Table of Contents Author Guidelines Submit a Manuscript
Journal of Sensors
Volume 2016 (2016), Article ID 7165326, 7 pages
http://dx.doi.org/10.1155/2016/7165326
Research Article

Improved Vegetation Profiles with GOCI Imagery Using Optimized BRDF Composite

1Electronics and Telecommunications Research Institute (ETRI), 218 Gajeongno, Yuseong-gu, Daejeon 305-700, Republic of Korea
2Department of Geoinformatic Engineering, Pukyong National University, Daeyeon-3 Nam-Gu, Busan 608-737, Republic of Korea
3Korea Aerospace Research Institute (KARI), 169-84 Gwahak-ro, Yuseong-gu, Daejeon 305-806, Republic of Korea

Received 27 November 2015; Revised 30 December 2015; Accepted 31 January 2016

Academic Editor: Chiman Kwan

Copyright © 2016 Sang-il Kim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. D. Tarpley, S. R. Schneider, and R. L. Money, “Global vegetation indices from the NOAA-7 meteorological satellite,” Journal of Climate & Applied Meteorology, vol. 23, no. 3, pp. 491–494, 1984. View at Publisher · View at Google Scholar · View at Scopus
  2. C. O. Justice, J. R. G. Townshend, B. N. Holben, and C. J. Tucker, “Analysis of the phenology of global vegetation using meteorological satellite data,” International Journal of Remote Sensing, vol. 6, no. 8, pp. 1271–1318, 1985. View at Publisher · View at Google Scholar · View at Scopus
  3. C. J. Tucker, “Red and photographic infrared linear combinations for monitoring vegetation,” Remote Sensing of Environment, vol. 8, no. 2, pp. 127–150, 1979. View at Publisher · View at Google Scholar · View at Scopus
  4. R. B. Myneni, F. G. Hall, P. J. Sellers, and A. L. Marshak, “The interpretation of spectral vegetation indexes,” IEEE Transactions on Geoscience and Remote Sensing, vol. 33, no. 2, pp. 481–486, 1995. View at Publisher · View at Google Scholar · View at Scopus
  5. C. Justice, A. Belward, J. Morisette, P. Lewis, J. Privette, and F. Baret, “Developments in the ‘validation’ of satellite sensor products for the study of the land surface,” International Journal of Remote Sensing, vol. 21, no. 17, pp. 3383–3390, 2000. View at Publisher · View at Google Scholar · View at Scopus
  6. A. Huete, K. Didan, T. Miura, E. P. Rodriguez, X. Gao, and L. G. Ferreira, “Overview of the radiometric and biophysical performance of the MODIS vegetation indices,” Remote Sensing of Environment, vol. 83, no. 1-2, pp. 195–213, 2002. View at Publisher · View at Google Scholar · View at Scopus
  7. P. Maisongrande, B. Duchemin, and G. Dedieu, “VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products,” International Journal of Remote Sensing, vol. 25, no. 1, pp. 9–14, 2004. View at Publisher · View at Google Scholar · View at Scopus
  8. R. Fensholt, I. Sandholt, S. Stisen, and C. Tucker, “Vegetation monitoring with the geostationary meteosat second generation seviri sensor,” Remote Sensing of Environment, vol. 101, pp. 212–229, 2006. View at Google Scholar
  9. Y. Tian, P. Romanov, Y. Yu, H. Xu, and D. Tarpley, “Analysis of vegetation index NDVI anisotropy to improve the accuracy of the GOES-R green vegetation fraction product,” in Proceedings of the 30th IEEE International Geoscience and Remote Sensing Symposium (IGARSS '10), pp. 2091–2094, Honolulu, Hawaii, USA, July 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. J. Jin, H. Jiang, X. Zhang, and Y. Wang, “Characterizing spatial-temporal variations in Vegetation phenology over the North-South transect of Northeast Asia based upon the MERIS terrestrial chlorophyll index,” Terrestrial, Atmospheric and Oceanic Sciences, vol. 23, no. 4, pp. 413–424, 2012. View at Publisher · View at Google Scholar · View at Scopus
  11. S. Liang, A. H. Strahler, M. J. Barnsley et al., “Multiangle remote sensing: past, present and future,” Remote Sensing Reviews, vol. 18, no. 2, pp. 83–102, 2000. View at Google Scholar · View at Scopus
  12. S. R. Proud, Q. Zhang, C. Schaaf et al., “The normalization of surface anisotropy effects present in SEVIRI reflectances by using the MODIS BRDF method,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 10, pp. 6026–6039, 2014. View at Publisher · View at Google Scholar · View at Scopus
  13. F. E. Nicodemus, “Directional reflectance and emissivity of an opaque surface,” Applied Optics, vol. 4, no. 7, pp. 767–773, 1965. View at Publisher · View at Google Scholar
  14. M. J. Barnsley, A. H. Strahler, K. P. Morris, and J. P. Muller, “Sampling the surface bidirectional reflectance distribution function (BRDF): 1. Evaluation of current and future satellite sensors,” Remote Sensing Reviews, vol. 8, no. 4, pp. 271–311, 1994. View at Publisher · View at Google Scholar · View at Scopus
  15. C. B. Schaaf, F. Gao, A. H. Strahler et al., “First operational BRDF, albedo nadir reflectance products from MODIS,” Remote Sensing of Environment, vol. 83, no. 1-2, pp. 135–148, 2002. View at Publisher · View at Google Scholar · View at Scopus
  16. W. Wanner, A. H. Strahler, B. Hu et al., “Global retrieval of bidirectional reflectance and albedo over land from EOS MODIS and MISR data: theory and algorithm,” Journal of Geophysical Research: Atmospheres, vol. 102, no. 14, pp. 17143–17161, 1997. View at Publisher · View at Google Scholar · View at Scopus
  17. F. Gao, C. B. Schaaf, A. H. Strahler, and W. Lucht, “Using a multikernel least-variance approach to retrieve and evaluate albedo from limited bidirectional measurements,” Remote Sensing of Environment, vol. 76, no. 1, pp. 57–66, 2001. View at Publisher · View at Google Scholar · View at Scopus
  18. W. Lucht and P. Lewis, “Theoretical noise sensitivity of BRDF and albedo retrieval from the EOS-MODIS and MISR sensors with respect to angular sampling,” International Journal of Remote Sensing, vol. 21, no. 1, pp. 81–98, 2000. View at Publisher · View at Google Scholar · View at Scopus
  19. B. Uudus, K.-A. Park, K.-R. Kim, J. Kim, and J.-H. Ryu, “Diurnal variation of NDVI from an unprecedented high-resolution geostationary ocean colour satellite,” Remote Sensing Letters, vol. 4, no. 7, pp. 639–647, 2013. View at Publisher · View at Google Scholar · View at Scopus
  20. J.-M. Yeom and H.-O. Kim, “Feasibility of using Geostationary Ocean Colour Imager (GOCI) data for land applications after atmospheric correction and bidirectional reflectance distribution function modelling,” International Journal of Remote Sensing, vol. 34, no. 20, pp. 7329–7339, 2013. View at Publisher · View at Google Scholar · View at Scopus
  21. J. M. Yeom and H. O. Kim, “Comparison of NDVIs from GOCI and MODIS data towards improved assessment of crop Temporal dynamics in the case of paddy rice,” Remote Sensing, vol. 7, no. 9, pp. 11326–11343, 2015. View at Publisher · View at Google Scholar
  22. J. M. Yeom, J. G. Ko, and H. O. Kim, “Application of GOCI-derived vegetation index profiles to estimation of paddy rice yield using the GRAMI rice model,” Computers and Electronics in Agriculture, vol. 118, pp. 1–8, 2015. View at Publisher · View at Google Scholar
  23. N. Gobron, F. Melin, B. Pinty, and M. M. Verstrasete, “SeaWiFS for global biosphere applications,” in Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, vol. 5, pp. 2238–2240, Sydney, Australia, July 2001. View at Publisher · View at Google Scholar
  24. M. E. Brown, J. E. Prinzon, K. Didan, J. T. Morisette, and C. J. Tucker, “Evaluation of the consistency of long-term NDVI time series derived from AVHRR, SPOT-vegetation, SeaWiFS, MODIS, and Landsat ETM+ sensors,” IEEE Transactions on Geoscience and Remote Sensing, vol. 44, no. 7, pp. 1787–1793, 2006. View at Publisher · View at Google Scholar
  25. R. Fensholt, A. Anyamba, S. Huber et al., “Analysing the advantages of high temporal resolution geostationary msg seviri data compared to polar operational environmental satellite data for land surface monitoring in Africa,” International Journal of Applied Earth Observation and Geoinformation, vol. 13, no. 5, pp. 721–729, 2011. View at Publisher · View at Google Scholar · View at Scopus
  26. Korea Meteorological Administration (KMA), Weather Almanac 2014, 2015.
  27. R. W. Saunders and K. T. Kriebel, “An improved method for detecting clear sky and cloudy radiances from AVHRR data,” International Journal of Remote Sensing, vol. 9, no. 1, pp. 123–150, 1988. View at Publisher · View at Google Scholar · View at Scopus
  28. E. F. Vermote, D. Tanré, J. L. Deuzé, M. Herman, and J.-J. Morcrette, “Second simulation of the satellite signal in the solar spectrum, 6S: an overview,” IEEE Transactions on Geoscience and Remote Sensing, vol. 35, no. 3, pp. 675–686, 1997. View at Publisher · View at Google Scholar · View at Scopus
  29. M. Wang, “An efficient method for multiple radiative transfer computations and the lookup table generation,” Journal of Quantitative Spectroscopy and Radiative Transfer, vol. 78, no. 3-4, pp. 471–480, 2003. View at Publisher · View at Google Scholar · View at Scopus
  30. A. S. L. Nunes, A. R. S. Marcal, and R. A. Vaughan, “Fast over-land atmospheric correction of visible and near-infrared satellite images,” International Journal of Remote Sensing, vol. 29, no. 12, pp. 3523–3531, 2008. View at Publisher · View at Google Scholar · View at Scopus
  31. A. Lyapustin, J. Martonchik, Y. Wang, I. Laszlo, and S. Korkin, “Multiangle implementation of atmospheric correction (MAIAC): 1. Radiative transfer basis and look-up tables,” Journal of Geophysical Research: Atmospheres, vol. 116, no. 3, Article ID D03210, 2011. View at Publisher · View at Google Scholar · View at Scopus
  32. J.-L. Roujean, M. Leroy, and P.-Y. Deschamps, “A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data,” Journal of Geophysical Research, vol. 97, no. 18, pp. 20–468, 1992. View at Google Scholar · View at Scopus
  33. F. Gao, C. B. Schaaf, A. H. Strahler, Y. Jin, and X. Li, “Detecting vegetation structure using a kernel-based BRDF model,” Remote Sensing of Environment, vol. 86, no. 2, pp. 198–205, 2003. View at Publisher · View at Google Scholar · View at Scopus
  34. W. Lucht, C. B. Schaaf, and A. H. Strahler, “An algorithm for the retrieval of albedo from space using semiempirical BRDF models,” IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 2, pp. 977–998, 2000. View at Publisher · View at Google Scholar · View at Scopus