Abstract
Accurate estimates of forest biomass are increasingly important in relation to sequestration of carbon by forest trees. Satellite remote sensing is a useful tool for biomass estimation and monitoring of forest ecological processes. Microwave synthetic aperture radar (SAR) can increase the accuracy of estimations of forest biomass in comparison to optical remote sensing, due to the unique capacities of SAR, including high penetrability, volumetric scattering, interaction with surface roughness, and dielectric property. We studied the potential of multi-polarized C-band Radarsat-2, a SAR technology, with HH, HV and VV polarization for estimating biomass of moist tropical Indian forest. Backscatter values are correlated with field-based biomass values and are regressed to generate models for estimating biomass. HH polarization provided maximum information regarding tree biomass. A coefficient of determination of 0.49 was calculated for HH polarized C-band image with in situ measurements. An exponential model was proved to be best suited for estimating forest biomass. Correlation of 0.62 and RMSE of 24.6 t ha−1 were calculated for the relationship between estimated and predicted biomass values for the best fit model. The average absolute accuracy of the model was 61%, while Willmott’s index of agreement was 0.87. Results suggest that most of the biomass of the area ranged within 70 t ha−1 a probably due to the saturation of C-band around 60–70 t ha−1 for tropical forests.






Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Alamgir M, Al-Amin M (2008) Allometric models to estimate biomass organic carbon stock in forest vegetation. J For Res 19(2):101–106
Chen W, Blain D, Li J, Keohler K, Fraser R, Zhang Y, Leblanc S, Olthof I, Wang J, Mcgovern M (2009) Biomass measurements and relationships with Landsat-7/ETM+ and JERS-1/SAR data over Canada’s western sub-arctic and low arctic. Int J Remote Sens 30(9):2355–2376
Dobson MC, Ulaby FT, LeToan T, Beaudoin A, Kasischke ES, Christensen N (1992) Dependence of radar backscatter on coniferous forest biomass. IEEE Trans Geosci Remote Sens 30(2):412–415
Englhart S, Keuck V, Siegert F (2011) Aboveground biomass retrieval in tropical forests—the potential of combined X- and L-band SAR data use. Remote Sens Environ 115:1260–1271
FRI (1996) Indian woods. Forest Research Institute, Dehradun
FSI (1996) Volume equations for forests of India, Nepal and Bhutan. Forest Survey of India, Ministry of Environment and Forests, Govt. of India, Dehradun
Gao R, Luo Y, Wang Z, Yu H, Shi J (2017) Patterns of biomass, carbon, and nitrogen storage distribution dynamics after the invasion of pine forests by Bursaphelenchus xylophilus (Nematoda: Aphelenchoididae) in the three Gorges Reservoir Region. J For Res. https://doi.org/10.1007/s11676-017-0432-5
Gibbs HK, Brown S, Niles JO, Foley JA (2007) Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environ Res Lett. https://doi.org/10.1088/1748-9326/2/4/045023
Hussin YA, Reich RM, Hoffer RM (1991) Estimating slash pine biomass using radar backscatter. IEEE Trans Geosci Remote Sens 29(3):427–431
Kumar S (2009) Retrieval of forest parameters from Envisat ASAR data for biomass inventory in Dudhwa National Park, U.P., India. M.Sc thesis, International Institute for Geo-information Science and Earth Observation (ITC), Enschede, The Netherlands & Indian Institute of Remote Sensing, National Remote Sensing Centre (NRSC), ISRO, Department of Space, Dehradun, India. www.itc.nl/library/papers_2009/msc/gfm/kumar_shashi.pdf. Accessed 23 Jan 2015
Kumar P, Sharma LK, Pandey PC, Sinha S, Nathawat MS (2013) Geospatial strategy for tropical forest-wildlife reserve biomass estimation. IEEE J Sel Top Appl Earth Obs Remote Sens 6(2):917–923
LeToan T, Beaudoin A, Riom J, Guyon D (1992) Relating forest biomass to SAR data. IEEE Trans Geosci Remote Sens 30(2):403–411
Nizalapur V, Jha CS, Madugundu R (2010) Estimation of above ground biomass in Indian tropical forested area using multi-frequency DLR-ESAR data. Int J Geomat Geosci 1(2):167–178
Pandey U, Kushwaha SPS, Kachhwaha TS, Kunwar P, Dadhwal VK (2010) Potential of envisat ASAR data for woody biomass assessment. Trop Ecol 51(1):117–124
Plugge D, Baldauf T, Ratsimba HR, Rajoelison G, Köhl M (2010) Combined biomass inventory in the scope of REDD (reducing emissions from deforestation and forest degradation). Madag Conserv Dev 5:23–34
Prakoso KU (2006) Tropical forest mapping using polarimetric and interferometric SAR data. A case study in Indonesia. Doctoral thesis, Wageningen University, Wageningen, The Netherlands
Quinones MJ, Hoekman DH (2002) Biomass mapping using biophysical forest type characterization of SAR polarimetric images. In: Proceedings of 3rd international symposium. ‘Retrieval of bio- and geophysical parameters from SAR data for land application’, Sheffield, UK, ESA SP, 475, pp 25–31
Romshoo SA, Shimada M (2001) Employing SAR for biomass retrieval from tropical forests of Southeast Asia. In: 22nd Asian conference on remote sensing, 5–9 Nov 2001, Singapore
Santoro M, Fransson JES, Eriksson LEB, Magnusson M, Ulander LMH, Olsson H (2009) Signatures of ALOS PALSAR L-band backscatter in Swedish forest. IEEE Trans Geosci Remote Sens 47(12):4001–4019
Sgrenzaroli M (2004) Tropical forest mapping at regional scale using the GRFM SAR mosaics over the Amazon in South America. Doctoral thesis, Wageningen University, Wageningen, The Netherlands
Sharma LK, Nathawat MS, Sinha S (2013) Top-down and bottom-up inventory approach for above ground forest biomass and carbon monitoring in REDD framework using multi-resolution satellite data. Environ Monit Assess 185(10):8621–8637
Shugart HH, Saatchi S, Hall FG (2010) Importance of structure and its measurement in quantifying function of forest ecosystems. J Geophys Res 115(G2):G00E13. https://doi.org/10.1029/2009JG000993
Sinha S (2016) Polarimetric scattering parameter products of ALOS PALSAR for forest biomass assessment. Res Rev J Space Sci Tech 5(1):1–9
Sinha S, Sharma LK (2013) Investigations on potential relationship between biomass and surface temperature using thermal remote sensing over tropical deciduous forests. Res Rev J Space Sci Tech 2(3):13–18
Sinha S, Sharma LK, Nathawat MS (2013) Integrated geospatial techniques for land-use/land-cover and forest mapping of deciduous Munger forests (India). Univers J Environ Res Technol 3(2):190–198
Sinha S, Pandey PC, Sharma LK, Nathawat, Kumar P, Kanga S (2014) Remote estimation of land surface temperature for different LULC features of a moist deciduous tropical forest region. In: Srivastava PK, Mukherjee S, Gupta M, Islam T (eds) Remote sensing applications in environmental research (part 1). Springer, Berlin, pp 57–68
Sinha S, Jeganathan C, Sharma LK, Nathawat MS (2015a) A review of radar remote sensing for biomass estimation. Int J Environ Sci Technol 12(5):1779–1792
Sinha S, Sharma LK, Nathawat MS (2015b) Improved land-use/land-cover classification of semi-arid deciduous forest landscape using thermal remote sensing. Egypt J Remote Sens Space Sci 18(2):217–233
Sinha S, Sharma LK, Jeganathan C, Nathawat MS, Das AK, Mohan S (2015c) Efficacy of InSAR coherence in tropical forest remote sensing in context of REDD. Int J Adv Remote Sens GIS Geogr 3(1a):38–46
Sinha S, Jeganathan C, Sharma LK, Nathawat MS, Das AK, Mohan S (2016) Developing synergy regression models with space-borne ALOS PALSAR and Landsat TM sensors for retrieving tropical forest biomass. J Earth Syst Sci 125(4):725–735
Wang C, Qi J (2008) Biophysical estimation in tropical forests using JERS-1 SAR and VNIR imagery. II. Aboveground woody biomass’. Int J Remote Sens 29(23):6827–6849
Wijaya A, Kusnadi S, Gloaguen R, Heilmeier H (2010) Improved strategy for estimating stem volume and forest biomass using moderate resolution remote sensing data and GIS. J For Res 21(1):1–12
Acknowledgements
The authors sincerely acknowledge Space Application Centre (SAC, ISRO) for providing the SAR data. The first author expresses sincere gratitude to the Department of Science and Technology (DST), Government of India for providing funds under DST-INSPIRE Program (Ref. No. DST/INSPIREFELLOWSHIP/2010/[316]) to carry out the research.
Author information
Authors and Affiliations
Corresponding author
Additional information
Project funding: This study was financially supported by DST-INSPIRE Program (Ref. No. DST/INSPIREFELLOWSHIP/2010/[316]) of the Department of Science and Technology (DST), Government of India.
The online version is available at http://www.springerlink.com
Corresponding editor: Yu Lei.
Rights and permissions
About this article
Cite this article
Sinha, S., Santra, A., Sharma, L. et al. Multi-polarized Radarsat-2 satellite sensor in assessing forest vigor from above ground biomass. J. For. Res. 29, 1139–1145 (2018). https://doi.org/10.1007/s11676-017-0511-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11676-017-0511-7


