Exploiting growing stock volume maps for large scale forest resource assessment: Cross-comparisons of ASAR- and PALSAR-based GSV estimates with forest inventory in Central Siberia

Forests

Volumn 5, Issue 7, 2014, Pages 1753-1776

  Hüttich, Christian ^a   Korets, Mikhail ^b   Bartalev, Sergey ^c   Zharko, Vasily ^c   Schepaschenko, Dmitry ^d   Shvidenko, Anatoly ^d   Schmullius, Christiane ^a  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

^b SUKACHEV INSTITUTE OF FOREST   (Russian Federation)

^c Space Research Institute of the Russian Academy of Sciences ^*  (Russian Federation)

^d International Institute for Advanced System Analyses   (Austria)

Author keywords

ALOS PALSAR; Biomass; Boreal forest management; ENVISAT ASAR; Forest inventory; Land cover fragmentation; Siberia

Indexed keywords

BIOMASS; GEODETIC SATELLITES; REMOTE SENSING;

ALOS PALSAR; ENVISAT ASAR; FOREST INVENTORY; LAND COVER; SIBERIA;

FORESTRY;

ALOS; BOREAL FOREST; ENVISAT-1; FOREST INVENTORY; FOREST MANAGEMENT; FOREST RESOURCE; INTERDISCIPLINARY APPROACH; LAND COVER; MODIS; PALSAR; PARAMETERIZATION; REMOTE SENSING; SATELLITE DATA; SYNTHETIC APERTURE RADAR;

BIOMASS; FOREST MANAGEMENT; INVENTORIES; LAND; REMOTE SENSING; SATELLITES; SIBERIA;

SIBERIA;

EID: 84905501233     PISSN: None     EISSN: 19994907     Source Type: Journal    
DOI: 10.3390/f5071753     Document Type: Article

References (52)

1. Shvidenko, A.; Schepaschenko, D.; Nilsson, S.; Bouloui, Y. Semi-empirical models for assessing biological productivity of Northern Eurasian forests. Ecol. Model. 2007, 204, 163-179.
2. Gusti, M.; Jonas, M. Terrestrial full carbon account for Russia: Revised uncertainty estimates and their role in a bottom-up/top-down accounting exercise. Clim. Chang. 2010, 103, 159-174.
3. Dolman, J.; Shvidenko, A.; Schepaschenko, D.; Ciais, P.; Tchebakova, N.; Chen, T.; van der Molen, M.K.; Belelli Marchesini, L.; Maximov, T.C.; Maksyutov, S.; Schulze, E.-D. An Estimate of the Terrestrial Carbon Budget of Russia Using Inventory-Based, Eddy Covariance and Inversion Methods. Biogeosciences 2012, 9, 5323-5340.
4. Shvidenko, A.; Schepaschenko, D. Russia faces tough climate change challenges. Options 2011, 18-19.
5. Schepaschenko, D.; See, L.; Fritz, S.; McCallum, I.; Christian, S.; Perger, C.; Baccini, A.; Gallaun, H.; Kindermann, G.; Kraxner, F.; et al. Observing forest biomass globally. Earthzine 2012.
6. Shvidenko, A.; Schepaschenko, D.; McCallum, I.; Nilsson, S. Can the uncertainty of full carbon accounting of forest ecosystems be made acceptable to policymakers? Clim. Chang. 2010, 103, 137-157.
7. Gustafson, E.J.; Shvidenko, A.Z.; Sturtevant, B.R.; Scheller, R.M. Predicting global change effects on forest biomass and composition in south-central Siberia. Ecol. Appl. 2010, 20, 700-715.
8. Pereira, H.M.; Ferrier, S.; Walters, M.; Geller, G.N.; Jongman, R.H.G.; Scholes, R.J.; Bruford, M.W.; Brummitt, N.; Butchart, S.H.M.; Cardoso, A.C.; et al. Essential Biodiversity Variables. Science 2013, 339, 277-278.
9. Houghton, R.A.; Butman, D.; Bunn, A.G.; Krankina, O.N.; Schlesinger, P.; Stone, T.A. Mapping Russian forest biomass with data from satellites and forest inventories. Environ. Res. Lett. 2007, 2, 045032.
10. McRoberts, R.E.; Gobakken, T.; Næsset, E. Post-stratified estimation of forest area and growing stock volume using lidar-based stratifications. Remote Sens. Environ. 2012, 125, 157-166.
11. Powell, S.L.; Cohen, W.B.; Healey, S.P.R.; Kennedy, E.; Moisen, G.G.; Pierce, K.B.; Ohmann, J.L. Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches. Remote Sens. Environ. 2010, 114, 1053-1068.
12. Tomppo, E.O.; Gagliano, C.; de Natale, F.; Katila, M.; McRoberts, R.E. Predicting categorical forest variables using an improved k-Nearest Neighbour estimator and Landsat imagery. Remote Sens. Environ. 2009, 113, 500-517.
13. Tomppo, E.; Nilsson, M.; Rosengren, M.; Aalto, P.; Kennedy, P. Simultaneous use of Landsat-TM and IRS-1C WiFS data in estimating large area tree stem volume and aboveground biomass. Remote Sens. Environ. 2002, 82, 156-171.
14. Santoro, M.; Beer, C.; Cartus, O.; Schmullius, C.; Shvidenko, A.; McCallum, I.; Wegmüller, U.; Wiesmann, A. Retrieval of growing stock volume in boreal forest using hyper-temporal series of Envisat ASAR ScanSAR backscatter measurements. Remote Sens. Environ. 2010, 115, 490-507.
15. Santoro, M.; Cartus, O.; Fransson, J.; Shvidenko, A.; McCallum, I.; Hall, R.; Beaudoin, A.; Beer, C.; Schmullius, C. Estimates of forest growing stock volume for Sweden, central Siberia, and québec using envisat advanced synthetic aperture radar backscatter data. Remote Sens. 2013, 5, 4503-4532.
16. Goetz, S.J.; Baccini, A.; Laporte, N.T.; Johns, T.; Walker, W.; Kellndorfer, J.; Houghton, R.; Sun, M. Mapping and monitoring carbon stocks with satellite observations: A comparison of methods. Carbon Balance Manag. 2009, 4, doi:10.1186/1750-0680-4-2.
17. Cartus, O.; Kellndorfer, J.; Rombach, M.; Walker, W. Mapping canopy height and growing stock volume using airborne lidar, ALOS PALSAR and landsat ETM+. Remote Sens. 2012, 4, 3320-3345.
18. De Grandi, G.D.; Bouvet, A.; Lucas, R.M.; Shimada, M.; Monaco, S.; Rosenqvist, A. The KC PALSAR mosaic of the African continent: Processing issues and first thematic results. IEEE Trans. Geosci. Remote Sens. 2011, 49, 3593-3610.
19. Santoro, M.; Schmullius, C.; Pathe, C.; Schwilk, J. Pan-boreal mapping of forest growing stock volume using hyper-temporal Envisat ASAR ScanSAR backscatter data. In Proceedings of the 2012 IEEE International on Geoscience Remote Sensing Symposium (IGARSS), Munich, Germany, 22-27 July 2012; pp. 7204-7207.
20. Seifert, F.M. GlobBiomass-User Consultation Meeting. 2012. Available online: http://due.esrin.esa.int/meetings/meetings283.php (accessed on 25 July 2013).
21. Corona, P. Integration of forest mapping and inventory to support forest management. iForest-Biogeosci. For. 2010, 3, 59-64.
22. Wulder, M.A.; White, J.C.; Fournier, R.A.J.; Luther, E.; Magnussen, S. Spatially explicit large area biomass estimation: Three approaches using forest inventory and remotely sensed imagery in a GIS. Sensors 2008, 8, 529-560.
23. Blackard, J.; Finco, M.; Helmer, E.; Holden, G.; Hoppus, M.; Jacobs, D.; Lister, A.; Moisen, G.; Nelson, M.; Riemann, R. Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information. Remote Sens. Environ. 2008, 112, 1658-1677.
24. Ryan, B. Introduction to GEO. In Proceedings of the UNFCCC COP-18, Doha, Qatar, 26 November-7 December 2012.
25. Minayeva, L.Y. Forest inventory regulations of Russia. Mil. Tiprg. 1995, 1, 274.
26. Santoro, M.; Eriksson, L.; Askne, J.; Schmullius, C. Assessment of stand-wise stem volume retrieval in boreal forest from JERS-1 L-band SAR backscatter. Int. J. Remote Sens. 2006, 27, 3425-3454.
27. Shimada, M.; Ohtaki, T. Generating large-scale high-quality SAR mosaic datasets: Application to PALSAR data for global monitoring. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2010, 3, 637-656.
28. Rosenqvist, A.; Ogawa, T.; Shimada, M.; Igarashi, T. Initiating the ALOS Kyoto & Carbon Initiative. In Proceedings of the IEEE 2001 International Geoscience and Remote Sensing Symposium on IGARSS 2001 Scanning the Present and Resolving the Future, Sydney, NSW, Australia, 9-13 July 2001; Volume 1, pp. 546-548.
29. Bartalev, S.A.; Belward, A.S.; Erchov, D.V.; Isaev, A.S. A new SPOT4-VEGETATION derived land cover map of Northern Eurasia. Int. J. Remote Sens. 2003, 24, 1977-1982.
30. Zharko, V.O.; Bartalev, S.A.; Egorov, V.A. Evaluation of forest tree species composition based on the analysis of their seasonal reflectance dynamic using satellite data (in Russian). In Proceedings of the Tenth Annual All Russian Open Conference Actual Problems in Remote Sensing of the Earth from Space, Moscow, Russia, 12-16 November 2012; p. 386.
31. FFSR. Manual on forest inventory and planning in forest fund of Russia. Part 1. Organization of forest inventory and field works; Federal Forest Service of Russia: Moscow, Russia, 1995; pp. 174.
32. Prasad, M.; Iverson, L.R.; Liaw, A. Newer classification and regression tree techniques: Bagging and random forests for ecological prediction. Ecosystem 2006, 9, 181-199.
33. Gislason, P.; Benediktsson, J.; Sveinsson, J. Random Forests for land cover classification. Pattern Recognit. Lett. 2006, 27, 294-300.
34. Cutler, D.R.; Edwards, T.C.; Beard, K.H.; Cutler, A.; Hess, K.T.; Gibson, J.; Lawler, J.J. Random forests for classification in ecology. Ecology 2007, 88, 2783-2792.
35. Hüttich, C.; Herold, M.; Strohbach, B.J.; Dech, S. Integrating in situ-, Landsat-, and MODIS data for mapping in Southern African savannas: Experiences of LCCS-based land-cover mapping in the Kalahari in Namibia. Environ. Monit. Assess. 2010, 176, 531-547.
36. Simard, M.; Pinto, N.; Fisher, J.B.; Baccini, A. Mapping forest canopy height globally with spaceborne lidar. J. Geophys. Res. 2011, 116, 1-12.
37. Carreiras, J.; Melo, J.; Vasconcelos, M. Estimating the above-ground biomass in Miombo savanna woodlands (Mozambique, East Africa) using L-band synthetic aperture radar data. Remote Sens. 2013, 5, 1524-1548.
38. Breiman, L.; Friedman, J.H.; Olshen, R.A.; Stone, C.J. Classification and Regression Trees; CRC Press: Boca Raton, FL, USA, 1984; pp. 368.
39. Imhoff, M.L. Radar backscatter and biomass saturation: Ramifications for global biomass inventory. IEEE Trans. Geosci. Remote Sens. 1995, 33, 511-518.
40. Wagner, W. Large-scale mapping of boreal forest in SIBERIA using ERS tandem coherence and JERS backscatter data. Remote Sens. Environ. 2003, 85, 125-144.
41. Santoro, M.; Shvidenko, A.; Mccallum, I.; Askne, J.; Schmullius, C. Properties of ERS-1/2 coherence in the Siberian boreal forest and implications for stem volume retrieval. Remote Sens. Environ. 2007, 106, 154-172.
42. 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 Sens. Lett. 2014, 5, 55-64.
43. Bartalev, S.A.; Egorov, V.A.; Ershov, D.V.; Isaev, A.S.; Loupian, E.A.; Plotnikov, D.E.; Uvarov, I.A. The vegetation mapping over Russia using MODIS spectroradiometer satellite data. Contemp. Earth Remote Sens. Sp. 2011, 8, 285-302.
44. McGarigal, K.; Cushman, S.A.; Neel, M.C.; Ene, E. FRAGSTATS: Spatial pattern analysis program for categorical maps. Computer Software Program Produced by the Authors at the University of Massachusetts; University of Massachusets: Amherst, United States of America, 2002; p. 171.
45. Jaeger, J.A.G. Landscape division, splitting index, and effective mesh size: New measures of landscape fragmentation. Landsc. Ecol. 2000, 15, 115-130.
46. Rauste, Y. Multi-temporal JERS SAR data in boreal forest biomass mapping. Remote Sens. Environ. 2005, 97, 263-275.
47. Thiel, C.; Schmullius, C. Investigating the impact of freezing on the ALOS PALSAR InSAR phase over Siberian forests. Remote Sens. Lett. 2013, 4, 900-909.
48. Kasischke, E.S.; Tanase, M.A.; Bourgeau-Chavez, L.L.; Borr, M. Soil moisture limitations on monitoring boreal forest regrowth using spaceborne L-band SAR data. Remote Sens. Environ. 2011, 115, 227-232.
49. JAXA. New Global 50 m-Resolution PALSAR Mosaic and Forest/Non-Forest Map (2007-2010). Available online: http://www.eorc.jaxa.jp/ALOS/en/palsar_fnf/fnf_index.htm (accessed on 12 May 2014).
50. Kuemmerle, T.; Chaskovskyy, O.; Knorn, J.; Radeloff, V.C.; Kruhlov, I.; Keeton, W.S.; Hostert, P. Forest cover change and illegal logging in the Ukrainian Carpathians in the transition period from 1988 to 2007. Remote Sens. Environ. 2009, 113, 1194-1207.
51. Hain, H.; Ahas, R. The structure and estimated extent of illegal forestry in Estonia 1998-2003. Int. For. Rev. 2005, 7, 90-100.
52. Le Toan, T.; Quegan, S.; Davidson, M.W.J.; Balzter, H.; Paillou, P.; Papathanassiou, K.; Plummer, S.; Rocca, F.; Saatchi, S.; Shugart, H.; et al. The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle. Remote Sens. Environ. 2011, 115, 2850-2860.