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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2015, Vol. 12, No. 5, pp. 203-221

Current state and development prospects of satellite mapping methods of Russia’s vegetation cover

S.A. Bartalev 1 , V.A. Egorov 1 , V.O. Zharko 1 , E.A. Loupian 1 , D.E. Plotnikov 1 , S.A. Khvostikov 1 
1 Space Research Institute RAS, Moscow, Russia
This paper presents an overview of main research activities and obtained results of Space Research Institute of the Russian Academy of Sciences (IKI RAS) in the area of Russia’s vegetation cover mapping methods based on satellite Earth remote sensing data. A historical overview of the main stages of the methodology development and specific features of automated methods of mapping vegetation cover from satellite data developed by IKI RAS is presented. A description of thematic maps that have been produced up to date based on satellite data for the territory of Russia, characterising spatial distribution of land cover types and arable lands as well as dominant tree species and growing stock volumes of forests is presented. Promising research and development areas in the field of vegetation cover satellite monitoring methods are analyzed considering new technical capabilities of remote sensing systems.
Keywords: vegetation cover, remote sensing, satellite mapping methods
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References:

  1. Bartalev S.A., Egorov V.A., Ershov D.V., Isaev A.S., Loupian E.A., Plotnikov D.E., Uvarov I.A., Sputnikovoe kartografirovanie rastitel'nogo pokrova Rossii po dannym spektroradiometra MODIS (Russian land cover satellite mapping using MODIS spectroradiometer data), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2011a, Vol. 8, No. 4, pp. 285–302.
  2. Bartalev S.A., Egorov V.A., Loupian E.A., Plotnikov D.E., Uvarov I.A., Raspoznavanie pakhotnykh zemel' na osnove mnogoletnikh sputnikovykh dannykh spektroradiometra MODIS i lokal'no-adaptivnoi klassifikatsii (Arable lands recognition based on multi-annual MODIS spectroradiometer satellite data and locally-adaptive classification), Komp'yuternaya optika, 2011b, Vol. 35, No. 1, pp. 103–116.
  3. Bartalev S.A., Loupian E.A., Issledovaniya i razrabotki IKI RAN po razvitiyu metodov sputnikovogo monitoringa rastitel'nogo pokrova (R&D on methods for satellite monitoring of vegetation by the Russian Academy of Sciences’ Space Research Institute), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2013, Vol. 10, No. 1, pp. 197–214.
  4. Burtsev M.A., Mazurov A.A., Neishtadt I.A., Proshin A.A., Postroenie arkhiva sputnikovykh dannykh dlya analiza dinamiki rastitel'nosti (Creation of satellite data archive for the analysis of vegetation dynamics), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2006, Issue 3, Vol. 1, pp. 170–174.
  5. Vernadskii V.I., Biosfera i noosfera (Biosphere and Noosphere), Moscow: Nauka, 1989. 261 p.
  6. Zharko V.O., Bartalev S.A., Otsenka raspoznavaemosti drevesnykh porod lesa na osnove sputnikovykh dannykh o sezonnykh izmeneniyakh ikh spektral'no-otrazhatel'nykh kharakteristik (Forest tree species recognizability assessment based on satellite data on their spectral reflectance seasonal changes), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2014a, Vol. 11, No. 3, pp. 159–170.
  7. Zharko V.O., Bartalev S.A., Assimilyatsiya izmerenii zapasa stvolovoi drevesiny po sputnikovym dannym v model' dinamiki lesov dlya otsenki ikh vozrastnoi struktury (Assimilation of growing stock volume satellite measurements into forest dynamics model to estimate their age structure), 12 konferentsiya “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa” (12th Conf. ''Current Problems in Remote Sensing of the Earth from Space''), Moscow, 10–14 November 2014, Book of Abstracts, p. 359.
  8. Maksakovskii V.P., Geograficheskaya kartina mira. Kn. I: Obshchaya kharakteristika mira (Geographical picture of the world. Book I: General characteristic of the world), Moscow: Drofa, 2003, 496 p.
  9. Plotnikov D.E., Miklashevich T.S., Bartalev S.A., Vosstanovlenie vremennykh ryadov dannykh distantsionnykh izmerenii metodom polinomial'noi approksimatsii v skol'zyashchem okne peremennogo razmera (Using local polynomial approximation within moving window for remote sensing data time-series smoothing and data gaps recovery), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2014, Vol. 11, No. 2, pp. 103–110.
  10. Khovratovich T.S., Bartalev S.A., Zharko V.O., Metod otsenki zapasa stvolovoi drevesiny na osnove sovmestnogo ispol'zovaniya produktov dannykh ASAR i MODIS (Growing stock volume estimation method based on joint use of ASAR and MODIS data products), 11 konferentsiya “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa” (11th Conf. ''Current Problems in Remote Sensing of the Earth from Space'') Moscow, 11–15 November 2013, Book of Abstracts, p. 331.
  11. Arino O., Bicheron P., Achard F., Latham J., Witt R., Weber J.L., GlobCover: the most detailed portrait of Earth, ESA Bulletin - European Space Agency, 2008, No. 136, pp. 24–31.
  12. Bartalev S.A., Belward A., Ershov D.V., Isaev A.S., A New SPOT4-VEGETATION Derived Land Cover Map of Northern Eurasia, International Journal of Remote Sensing, 2003, Vol. 24, Issue 9, pp. 1977–1982.
  13. Bartalev S.A., Egorov V.A., Loupian E.A., Khvostikov S.A., A new locally-adaptive classification method LAGMA for large-scale land cover mapping using remote-sensing data, Remote Sensing Letters, 2014, Vol. 5, Issue 1, pp. 55–64.
  14. Bartholome E., Belward A., GLC2000: a new approach to global land cover mapping from Earth observation data, International Journal of Remote Sensing, 2005, Vol. 26, Issue 9, pp. 1959–1977.
  15. Belward A., The IGBP-DIS Global 1 Km Land Cover Data Set “DISCover”: Proposal and Implementation Plans: Report of the Land Recover Working Group of IGBP-DIS, IGBP-DIS, 1996.
  16. Chen Jun, Chen Jin, Liao A., Cao X., Chen L., Chen X., He C., Han G., Peng S., Lu M., Zhang W., Tong X., Mills J., Global land cover mapping at 30 m resolution: A POK-based operational approach, ISPRS Journal of Photogrammetry and Remote Sensing, 2015, Vol. 103, pp. 7–27.
  17. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets, Remote Sensing of Environment, 2010, Vol. 114, Issue 1, pp. 168-182.
  18. Hansen M., DeFries R., Townshend J.R.G., Sohlberg R., Global land cover classification at 1 km resolution using a decision tree classifier, International Journal of Remote Sensing, 2000, Vol. 21, Issue 6–7, pp. 1331–1365.
  19. Loveland T.R., Zhu Z., Ohlen D.O., Brown J.F., Reed B.C., Yang L., An analysis of the IGBP Global Land-Cover Characterization Process, Photogrammetric engineering and remote sensing, 1999, Vol. 65, No. 9, pp. 1021–1032.