DOI QR코드

DOI QR Code

Analysis of MODIS LAI and NDVI Patterns of Broad-leaved Trees by the Timesat Program on the Korean Peninsula

Timesat 프로그램에 의한 한반도 활엽수의 지역별 MODIS LAI 및 NDVI 패턴 분석

  • Seo, Dae Kyo (Department of Smart ICT Convergence, Konkuk University) ;
  • Lee, Jeong Min (Department of Advanced Technology Fusion, Konkuk University) ;
  • Lim, Ye Seul (Plant Conservation Division, Korea National Arboretum) ;
  • Han, Sang Won (Department of Civil Engineering, Konkuk University) ;
  • Pyeon, Mu Wook (Department of Civil Engineering, Konkuk University)
  • 서대교 (건국대학교 일반대학원 스마트ICT융합학과) ;
  • 이정민 (건국대학교 신기술융합학과) ;
  • 임예슬 (국립수목원 산림자원보존과) ;
  • 한상원 (건국대학교 토목공학과) ;
  • 편무욱 (건국대학교 인프라시스템공학과)
  • Received : 2017.02.20
  • Accepted : 2017.05.23
  • Published : 2017.06.30

Abstract

This paper analyzed MODIS data from 2006 to 2013 to determine relationship between meteorological changes and vegetation index. The experimental area was divided into the northern, central and southern regions according to the regional characteristics, and the smoothed MODIS LAI and NDVI were obtained using Timesat. In the case of precipitation, MODIS NDVI had correlation coefficients of 0.66, 0.44 and 0.35 in the northern, central and southern regions and the correlation was the highest in the northern region. In the case of temperature, MODIS LAI had correlation coefficients of 0.66, 0.64 and 0.68, and MODIS NDVI had 0.89, 0.89 and 0.80. The correlation of MODIS NDVI was higher and showed similar positive correlation regardless of region. In addition, The accuracy between Timesat plant seasonal start and actual plant seasonal start in MODIS NDVI was higher than MODIS LAI. The average error in MODIS LAI was 19 days in the central region and 20 days in the southern region. And the average error in MODIS NDVI was 6 days in the central region and 8 days in the southern region.

2006년부터 2013년까지의 환경위성 자료인 MODIS자료를 대상으로 기상변화와 식생지수와의 관계를 분석하였다. 실험지역은 한반도를 북부, 중부 및 남부로 나누어 지역특성에 따라 분석하였으며, Timesat을 활용하여 평활화된 MODIS LAI 및 NDVI를 획득하였다. 강수량과 MODIS NDVI의 경우 0.66, 0.44, 0.35로 MODIS LAI보다 높은 상관성을 나타냈으며, 북부에서의 상관성이 가장 높았다. 기온의 경우 MODIS LAI는 북부, 중부 및 남부에서 0.66, 0.64, 0.68의 상관계수값을 가졌고, MODIS NDVI의 경우 0.89, 0.89, 0.80의 상관계수 값을 나타냈다. MODIS NDVI의 상관성이 더 높았으며, 지역에 상관없이 유사한 양의 상관성을 나타냈다. 또한 Timesat을 통해 획득한 식물계절의 시작일과 실제 식물계절의 시작일을 비교한 결과, MODIS NDVI의 정확도가 높았다. MODIS LAI에서의 오차의 경우 중부에서 평균 19일, 남부에서 평균 20일이었고, MODIS NDVI에서의 오차의 경우 중부에서 평균 6일, 남부에서 평균 8일을 나타냈다.

Keywords

Acknowledgement

Supported by : 산업통상자원부

References

  1. Asner, G. P., Nepstad, D., Cardinot, G. and Ray, D., 2004, Drought stress and carbon uptake in an Amazon forest measured with spaceborne imaging spectroscopy, Proceedings of the National Academy of Sciences, Vol. 101, No. 16, pp. 6039-6044. https://doi.org/10.1073/pnas.0400168101
  2. Chen, J., Jonsson, P., Tamura, M., Gu, Z., Matsushita, B. and Eklundh, L., 2004, A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter, Remote Sensing of Environment, Vol. 91, No. 3, pp. 332-344. https://doi.org/10.1016/j.rse.2004.03.014
  3. Deering, D.W., 1978, Rangeland reflectance characteristics measured by aircraft and spacecraft sensors, Ph.D. Dissertation, Texas A & M University, p. 338.
  4. Feng, G., Jeffrey, T. M., Robert, E. W. and Jeff, P., 2008, An Algorithm to Produce Temporally and Spatially Continuous MODIS-LAI Time Series, IEEE Geoscience and Remote Sensing Letters, Vol. 5, No. 1, pp. 60-64. https://doi.org/10.1109/LGRS.2007.907971
  5. Ha, R., Shin, H. J., Park, G. A. and Kim, S. J., 2008, Assessment of MODIS leaf index (LAI) influence on the Penman-Monteith evaportranspiration of SLURP model, Journal of the Korean Society of Civil Engineers, Vol. 28, No. 5, pp. 495-504.
  6. Ha, R., Shin, H. J., Park, G. A., Hong, W. Y. and Kim, S. J., 2008, The evaluation of application to MODIS LAI (leaf area index) product, Journal of the Korean Association of Geographic Information Studies, Vol. 11, No. 2, pp. 61-72.
  7. Hong, W. Y., Park, G. A., Jeong, I. K. and Kim, S. J., 2010, Development of a grid-based daily watershed runoff model and the evaluation of its applicability, Journal of the Korean Society of Civil Engineers, Vol. 30, No. 5, pp. 459-469.
  8. Jonsson, P. and Eklundh, L., 2002, Seasonality extraction and noise removal by function fitting to time-series of satellite sensor data, IEEE Transactions of Geoscience and Remote Sensing, Vol. 40, No. 8, pp. 1824-1832. https://doi.org/10.1109/TGRS.2002.802519
  9. Jonsson, P. and Eklundh, L., 2004, TIMESAT-a program for analyzing time-series of satellite sensor data, Computers & Geosciences, Vol. 30, No. 8, 833-845. https://doi.org/10.1016/j.cageo.2004.05.006
  10. Jung, M. H., 2012, Automatic Change Detection of MODIS NDVI using Artificial Neural Networks, The Institute of Electronics Engineers of Korea - Computer and Information, Vol. 49, No. 2, pp. 83-89. https://doi.org/10.5573/ieek.2012.49.10.083
  11. Kim, N. S., Cho, Y. C., Oh, S. H., Kwon, H. J. and Kim, G. S., 2014, A phenology modeling using MODIS time series data in South Korea, Journal of the Korean Society of Limnology, Vol. 47, No. 3, pp. 186-193.
  12. La, H. P., Patrick, T. R., Park, B. W. and Eo, Y. D., 2013, Analysis of the relationship between MODIS NDVI, LAI and rainfall in the forest region of Rwanda, International Journal of Digital Content Technology and its Applications, Vol. 7, No. 8, pp. 559-569. https://doi.org/10.4156/jdcta.vol7.issue8.63
  13. Lee, D. K., Park, C. and Oh, Y. C., 2010, Projected spatial-temporal changes in carbon reductions of soil and vegetation in South Korea under climate change, Journal of the Korean Society of Rural Planning, Vol. 16, No. 4, pp. 109-116.
  14. Lee, M. J. and Han, K. S., 2010, Vegetation spatial distribution analysis of Tundra-Taiga boundary using MODIS LAI data, Journal of the Korean Spatial Information Society, Vol. 18, No. 5, pp. 27-36.
  15. Li, M., Wu, Z., Qin, L. and Meng, X., 2011, Extracting vegetation phenology metrics in Changbai Mountains using an improved logistic model, Chinese Geographical Science, Vol. 21, No. 3, pp. 304-311. https://doi.org/10.1007/s11769-011-0471-3
  16. Park, M. J., Shin, H. J., Park, J. Y., Park, G. A. and Kim, S. J., 2010, Application of SWAT-K considering climate change, Journal of Hydroenvironment Research, Vol. 43, No. 7, pp. 31-39.
  17. Reeves, M. C., Winslow, J. C. and Running, S. W., 2002, Mapping weekly rangeland vegetation productivity using MODIS data, Proc. of First Vitual Global Conference on Organic Beef Cattle Production, Embrapa, Concordia, Brazil, pp. 90-105.