Table of Contents
ISRN Forestry
Volume 2013, Article ID 529193, 8 pages
http://dx.doi.org/10.1155/2013/529193
Research Article

Simple Method of Forest Type Inventory by Joining Low Resolution Remote Sensing of Vegetation Indices with Spatial Information from the Corine Land Cover Database

1Department of Environmental Engineering, Warsaw University of Technology, Ulica Nowowiejska 20, 00-653 Warsaw, Poland
2Space Research Centre, Polish Academy of Sciences, Ulica Bartycka 18A, 00-716 Warsaw, Poland

Received 20 December 2012; Accepted 26 January 2013

Academic Editors: N. Frascaria-Lacoste, G. Martinez Pastur, and J. F. Negron

Copyright © 2013 Jarosław J. Zawadzki 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. Food and Agriculture Organization of the United Nations, http://www.fao.org/news/story/en/item/40893/icode/.
  2. M. C. Hansen, S. V. Stehman, P. V. Potapov et al., “Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data,” Proceedings of the National Academy of Sciences of the United States of America, vol. 105, no. 27, pp. 9439–9444, 2008. View at Publisher · View at Google Scholar · View at Scopus
  3. M. C. Hansen, S. V. Stehman, and P. V. Potapov, “Quantification of global gross forest cover loss,” Proceedings of the National Academy of Sciences of the United States of America, vol. 107, no. 19, pp. 8650–8655, 2010. View at Publisher · View at Google Scholar · View at Scopus
  4. M. C. Hansen, S. V. Stehman, and P. V. Potapov, “Reply to Wernick et al.: Global scale quantification of forest change,” Proceedings of the National Academy of Sciences of the United States of America, vol. 107, no. 38, p. E148, 2010. View at Publisher · View at Google Scholar · View at Scopus
  5. J. Zawadzki, C. J. Cieszewski, M. Zasada, and R. C. Lowe, “Applying geostatistics for investigations of forest ecosystems using remote sensing imagery,” Silva Fennica Monographs, vol. 39, no. 4, pp. 599–617, 2005. View at Google Scholar · View at Scopus
  6. F. Baret, K. Pavageau, Bacour et al., “Algorithm Theoretical Basis Document for MERIS Top of Atmosphere Land Prod. (TOA-VEG),” INRA-Novelties, 2009, http://www.brockmann-consult.de/beam/plugins.html.
  7. C. Bacour, F. Baret, D. Béal, M. Weiss, and K. Pavageau, “Neural network estimation of LAI, fAPAR, fCover and LAI×Cab, from top of canopy MERIS reflectance data: principles and validation,” Remote Sensing of Environment, vol. 105, no. 4, pp. 313–325, 2006. View at Publisher · View at Google Scholar · View at Scopus
  8. N. Gobron, B. Pinty, F. Mélin et al., “Evaluation of the MERIS/ENVISAT FAPAR product,” Advances in Space Research, vol. 39, no. 1, pp. 105–115, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. R. B. Myneni, S. Hoffman, Y. Knyazikhin et al., “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sensing of Environment, vol. 83, no. 1-2, pp. 214–231, 2002. View at Publisher · View at Google Scholar · View at Scopus
  10. J. W. Rouse, R. H. Haas, J. A. Schell, and D. W. Deering, “Monitoring vegetation systems in the great plains with ERTS,” in Proceedings of the 3rd ERTS Symposium. NASA SP-351, pp. 309–317, NASA, Washington, DC, USA, 1973.
  11. R. Nemani, L. Pierce, S. Running, and L. Band, “Forest ecosystem processes at the watershed scale: sensitivity to remotely-sensed leaf area index estimates,” International Journal of Remote Sensing, vol. 14, no. 13, pp. 2519–2534, 1993. View at Google Scholar · View at Scopus
  12. A. H. Strahler, C. E. Woodcock, and J. A. Smith, “On the nature of models in remote sensing,” Remote Sensing of Environment, vol. 20, no. 2, pp. 121–139, 1986. View at Google Scholar · View at Scopus
  13. P. Treitz and P. Howarth, “High spatial resolution remote sensing data for forest ecosystem classification: an examination of spatial scale,” Remote Sensing of Environment, vol. 72, no. 3, pp. 268–289, 2000. View at Publisher · View at Google Scholar · View at Scopus
  14. ESA—SMOS Earth Explorers, http://www.esa.int/esaLP/ESAS7C2VMOC_LPsmos_0.html.
  15. M. Bossard, J. Feranec, and J. Otahel, “Corine land cover technical guide—Addendum,” Technical Report 40, EEA, Copenhagen, Denmark, 2000. View at Google Scholar
  16. A. M. Jönsson, L. Eklundh, M. Hellström, L. Bärring, and P. Jönsson, “Annual changes in MODIS vegetation indices of Swedish coniferous forests in relation to snow dynamics and tree phenology,” Remote Sensing of Environment, vol. 114, no. 11, pp. 2719–2730, 2010. View at Google Scholar
  17. Q. Zhang, X. Xiao, B. Braswell et al., “Characterization of seasonal variation of forest canopy in a temperate deciduous broadleaf forest, using daily MODIS data,” Remote Sensing of Environment, vol. 105, no. 3, pp. 189–203, 2006. View at Publisher · View at Google Scholar · View at Scopus
  18. S. Lewiński, “Object based classification of middle resolution MODIS satellite image, first results,” Archiwum Fotogrametrii, Kartografii i Teledetekcji, vol. 21, pp. 211–219, 2010. View at Google Scholar
  19. S. Lewiński, “Applying fused multispectral and panchromatic data of Landsat ETM+ to object oriented classification,” in New Developments and Challenges in Remote Sensing, Millpress, Rotterdam, The Netherlands, 2007. View at Google Scholar