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Estimation of surface soil properties in peatland using ALOS/PALSAR

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Abstract

By examining the area of the Sarobetsu Mire in northern Japan using ALOS/PALSAR data, we have clarified the backscattering behavior and characteristics of the L-band microwaves when used in the study of peatlands. We classified the vegetation into six categories and noted the differences in scattering intensity and incident-angle dependencies among these. The scattering intensity for HH and HV polarizations was greatest with sasa (dwarf bamboo) and reeds, and least with sphagnum. The incident-angle dependency with the HH polarization was higher for sasa and reed than for other vegetation types. Analysis of the polarization revealed that such differences among vegetation classes were reflected most clearly in the volume scattering characteristic. Applying simple and multiple regression analysis for the environmental factors of soil, hydrology, vegetation, and roughness against the backscatter coefficient, we also found stronger interrelations with soil factors such as bulk density, nitrogen and carbon content, and C/N ratio, and against the backscatter coefficient, than with either the roughness or vegetation. Based on such results, we clarified the unique scattering characteristics of peatlands in which scattering from the surface soil is more marked than that from other elements. We consequently estimated the spatial distribution of surface soil characteristics in peatland using the combined data available from L-band satellite SAR, aircraft laser (airborne LiDAR), and optical sensors.

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References

  • Boast CW, Kirkham D (1971) Auger hole seepage theory. Soil Sci Soc Am 35:365–373

    Google Scholar 

  • Bourgeau-Chavez LL, Kasischke ES, Brunzell SM, Mudd JP, Smith KB, Frick AL (2001) Analysis of space-borne SAR data for wetland mapping in Virginia riparian ecosystems. Int J Remote Sens 22:3665–3687

    Article  Google Scholar 

  • Cloude SR, Pottier E (1996) A review of target decomposition theorems in radar polarimetry. IEEE Trans Geosci Remote Sens 34:498–518

    Article  Google Scholar 

  • Dwivedi RS, Rao BRM, Bhattacharya S (1999) Mapping wetlands of the Sundaban Delta and its environs using ERS–1 SAR data. Int J Remote Sens 20:2235–2247

    Article  Google Scholar 

  • Freeman A, Durden SL (1998) A three-component scattering model for polarimetric SAR data. IEEE Trans Geosci Remote Sens 36:963–973

    Article  Google Scholar 

  • Fujita H, Kanoh S, Imai H (2003) The time series mapping and detecting area changed of dwarf bamboo in Kami-Sarobetsu Mire (in Japanese). Bull Bot Garden, Hokkaido University, p 43

  • Fujita H, Igarashi Y, Hotes S, Takada M, Inoue T, Kaneko M (2007) An inventory of the mires of Hokkaido, Japan-their development, classification, decline, and conservation. Plant Ecol. doi:10.1007/s11258-007-9267-z

  • Gafni A, Brooks K (1990) Hydraulic characteristics of four peatlands in Minnesota. Can J Soil Sci 70:239–253

    Article  Google Scholar 

  • Görres JH, Dichiaro MJ, Lyons JB, Amador JA (1998) Spatial and temporal patterns of soil biological activity in a forest and an old field. Soil Biol Biochem 30:219–230

    Article  Google Scholar 

  • Hokkaido Development Agency (1997) Environment of peatlands, environmental change survey report in Sarobetsu area (in Japanese). Hokkaido Development Agency, Sapporo, pp 158

  • Iisaka J (1998) Synthetic aperture radar image handbook (in Japanese). Asakura Publishing, Tokyo

    Google Scholar 

  • JAXA (2008) ALOS PALSAR level 1 product format description, vol 2, level 1.1/1.5, rev. K. http://www.eorc.jaxa.jp/ALOS/doc/format.htm. Accessed 3 Jan 2009

  • Kellner E, Halldin S (2002) Water budget and surface-layer water storage in a Sphagnum bog in central Sweden. Hydrol Processes 16:87–103

    Article  Google Scholar 

  • Kovacs JM, Vandenberg CV, Florse-Verdugo F (2006) Assessing fine beam RADARSAT–1 backscatter from a white mangrove canopy. Wetlands Ecol Manage 14:401–408

    Article  Google Scholar 

  • Martini IP, Cortizas AM, Chesworth W (2006) Peatlands: evolution and records of environmental and climate changes, 1st edn. Elsevier, Amsterdam

    Google Scholar 

  • Nakamura K, Shinsho H, Uratsuka S, Nadai A, Umehara T, Maeno H, Moriyama T (2005) Study on vegetation classification in Kushiro Wetland applied single temporal and dual-frequency and multi-polarimetry SAR data (in Japanese with English summary). J Remote Sens Jpn 25:13–31

    Google Scholar 

  • Nakase H, Sonou M, Nakazima K, Aizawa Y (2006) Restoring of farmland and wetland in Sarobetsu peatlands (in Japanese). J Jpn Soc Irrigation Drainage Reclam Eng 74:699–702

    Google Scholar 

  • Nilson M (1996) Estimation tree heights and stand volume using an airborne lidar system. Remote Sens Environ 56:1–7

    Article  Google Scholar 

  • Oguma H, Yamagata Y (1997) Classification of wetland vegetation with multi-temporal dual frequency SAR data (in Japanese with English summary). J Jpn Soc Photogramm Remote Sens 36:4–12

    Google Scholar 

  • Omasa K, Akiyama Y, Ishigami Y, Yoshimi K (2000) 3-D remote sensing of woody canopy height using a scanning helicopter-borne lidar system with high spatial resolution (in Japanese with English summary). J Remote Sens Jpn 20:34–46

    Google Scholar 

  • Ouchi K (2004) Principles of synthetic aperture radar for remote sensing (in Japanese). Tokyo Denki University Press, Tokyo

    Google Scholar 

  • Petrone RM, Price JS, Carey SK, Waddington JM (2004) Statistical characterization of the spatial variability of soil moisture in a cutover peatland. Hydrol Processes 18:41–52

    Article  Google Scholar 

  • Reynolds WD, Elrick DE (1987) A laboratory and numerical assessment of the Guelph permeameter method. Soil Sci 144:282–299

    Article  Google Scholar 

  • Robertson GP, Hutson MA, Evans FC, Tiedje JM (1988) Spatial variability in a successional plant community: patterns of nitrogen availability. Ecology 69:1517–1524

    Article  Google Scholar 

  • Romshoo SA, Shimada M, Igarashi T (2002) Peatland ecosystem characterization employing L-band SAR. In: Geoscience and remote sensing symposium, 2002. IGARSS ’02 IEEE International, pp 1795–1797

  • Rydin H, Jeglum J (2006) The biology of peatlands, 1st edn. Oxford University Press, Oxford

    Book  Google Scholar 

  • Shoshany M, Svoray T, Curran PJ, Foody GM, Perevolotsky A (2000) The relationship between ERS–2 SAR backscatter and soil moisture: generalization from a humid to semi-arid transect. Int J Remote Sens 21:2337–2343

    Article  Google Scholar 

  • Stiles WH, Ulaby FT (1980) The active and passive microwave response to snow parameters. 1. Wetness. J Geophys Res 85(C2):1037–1044

    Google Scholar 

  • Stolt MH, Genthner MH, Daniels WL, Groover VA, Nagle S, Haering KC (2000) Comparison of soil and other environmental conditions in constructed and adjacent palustrine reference wetlands. Wetlands 20:671–683

    Article  Google Scholar 

  • Takada M, Buhe A, Natsume S, Saito K, Kato K (2006) Classifying the vegetation at Sarobetsu Mire, Hokkaido, using satellite remote sensing (in Japanese with English summary). Landsc Ecol Manage 11:3–14

    Google Scholar 

  • Wang C, Qi J, Moran S, Marsett R (2004) Soil moisture estimation in a semiarid rangeland using ERS–2 and TM imagery. Remote Sens Environ 90:178–189

    Article  Google Scholar 

  • Weimann A, Schönermark MV, Schumann A, Jörn P, Günther R (1998) Soil moisture estimation with ERS-1 SAR data in the East-German loess soil area. Int J Remote Sens 19:237–243

    Article  Google Scholar 

  • Yamaguchi Y, Moriyama T, Ishido M, Yamada H (2005) Four-component scattering modelfor polarimetric SAR image decomposition. IEEE Trans Geosci Remote Sens 43:1699–1706

    Article  Google Scholar 

  • Yamamoto S (1970) Study on permeability of soil, especially of peat soil, vol 7 (in Japanese with English summary). Memoirs of the Faculty of Agriculture, Hokkaido University, pp 307–411

  • Zribi M, Baghdadi N, Holah N, Fafin O (2005) New methodology for soil surface moisture estimation and its application to ENVISAT-ASAR multi-incidence data inversion. Remote Sens Environ 96:485–496

    Article  Google Scholar 

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Acknowledgments

Our research into “Understanding Peat Land Structure and Building a Wetland Change Model for Sarobetsu Mire Restoration” was supported financially by the Ministry of the Environment, and also as one activity of the Satellite Remote Sensing Promotion Committee organized by Japan Aerospace Exploration Agency (JAXA) and the Remote Sensing Technology Center of Japan (RESTEC). We appreciate ALOS images provided by that committee. For the on-site survey as well as the analysis we made, we received great help from Dr. Takashi Inoue and Mr. Taichi Suzumura of Hokkaido University, Dr. Hidenori Takahashi of Hokkaido Institute of Hydro-climate, Mr. Nobuhiro Sasaki of Hokkaido Seabird Center, Mr. Toshihiro Shimazaki of NPO Sarobetsu Eco-Network, and Ms. Sanae Takada of Echigo-numa Study Group. We here express our utmost appreciation to all of them.

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Correspondence to Masayuki Takada.

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Takada, M., Mishima, Y. & Natsume, S. Estimation of surface soil properties in peatland using ALOS/PALSAR. Landscape Ecol Eng 5, 45–58 (2009). https://doi.org/10.1007/s11355-008-0061-4

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