A review of radar remote sensing for biomass estimation

Suman Sinha1, C. Jeganathan1, Laxmi Kant Sharma2, Mahendra Singh Nathawat3
1Department of Remote Sensing, Birla Institute of Technology, Mesra, Ranchi, India
2Centre for Land Resource Management, Central University of Jharkhand, Brambe, Ranchi, India
3School of Sciences, Indira Gandhi National Open University (IGNOU), Maidan Garhi, New Delhi, India

Tóm tắt

Từ khóa


Tài liệu tham khảo

Alappat VO, Joshi AK, Krishnamurthy YVN (2011) Tropical dry deciduous forest stand variable estimation using SAR data. J Indian Soc Remote Sens 39(4):583–589

Amini J, Sumantyo JTS (2009) Employing a method on SAR and optical images for forest biomass estimation. IEEE Trans Geosci Remote Sens 47(12):4020–4026

Antropov O, Rauste Y, Ahola H, Hame T (2013) Stand-level stem volume of boreal forests from spaceborne SAR imagery at L-band. IEEE J Sel Top Appl Earth Obs Remote Sens 6(1):35–44. doi: 10.1109/JSTARS.2013.2241018

Austin JM, Mackey BG, van Niel KP (2003) Estimating forest biomass using satellite radar: an exploratory study in a temperate Australian Eucalyptus forest. For Ecol Manag 176:575–583

Ban Y (2003) Synergy of multitemporal ERS-1 SAR and Landsat TM data for classification of agricultural crops. Can J Remote Sens 29(4):518–526

Beaudoin A, Le Toan T, Goze S et al (1994) Retrieval of forest biomass from SAR data. Int J Remote Sens 15:2777–2796

Becek K (2009) Biomass representation in synthetic aperture radar interferometry data sets. Dissertation, The University of Brunei Darussalam, Brunei

Carreiras JMB, Melo JB, Vasconcelos MJ (2013) Estimating the above-ground biomass in Miombo savanna woodlands (Mozambique, East Africa) using L-band synthetic aperture radar data. Remote Sens 5:1524–1548. doi: 10.3390/rs5041524

Congalton RG (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens Environ 37:35–46

Deepika B, Avinash K, Jayappa KS (2014) Shoreline change rate estimation and its forecast: remote sensing, geographical information system and statistics-based approach. Int J Environ Sci Technol 11(2):395–416

Dobson MC, Ulaby FT, Le Toan T et al (1992) Dependence of radar backscatter on coniferous forest biomass. IEEE Trans Geosci Remote Sens 30:412–416

Dungan JL (2002) Toward a comprehensive view of uncertainty in remote sensing analysis. In: Foody GM, Atkinson PM (eds) Uncertainty in Remote Sensing and GIS. Wiley, West Sussex, pp 25–35

Englhart S, Keuck V, Siegert F (2012) Modeling aboveground biomass in tropical forests using multi-frequency SAR data—a comparison of methods. IEEE J Sel Top Appl Earth Obs Remote Sens 5(1):298–306. doi: 10.1109/JSTARS.2011.2176720

FAO (2001) Global forest resources assessment 2000—main report. FAO Forestry Paper 140, Food and Agriculture Organization of the United Nations, Rome, pp 363

Fatoyinbo TE, Armstrong AH (2010) Remote characterization of biomass measurements: case study of mangrove forests. In: Momba M, Bux F (eds) biomass. InTech Publishers, Croatia

Field CB, Buitenhuis ET, Ciais P et al (2007) Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proc Nat Acad Sci USA (PNAS) 104:18866–18870

Foody GM, Boyd DS, Cutler MEJ (2003) Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions. Remote Sens Environ 85:463–474

Fransson JES, Smith G, Askne J, Olsson H (2001) Stem volume estimation in boreal forests using ERS-1/2 coherence and SPOT XS optical data. Int J Remote Sens 22(14):2777–2791

Gama FF, Santos JR, Mura JC (2010) Eucalyptus biomass and volume estimation using interferometric and polarimetric SAR data. Remote Sens 2:939–956

Ghasemi N, Sahebi MR, Mohammadzadeh A (2011) A review on biomass estimation methods using synthetic aperture radar data. Int J Geomat Geosci 1(4):776–788

Ghasemi N, Sahebi MR, Mohammadzadeh A (2013) Biomass estimation of a temperate deciduous forest using wavelet analysis. IEEE Trans Geosci Remote Sens 51(2):765–776

Gibbs HK, Brown S, Niles JO, Foley JA (2007) Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environ Res Lett 2:1–13

GTOS (Global Terrestrial Observing System) (2009) Biomass—assessment of the status of the development of the standards for the terrestrial essential climate variables. Rome, p 18. http://www.fao.org/gtos/doc/ECVs/T12/T12.pdf

Hamdan O, Aziz HK, Rahman KA (2011) Remotely sensed L-band SAR data for tropical forest biomass estimation. J Trop For Sci 23(3):318–327

Hame T, Rauste Y, Antropov O, Ahola HA, Kilpi J (2013) Improved mapping of tropical forests with optical and SAR imagery, Part II: above ground biomass estimation. IEEE J Sel Top Appl Earth Obs Remote Sens 6(1):92–101

Herold M, Brady M, Wulder M, Kalensky D (2007) Biomass ECV report. ftp.fao.org/docrep/fao/011/i0197e/i0197e16.pdf

Hoekman DH, Quinones MJ (1997) Land cover type and forest biomass assessment in the Colombian Amazon. In: Geoscience and remote sensing, 1997. IGARSS ‘97. Remote sensing—a scientific vision for sustainable development. 1997 IEEE International. IEEE IGARSS 4:1728–1730

Houghton RA (2005) Aboveground forest biomass and the global carbon cycle. Global Change Biol 11:945–958

House JI, Prentice IC, Ramankutty N, Houghton RA, Heimann M (2003) Reconciling apparent inconsistencies in estimates of terrestrial CO2 sources and sinks. Tellus 55B:345–363

Husch B, Beers TW, Kershaw JA (2003) Forest mensuration, 4th edn. Wiley, New Jersey

Hyde P, Dubayah R, Walker W et al (2006) Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy. Remote Sens Environ 102:63–73

Imhoff ML, Johnson P, Holford W et al (2000) BioSar (TM): an inexpensive airborne VHF multiband SAR system for vegetation biomass measurement. IEEE Trans Geosci Remote Sens 38(3):1458–1462

Jha CS, Rangaswamy M, Murthy MSR, Vyjayanthi N (2006) Estimation of forest biomass using Envisat-ASAR data. Proc SPIE 6410:641002

Kasischke ES, Melack JM, Dobson MC (1997) The use of imaging radars for ecological applications—a review. Remote Sens Environ 59:141–156

Keller M, Palace M, Hurtt G (2001) Biomass estimation in the Tapajos National Forest, Brazil: examination of sampling and allometric uncertainties. For Ecol Manage 154:371–382

Ketterings QM, Coe R, van Noordwijk M, Ambagau K, Palm CA (2001) Reducing uncertainty in the use of allometric biomass equations for predicting aboveground tree biomass in mixed secondary forests. For Ecol Manage 146:199–209

Kumar NR (2007) Forest cover, stand volume and biomass assessment in Dudhwa National Park using satellite remote sensing data (optical and EnviSat ASAR). Dissertation, Andhra University, India

Kumar S (2009) Retrieval of forest parameters from Envisat ASAR data for biomass inventory in Dudhwa National Park, UP, India. Dissertation, IIRS, Dehradun, India and ITC, Enschede, Netherlands

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. doi: 10.1109/JSTARS.2012.2221123

Kuplich TM, Salvatori V, Curran PJ (2000) JERS-1/SAR backscatter and its relationship with biomass of regenerating forests. Int J Remote Sens 21:2513–2518

Kurvonen L, Pulliainen J, Hallikainen M (1999) Retrieval of biomass in boreal forests from multitempotal ERS-1 and JERS-1 SAR images. IEEE Trans Geosci Remote Sens 37(1):198–205

Le Toan TB, Beaudoin A, Riom J, Guyon D (1992) Relating forest biomass to SAR data. IEEE Trans Geosci Remote Sens 30(2):403–411

Le Toan T, Quegan S, Davidson MWJ et al (2011) The BIOMASS mission: mapping global forest biomass to better understand the terrestrial carbon cycle. Remote Sens Environ 115:2850–2860

Liang J, Zeng GM, Shen S et al. (2013) Bayesian approach to quantify parameter uncertainty and impacts on predictive flow and mass transport in heterogeneous aquifer. Int J Environ Sci Technol. doi: 10.1007/s13762-013-0453-3

Loehle C (2000) Forest ecotone response to climate change: sensitivity to temperature response functional forms. Can J For Res 30:1632–1645

Lu D (2005) Aboveground biomass estimation using Landsat TM data in the Brazilian Amazon Basin. Int J Remote Sens 26:2509–2525

Lu D (2006) The potential and challenge of remote sensing-based biomass estimation. Int J Remote Sens 27(7):1297–1328

Lucas RM, Cronin N, Lee A et al (2006) Empirical relationships between AIRSAR backscatter and LiDAR-derived forest biomass, Queensland, Australia. Remote Sens Environ 100(3):407–425

Lucas RM, Lee AC, Bunting PJ (2008) Retrieving forest biomass through integration of CASI and LiDAR data. Int J Remote Sens 29(5):1553–1577

Lucas RM, Armston J, Fairfax R et al (2010) An evaluation of the ALOS PALSAR L-band backscatter—above ground biomass relationship Queensland, Australia: impacts of surface moisture condition and vegetation structure. IEEE J Sel Top Appl Earth Obs Remote Sens 3(4):576–593. doi: 10.1109/JSTARS.2010.2086436

Luckman A, Baker JR, Kuplich TM, Yanasse CCF, Frery AC (1997) A study of the relationship between radar backscatter and regenerating forest biomass for space borne SAR instrument. Remote Sens Environ 60:1–13

Malhi YP (2002) Forests, carbon and global climate. Phil Trans R Soc Lond A 360:1567–1591

Mette T, Papathanassiou K, Hajnsek I (2004) Biomass estimation from polarimetric SAR interferometry over heterogeneous forest terrain. In: Geoscience and remote sensing symposium (IGARSS), 2004 IEEE International. Anchorage, AK. IEEE IGARSS 1:511–514

Nabuurs GJ, Masera O, Andrasko K et al (2007) Forestry. In: Metz B, Davidson OR, Bosch PR, Dave R, Meyer LA (eds) Climate change 2007: mitigation. Contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge

Neumann M (2009) Remote sensing of vegetation using multi-baseline polarimetric SAR interferometry: theoretical modeling and physical parameter retrieval. Dissertation, University of Rennes 1, France

Nizalapur V, Jha CS, Madugundu R (2010) Estimation of above ground biomass in Indian tropical forested area using multifrequency DLR-ESAR data. Int J Geomat Geosci 1(2):167–178

Ouchi K (2013) Recent trend and advance of synthetic aperture radar with selected topics. Remote Sens 5:716–807. doi: 10.3390/rs5020716

Patenaude GM, Milne R, Dawson TP (2005) Synthesis of remote sensing approaches for forest carbon estimation: reporting to the Kyoto Protocol. Environ Sci Policy 8:161–178

Peregon A, Yamagata Y (2013) The use of ALOS/PALSAR backscatter to estimate above-ground forest biomass: a case study in Western Siberia. Remote Sens Environ 137:139–146

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

Pulliainen JT, Engdahl M, Hallikainen M (2003) Feasibility of multi-temporal interferometric SAR data for stand-level estimation of boreal forest stem volume. Remote Sens Environ 85:397–409

Ranson KJ, Sun G (1994) Mapping biomass of a northern forest using multifrequency SAR data. IEEE Trans Geosci Remote Sens 32:388–396

Ranson KJ, Sun G, Weishampel JF, Knox RG (1997) Forest biomass from combined ecosystem and radar backscatter modeling. Remote Sens Environ 59:118–133

Rauste Y (2005) Techniques for wide-area mapping of forest biomass using radar data. Espoo 2005. VTT Publications, Finland. ISBN 951–38–6695–5

Roy PS, Diwakar PG, Singh IJ, Bhan SK (1994) Evaluation of microwave remote sensing data for forest stratification and canopy characterization. J Indian Soc Remote Sens 22(1):31–44

Sambatti JBM, Leduc R, Lübeck D, Moreira JR, Santos JR (2012) Assessing forest biomass and exploration in the Brazilian Amazon with airborne InSAR: an alternative for REDD. Open Remote Sens J 5:21–36

Santoro M, Askne J, Dammert PBG (2003) Tree height estimation from multi-temporal ERS SAR interferometric phase. Proceeding of FRINGE 2003 Workshop, 1–5 Dec 2003, Frascati, Italy

Santoro M, Eriksson L, Askne J, Schmullius C (2006) Assessment of stand-wise stem volume retrieval in boreal forest from JERS-1 L-band SAR backscatter. Int J Remote Sens 27(16):3425–3454

Santos JR, Pardi Lacruz MS, Araujo LS, Keil M (2002) Savanna and tropical rainforest biomass estimation and spatialization using JERS-1 data. Int J Remote Sens 23:1217–1229

Santos JR, Neeff T, Dutra LV et al (2004) Tropical forest biomass mapping from dual frequency SAR interferometry (X and P-Bands). In: Twentieth international society for photogrametry and remote sensing (ISPRS) congress. GeoImagery bridging continents, Istanbul, v.XXXV, pp 1133–1136

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 185:8621–8637. doi: 10.1007/s10661-013-3199-y

Shen Z, Xie H, Chen L, Qiu J, Zhong Y (2015) Uncertainty analysis for nonpoint source pollution modeling: implications for watershed models. Int J Environ Sci Technol 12:739–746

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. doi: 10.1029/2009JG000993

Sinha S, Sharma LK, Nathawat MS (2012) Tigers losing grounds: impact of anthropogenic occupancy on tiger habitat suitability using integrated geospatial-fuzzy techniques. The Ecoscan 1:259–263

Soja M, Sandberg G, Ulander L (2010) Topographic correction for biomass retrieval from P-band SAR data in boreal forests. In: Geoscience and remote sensing symposium (IGARSS), 2010 IEEE International. Honolulu, HI, pp 4776–4779

Stephens BB, Gurney KR, Tans PP et al (2007) Weak northern and strong tropical Land carbon uptake from vertical profiles of atmospheric CO2. Science 316:1732–1735

Sun G, Ranson KJ, Kharuk VI (2002) Radiometric slope correction for forest biomass estimation from SAR data in the western Sayani Mountains, Siberia. Remote Sens Environ 79:279–287

Townshend JR, Masek JG, Huang C et al (2012) Global characterization and monitoring of forest cover using Landsat data: opportunities and challenges. Int J Digit Earth 5(5):373–397

Treuhaft RN, Asner GP, Law BE (2003) Structure-based forest biomass from fusion of radar and hyperspectral observations. Geophys Res Lett 30(9):1472. doi: 10.1029/2002GL016857

Treuhaft RL, Law BE, Asner GP (2004) Forest attributes from radar interferometric structure & its fusion with optical remote sensing. Biosci 54:561–571

Wiley CA (1985) Synthetic aperture radars: a paradigm for technology evolution. IEEE Trans Aerosp Electron Syst AES 21(3):440–443

Wollersheim M, Collins MJ, Leckie D (2011) Estimating boreal forest species type with airborne polarimetric synthetic aperture radar. Int J Remote Sens 32(9):2481–2505

Yavasli DD (2012) Recent approaches in above ground biomass estimation methods. Aegean Geographical Journal 21(1):39–51

Yu Y, Saatchi S, Heath LS et al (2010) Regional distribution of forest height and biomass from multisensor data fusion. J Geophys 115:G00E12. doi: 10.1029/2009JG000995

Zolkos SG, Goetz SJ, Dubayah R (2013) A meta-analysis of terrestrial aboveground biomass estimation using lidar remote sensing. Remote Sens Environ 128:289–298