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Regional Scale Forest Mapping with Medium Resolution Satellite Data

This study delves into regional forest mapping using medium-resolution satellite data, focusing on vital parameters such as forest cover, dominant tree species, canopy age, and productivity estimates. It employs various datasets, including MODIS, Landsat TM/ETM+, and IRS-P6 AWiFS, to classify forest types and detect changes over time. Our analysis incorporates a mix of classification techniques and ground data to enhance accuracy. The findings emphasize the importance of sustainable logging and reforestation while addressing challenges faced by forest ecosystems in regions like Kirov Oblast.

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Regional Scale Forest Mapping with Medium Resolution Satellite Data

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  1. Regional Scale Forest Mappingwith Medium Resolution Satellite Data DmitryE. Aksenov ElenaS. Esipova Natalia V. Kuksina MikhailL. Karpachevsky

  2. Minimum set of information includes: • Forest cover • Dominant tree species • Age of the upper canopy • Productivity / growing stock estimation

  3. Options for the forest cover and tree species: • Modis data (like UMD TreeCover) +official forest survey data (lesoustroistvo) • Landsat TM/ETM+ classification • IRS-P6 AWiFS classification

  4. Example of Landsat ETM+

  5. dark coniferous (spruce, fir) ...and its classification by tree species pine mixed deciduous – dark coniferous deciduous (birch, aspen) cleacuts fire scars

  6. IRS-P6 AWiFS

  7. Retrospective data allow age classification Change detection MSS-TM Change detection TM-ETM+ Change detection ETM+-AWiFS MSS classification ~2000Landsat ETM+ GLCF 2007 Landsat TM IRS-P6 AWiFS ScanEx ~1980 Landsat MSS GLCF <1980 clearcuts in Landsat MSS ~1990 Landsat TM GLCF

  8. Landsat MSS (~1980)

  9. Landsat TM (~1990)

  10. Change detection MSS-TM

  11. Landsat TM (~1990)

  12. Landsat ETM+ (~2000)

  13. Change TM-ETM+

  14. Logging of 1980-2000

  15. Productivity / growing stockis still a problem • NDVI in combination with official data? • Radar data for sparse forests? • Landsat imagery classification in combination with ground data(kNN-method)?

  16. Kirov Oblast Mapping (2004-2006) Change detection MSS-TM Change detection TM-ETM+ Change detection ETM+-AWiFS MSS classification ~2000Landsat ETM+ GLCF 2007 Landsat TM IRS-P6 AWiFS ScanEx ~1980 Landsat MSS GLCF <1980 clearcuts in Landsat MSS ~1990 Landsat TM GLCF + Landsat ETM+ classification for tree species

  17. European Russia Mapping (2006-2007) Change detection MSS-TM Change detection TM-ETM+ Change detection Modis 2001-2006 MSS classification ~2000Landsat ETM+ GLCF 2006 Modis ~1980 Landsat MSS GLCF <1980 clearcuts in Landsat MSS ~1990 Landsat TM GLCF + UMD Treecover Forest of the USSR (1990)Modis classification (Bartalev et al.)

  18. European Russia Mapping (plans for 2008) Change detection MSS-TM Change detection TM-ETM+ Change detection ETM+-AWiFS MSS classification ~2000Landsat ETM+ GLCF 2007 Landsat TM IRS-P6 AWiFS ScanEx ~1980 Landsat MSS GLCF <1980 clearcuts in Landsat MSS ~1990 Landsat TM GLCF + IRS-P6 AWiFS classification for tree species

  19. Logging sustainability Planting Natural reforestation Forest resources • Economically unavailable • forests: • remote areas; • low-productive stands; • environmental limitations; • protected areas clearcuts selective logging forest fires pest outbreaks

  20. MSS-TM-ETM+ change detection Northern Kirov Oblast

  21. Lamdsat MSS, ~1980

  22. Landsat TM, ~1990

  23. Landsat ETM+, ~2000

  24. non-forest areas clearcuts 1990 – 2000 ther forest clearcuts 1980-1990

  25. non-forest areas clearcuts 1980 – 2000 гг. other forest

  26. non-forest lands old coniferous clearcuts 1980 – 2000 other forest

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