B.C. Pijanowski, and J.D. Duh, 2000. Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA, Journal of Environmental Management, 59(4): 247-263. https://doi.org/10.1006/jema.2000.0369
  4. Chase, T.N., R.A. Pielke Sr, T.G.F. Kittel, R.R. Nemani, and S.W. Running, 2000. Simulated impacts of historical land cover changes on global climate in northern winter, Climate Dynamics, 16(2-3): 93-105. https://doi.org/10.1007/s003820050007
  5. Cho, A-R. and M.S. Suh, 2013. Detection of contaminated pixels based on the short-term continuity of NDVI and correction using spatiotemporal continuity, Asia-Pacific Journal of Atmospheric Sciences, 49(4): 511-525. https://doi.org/10.1007/s13143-013-0045-7
  6. Friedl, M.A., D. Sulla-Menashe, B. Tan, A. Schneider, N. Ramankutty, A. Sibley, and X. Huang, 2010. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets, Remote Sensing of Environment, 114(1): 168-182. https://doi.org/10.1016/j.rse.2009.08.016
  7. Ge, J., J. Qi, B.M. Lofgren, N. Moore, N. Torbick, and J.M. Olson, 2007. Impacts of land use/cover classification accuracy on regional climate simulations, Journal of Geophysical Research: Atmospheres, 112: 1984-2012.
  8. Hansen, M.C., R.S. DeFries, J.R. Townshend, and R. Sohlberg, 2000. Global land cover classification at 1 km spatial resolution using a classification tree approach, International Journal of Remote Sensing, 21(6-7): 1331-1364. https://doi.org/10.1080/014311600210209
  9. Herold, M., P. Mayaux, C.E. Woodcock, A. Baccini, and C. Schmullius, 2008. Some challenges in global land cover mapping: An assessment of agreement and accuracy in existing 1 km datasets, Remote Sensing of Environment, 112(5): 2538-2556. https://doi.org/10.1016/j.rse.2007.11.013
  10. Huang, S. and F. Siegert, 2006. Land cover classification optimized to detect areas at risk of desertification in North China based on SPOT VEGETATION imagery, Journal of Arid Environments, 67(2): 308-327. https://doi.org/10.1016/j.jaridenv.2006.02.016
  11. Kang, J.H., M.S. Suh, and C.H. Kwak, 2007. A comparison of the land cover data sets over Asian region: USGS, IGBP and UMD, Atmosphere, 17(2): 159-169.
  12. Kang, J.H., M.S. Suh, and C.H. Kwak, 2009. Classification of land cover over the Korean Peninsula using MODIS data, Atmosphere, 19(2): 169-182.
  13. Kang, J.H., M.S. Suh, and C.H. Kwak, 2010. Land cover classification over East Asian region using recent MODIS NDVI data (2006-2008), Atmosphere, 20(4): 415-426.
  14. Kim, S.I., K.S. Han, and K.J. Pi, 2011. The trend analysis of vegetation change applied to unsupervised classification over East Asia: using the NDVI 10-day data in 1999-2010, The Korean Society for GeoSpatial Information System, 19(4): 153-159.
  15. Loveland, T.R., B.C. Reed, J.F. Brown, D.O. Ohlen, Z. Zhu, L. Yang, and J.W. Merchant, 2000. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data, International Journal of Remote Sensing, 21(6): 1303-1330. https://doi.org/10.1080/014311600210191
  16. Masson, V., J.L. Champeaux, F. Chauvin, C. Meriguet, and R. Lacaze, 2003. A global database of land surface parameters at 1-km resolution in meteorological and climate models, Journal of climate, 16(9): 1261-1282. https://doi.org/10.1175/1520-0442(2003)16<1261:AGDOLS>2.0.CO;2
  17. McCallum, I., M. Obersteiner, S. Nilson, and A. Shivdenko, 2006. A spatial comparison of four satellite derived 1 km global land cover datasets, International Journal of Applied Earth Observation and Geoinformation, 8(4): 246-255. https://doi.org/10.1016/j.jag.2005.12.002
  18. Park, J.Y. and M.S. Suh, 2014. Characteristics of MODIS land-cover data sets over Northeast Asia for the recent 12 years(2001-2012), Korean Journal of Remote Sensing, 30(4): 511-524. https://doi.org/10.7780/kjrs.2014.30.4.9
  19. Ryu, J.H., K.S. Han, K.J. Pi, and M.J. Lee, 2013. Analysis of land cover change around desert areas of East Asia, Korean Journal of Remote Sensing, 29(1): 105-114. https://doi.org/10.7780/kjrs.2013.29.1.10
  20. Sellers, P.J., R.E. Dickinson, D.A. Randall, A.K. Betts, F.G. Hall, J.A. Berry, G.J. Collatz, A.S. Denning, H.A. Mooney, C.A. Nobre, N. Sato, C.B. Field, and A. Henderson-Sellers 1997. Modeling the exchanges of energy, water, and carbon between continents and the atmosphere, Science, 275(5299): 502-509. https://doi.org/10.1126/science.275.5299.502
  21. Suh, M.S., J.R. Lee, J.H. Kang, D.K. Lee and M.H. Ahn, 2005. On the relationship between seasonal change of vegetation and climate elements in East Asia, Journal of Korean Meteorological Society, 41(4): 557-570.
  22. Tchuente, A.T.K., J.L. Roujean, and S.M. De Jong, 2011. Comparison and relative quality assessment of the GLC2000, GLOBCOVER, MODIS and ECOCLIMAP land cover data sets at the African continental scale, International Journal of Applied Earth Observation and Geoinformation, 13(2): 207-219. https://doi.org/10.1016/j.jag.2010.11.005
  23. Verburg, P.H., K.Neumann, and L. Nol, 2011. Challenges in using land use and land cover data for global change studies, Global Change Biology, 17(2): 974-989. https://doi.org/10.1111/j.1365-2486.2010.02307.x
  24. Wang, Q. and J.D. Tenhunen, 2004. Vegetation mapping with multitemporal NDVI in North Eastern China transect (NECT), International Journal of Applied Earth Observation and Geoinformation, 6(1): 17-31. https://doi.org/10.1016/j.jag.2004.07.002

Cited by

  1. Impact of Urban Canopy and High Horizontal Resolution on Summer Convective Rainfall in Urban Area: A case Study of Rainfall Events on 16 August 2015 vol.26, pp.1, 2016, https://doi.org/10.14191/Atmos.2016.26.1.141
  2. High-resolution modeling study of an isolated convective storm over Seoul Metropolitan area pp.1436-5065, 2019, https://doi.org/10.1007/s00703-019-0657-2
  3. Accuracy Assessment of Global Land Cover Datasets in South Korea vol.34, pp.4, 2015, https://doi.org/10.7780/kjrs.2018.34.4.3
  4. Urban Effect on Sea-Breeze-Initiated Rainfall: A Case Study for Seoul Metropolitan Area vol.12, pp.11, 2015, https://doi.org/10.3390/atmos12111483