Detection of forest clear-cuts with shuttle radar topography mission (SRTM) and tandem-x inSAR data

Remote Sensing

Volumn 5, Issue 11, 2013, Pages 5449-5462

  Solberg, Svein ^a   Astrup, Rasmus ^a   Weydahl, Dan J ^b  

^a NORWEGIAN INSTITUTE OF BIOECONOMY RESEARCH   (Norway)

^b NORWEGIAN DEFENCE RESEARCH ESTABLISHMENT FFI   (Norway)

Author keywords

3D; Clear cut; Digital surface model; Forest monitoring; InSAR; Tandem X

Indexed keywords

DEFORESTATION; ERRORS; SYNTHETIC APERTURE RADAR;

3D; CLEAR-CUT; DIGITAL SURFACE MODELS; FOREST MONITORING; INSAR; TANDEM-X;

TRACKING RADAR;

DEFORESTATION; ERRORS; FOREST MANAGEMENT; MODELS; MONITORING; RADAR;

EID: 84904685673     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs5115449     Document Type: Article

References (39)

1. Kuntz, S. Potential of spaceborne SAR for monitoring the tropical environments. Trop. Ecol. 2010, 51, 3-10.
2. Lynch, J.; Maslin, M.; Balzter, H.; Sweeting, M. Choose satellites to monitor deforestation. Nature 2013, 496, 293-294.
3. Patenaude, G.; Milne, R.; Dawson, T.P. Synthesis of remote sensing approaches for forest carbon estimation: Reporting to the Kyoto Protocol. Environ. Sci. Policy 2005, 8, 161-178.
4. Frolking, S.; Palace, M.W.; Clark, D.B.; Chambers, J.Q.; Shugart, H.H.; Hurtt, G.C. Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure. J. Geophys. Res.: Biogeosci. 2009, 114, doi: 10.1029/2008JG000911.
5. Kuntz, S.; von Poncet, F.; Baldauf, T.; Plugge, D.; Kenter, B.; Köhl, M. A Multi-Stage Inventory Scheme for REDD Inventories in Tropical Countries. In Proceedings of the 34th ISRSE Conference, Sydney, NSW, Australia, 10-15 April 2011.
6. Global Forest Resources Assessments 2005. Available online: http://www.fao.org/docrep/ 008/a0400e/a0400e00.htm (accessed on 1 July 2013).
7. Willén, E.; Rosengren, M. Satellitdata för Skoglig Planering; Metria: Stockholm, Sweden, 2003.
8. Santoro, M.; Pantze, A.; Fransson, J.E.S.; Dahlgren, J.; Persson, A. Nation-wide clear-cut mapping in sweden using ALOS PALSAR strip images. Remote Sens. 2012, 4, 1693-1715.
9. Askne, J.I.H.; Dammert, P.B.G.; Ulander, L.M.H.; Smith, G. C-band repeat-pass interferometric SAR observations of the forest. IEEE Trans. Geosci. Remote Sens. 1997, 35, 25-35.
10. Solberg, S.; Astrup, R.; Lyytikainen-Saarenmaa, P.; Kantola, T.; Holopainen, M.; Weydahl, D.J.; Kaartinen, H. Testing TerraSAR-X for Forest Disturbance Mapping. In Proceedings of the 4th TerraSAR-X Science Team Meeting, Oberpfaffenhofen, Germany, 14-16 February 2011.
11. Hansen, M.C.; Shimabukuro, Y.E.; Potapov, P.; Pittman, K. Comparing annual MODIS and PRODES forest cover change data for advancing monitoring of Brazilian forest cover. Remote Sens. Environ. 2008, 112, 3784-3793
12. Yu, X.W.; Hyyppa, J.; Kaartinen, H.; Maltamo, M. Automatic detection of harvested trees and determination of forest growth using airborne laser scanning. Remote Sens. Environ. 2004, 90, 451-462.
13. Dwyer, E.; Pasquali, P.; Holecz, F.; Arino, O. Mapping forest damage caused by the 1999 Lothar Storm in Jura (France), using SAR Interferometry. ESA Earth Observ. Q 1999, 65, 28-29.
14. Olander, L.P.; Gibbs, H.K.; Steininger, M.; Swenson, J.J.; Murray, B.C. Reference scenarios for deforestation and forest degradation in support of REDD: A review of data and methods. Environ. Res. Lett. 2008, 3, doi: 10.1088/1748-9326/3/2/025011.
15. Rosenvald, R.; Lohmus, A. For what, when, and where is green-tree retention better than clear-cutting? A review of the biodiversity aspects. For. Ecol. Manag. 2008, 255, 1-15.
16. Baker, S.C.; Read, S.M. Variable retention silviculture in Tasmania's wet forests: Ecological rationale, adaptive management and synthesis of biodiversity benefits. Aust. For. 2011, 74, 218-232.
17. Englhart, S.; Jubanski, J.; Siegert, F. Quantifying dynamics in tropical peat swamp forest biomass with multi-temporal LiDAR datasets. Remote Sens. 2013, 5, 2368-2388.
18. Boutet, J.C.; Weishampel, J.F. Spatial pattern analysis of pre- and post-hurricane forest canopy structure in North Carolina, USA. Landsc. Ecol. 2003, 18, 553-559.
19. Vastaranta, M.; Korpela, I.; Uotila, A.; Hovi, A.; Holopainen, M. Mapping of snow-damaged trees based on bitemporal airborne LiDAR data. Eur. J. For. Res. 2012, 131, 1217-1228.
20. Solberg, S.; Naesset, E.; Hanssen, K.H.; Christiansen, E. Mapping defoliation during a severe insect attack on Scots pine using airborne laser scanning. Remote Sens. Environ. 2006, 102, 364-376.
21. Nystrom, M.; Holmgren, J.; Olsson, H. Change detection of mountain birch using multi-temporal ALS point clouds. Remote Sens. Lett. 2013, 4, 190-199.
22. Dolan, K.A.; Hurtt, G.C.; Chambers, J.Q.; Dubayah, R.O.; Frolking, S.; Masek, J.G. Using ICESat's Geoscience Laser Altimeter System (GLAS) to assess large-scale forest disturbance caused by hurricane Katrina. Remote Sens. Environ. 2011, 115, 86-96.
23. Deutscher, J.; Perko, R.; Gutjahr, K.; Hirschmugl, M.; Schardt, M. Mapping tropical rainforest canopy disturbances in 3D by COSMO-SkyMed spotlight InSAR-stereo data to detect areas of forest degradation. Remote Sens. 2013, 5, 648-663.
24. Balzter, H. Forest mapping and monitoring with interferometric synthetic aperture radar (InSAR). Prog. Phys. Geogr. 2001, 25, 159-177.
25. Rombach, M.; Moreira, J. Description and Applications of the Multipolarized Dual Band OrbiSAR-1 InSAR Sensor. In Proceedings of the IEEE International Radar Conference, Adelaide, SA, Australia, 3-5 September 2003.
26. Neeff, T.; Dutra, L.V.; dos Santos, J.R.; Freitas, C.D.; Araujo, L.S. Tropical forest measurement by interferometric height modeling and P-band radar backscatter. For. Sci. 2005, 51, 585-594.
27. Balzter, H.; Rowland, C.S.; Saich, P. Forest canopy height and carbon estimation at Monks Wood National Nature Reserve, UK, using dual-wavelength SAR interferometry. Remote Sens. Environ. 2007, 108, 224-239.
28. Gama, F.F.; dos Santos, J.R.; Mura, J.C. Eucalyptus biomass and volume estimation using interferometric and polarimetric SAR data. Remote Sens. 2010, 2, 939-956.
29. Solberg, S.; Astrup, R.; Gobakken, T.; Næsset, E.; Weydahl, D.J. Estimating spruce and pine biomass with interferometric X-band SAR. Remote Sens. Environ. 2010, 114, 2353-2360.
30. Solberg, S.; Astrup, R.; Bollandsas, O.M.; Næsset, E.; Weydahl, D.J. Deriving forest monitoring variables from X-band InSAR SRTM height. Can. J. Remote Sens. 2010, 36, 68-79.
31. Solberg, S.; Astrup, R.; Breidenbach, J.; Nilsen, B.; Weydahl, D. Monitoring spruce volume and biomass with InSAR data from TanDEM-X. Remote Sens. Environ. 2013, 139, 60-67.
32. Weydahl, D.J.; Sagstuen, J.; Dick, O.B.; Ronning, H. SRTM DEM accuracy assessment over vegetated areas in Norway. Int. J. Remote Sens. 2007, 28, 3513-3527.
33. Chen, Y.; Shi, P.; Deng, L.; Li, J. Generation of a top-of-canopy Digital Elevation Model (DEM) in tropical rain forest regions using radargrammetry. Int. J. Remote Sens. 2007, 28, 4345-4349.
34. Perko, R.; Raggam, H.; Deutscher, J.; Gutjahr, K.; Schardt, M. Forest assessment using high resolution SAR data in X-band. Remote Sens. 2011, 3, 792-815.
35. Karjalainen, M.; Kankare, V.; Vastaranta, M.; Holopainen, M.; Hyyppa, J. Prediction of plot-level forest variables using TerraSAR-X stereo SAR data. Remote Sens. Environ. 2012, 117, 338-347.
36. Rabus, B.; Eineder, M.; Roth, A.; Bamler, R. The shuttle radar topography mission-A new class of digital elevation models acquired by spaceborne radar. ISPRS J. Photogramm. Remote Sens. 2003, 57, 241-262.
37. The CGIAR Consortium for Spatial Information (CGIAR-CSI). SRTM 90 m Digital Elevation Data. Available online: http://srtm.csi.cgiar.org/index.asp (accessed on 20 July 2013).
38. Goldstein, R.M.; Werner, C.L. Radar interferogram filtering for geophysical applications. Geophys. Res. Lett. 1998, 25, 4035-4038.
39. Way, J.; Paris, J.; Kasischke, E.; Slaughter, C.; Viereck, L.; Christensen, N.; Dobson, M.C.; Ulaby, F.; Richards, J.; Milne, A.; et al. The effect of changing environmental-conditions on microwave signatures of forest ecosystems: Preliminary-results of the March 1988 Alaskan aircraft SAR experiment. Int. J. Remote Sens. 1990, 11, 1119-1144.