Salvador R, Pons X (1998) On the reliability of Landsat TM for estimating forest variables by
regression techniques: a methodological analysis. IEEE Trans Geosci Remote Sens
36:1888–1897
Sarker LR, Nichol JE (2011) Improved forest biomass estimates using ALOS AVNIR-2 texture
indices. Remote Sens Environ 115:968–977
Schull MA, Ganguly S, Samanta A, Huang D, Shabanov NV, Jenkins JP, Chiu JC, Marshak A,
Blair JB, Myneni RB, Knyazikhin Y (2007) Physical interpretation of the correlation between
multiangle spectral data and canopy height. Geophys Res Lett 34:L18405. doi:10.1029/
2007GL031143
Segura M and Kanninen M (2005) Allometric models for tree volume and total aboveground
biomass in atropical humid forest in Costa Rica. Biotropica 37:2–8
Slatton KC, Crawford MM, Evans BL (2001) Fusing interferometric radar and laser altimeter
data to estimate surface topography and vegetation heights. IEEE Trans Geosci Remote Sens
39(11):2470–2482
Soenen SA, Peddle DR, Hall RJ et al (2010) Estimating aboveground forest biomass from canopy
reflectance model inversion in mountainous terrain. Remote Sens Environ 114(7):1325–1337.
doi:10.1016/j.rse.2009.12.012
Steininger MK (2000) Satellite estimation of tropical secondary forest above-ground biomass:
data from Brazil and Bolivia. Int J Remote Sens 21:1139–1157
Sun G, Ranson KJ (1995) A three-dimensional radar backscatter model of forest canopies. IEEE
Trans Geosci Remote Sens 33(2):372–382
Swatantran A, Dubayah R, Roberts D, Hofton M, Blair JB (2011) Mapping biomass and stress in
the Sierra Nevada using lidar and hyperspectral data fusion. Remote Sens Environ
115:2917–2930
Ter-Mikaelian MT, Korzukin MD (1997) Biomass equations for sixty-five North America tree
species. For Ecol Manag 97:1–24
Tomppo E (1991) Satellite Image-Based National Forest Inventory of Finland. In: Proceedings of
the symposium on Global and Environmental Monitoring, Techniques and Impacts.
September 17–21, 1990 Victoria, British Columbia Canada. International Archives of
Photogrammetry and Remote Sensing, Vol 28, Part 7-1, pp 419–424
Tomppo E, Halme M (2004) Using coarse scale forest variables as ancillary information and
weighting of variable sin k-NN estimation: a genetic algorithm approach. Remote Sens
Environ 92:1–20
Tomppo E, Goulding C, Katila M (1999) Adapting Finnish multi-source forest inventory
techniques to the New Zealand preharvest inventory. Scand J For Res 14:182–192
Tomppo E, Korhonen KT, Heikkinen J, Yli-Kojola H (2001) Multisource inventory of the forests
of the Hebei Forestry Bureau, Heilongjiang, China. Silva Fennica 35(3):309–328
Tomppo E, Czaplewski R, Mäkisara K (2002) The role of remote sensing in global forest
assessment. FAO Forest Resource Assessment Programme Working Paper 61.pp 90
Treuhaft RN, Siqueira PR (2000) Vertical structure of vegetated land surfaces from interferometric and polarimetric radar. Radio Sci 35:141–177
Treuhaft RN, Madsen SN, Moghaddam M, Van Zyl JJ (1996) Vegetation characteristics and
surface topography from interferometric radar. Radio Science 31:1449–1485
Trotter CM, Dymond JR, Goulding CJ (1997) Estimation of timber volume in a coniferous
plantation forest using Landsat TM. Int J Remote Sens 18:2209–2223
Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation.
Remote Sens Environ 8:127–150
Turner DP, Ollinger SV, Kimball JS (2004) Integrating remote sensing and ecosystem process
models for landscape- to regional-scale analysis of the carbon cycle. Bioscience 54:573–584
Ulaby FT, Sarabandi K, McDonald K, Whitt M, Dobson MC (1990) Michigan Microwave
Canopy Scattering Model. Int J Remote Sens 11(7):1223–1253
Van der Werf GR, Randerson JT, Giglio L, Collatz GJ, Mu M, Kasibhatla PS, Morton DC
DeFries RS, Jin Y, and van Leeuwen TT (2010) Global fire emissions and the contribution of
3 Remote Sensing of Forest Biomass
97
regression techniques: a methodological analysis. IEEE Trans Geosci Remote Sens
36:1888–1897
Sarker LR, Nichol JE (2011) Improved forest biomass estimates using ALOS AVNIR-2 texture
indices. Remote Sens Environ 115:968–977
Schull MA, Ganguly S, Samanta A, Huang D, Shabanov NV, Jenkins JP, Chiu JC, Marshak A,
Blair JB, Myneni RB, Knyazikhin Y (2007) Physical interpretation of the correlation between
multiangle spectral data and canopy height. Geophys Res Lett 34:L18405. doi:10.1029/
2007GL031143
Segura M and Kanninen M (2005) Allometric models for tree volume and total aboveground
biomass in atropical humid forest in Costa Rica. Biotropica 37:2–8
Slatton KC, Crawford MM, Evans BL (2001) Fusing interferometric radar and laser altimeter
data to estimate surface topography and vegetation heights. IEEE Trans Geosci Remote Sens
39(11):2470–2482
Soenen SA, Peddle DR, Hall RJ et al (2010) Estimating aboveground forest biomass from canopy
reflectance model inversion in mountainous terrain. Remote Sens Environ 114(7):1325–1337.
doi:10.1016/j.rse.2009.12.012
Steininger MK (2000) Satellite estimation of tropical secondary forest above-ground biomass:
data from Brazil and Bolivia. Int J Remote Sens 21:1139–1157
Sun G, Ranson KJ (1995) A three-dimensional radar backscatter model of forest canopies. IEEE
Trans Geosci Remote Sens 33(2):372–382
Swatantran A, Dubayah R, Roberts D, Hofton M, Blair JB (2011) Mapping biomass and stress in
the Sierra Nevada using lidar and hyperspectral data fusion. Remote Sens Environ
115:2917–2930
Ter-Mikaelian MT, Korzukin MD (1997) Biomass equations for sixty-five North America tree
species. For Ecol Manag 97:1–24
Tomppo E (1991) Satellite Image-Based National Forest Inventory of Finland. In: Proceedings of
the symposium on Global and Environmental Monitoring, Techniques and Impacts.
September 17–21, 1990 Victoria, British Columbia Canada. International Archives of
Photogrammetry and Remote Sensing, Vol 28, Part 7-1, pp 419–424
Tomppo E, Halme M (2004) Using coarse scale forest variables as ancillary information and
weighting of variable sin k-NN estimation: a genetic algorithm approach. Remote Sens
Environ 92:1–20
Tomppo E, Goulding C, Katila M (1999) Adapting Finnish multi-source forest inventory
techniques to the New Zealand preharvest inventory. Scand J For Res 14:182–192
Tomppo E, Korhonen KT, Heikkinen J, Yli-Kojola H (2001) Multisource inventory of the forests
of the Hebei Forestry Bureau, Heilongjiang, China. Silva Fennica 35(3):309–328
Tomppo E, Czaplewski R, Mäkisara K (2002) The role of remote sensing in global forest
assessment. FAO Forest Resource Assessment Programme Working Paper 61.pp 90
Treuhaft RN, Siqueira PR (2000) Vertical structure of vegetated land surfaces from interferometric and polarimetric radar. Radio Sci 35:141–177
Treuhaft RN, Madsen SN, Moghaddam M, Van Zyl JJ (1996) Vegetation characteristics and
surface topography from interferometric radar. Radio Science 31:1449–1485
Trotter CM, Dymond JR, Goulding CJ (1997) Estimation of timber volume in a coniferous
plantation forest using Landsat TM. Int J Remote Sens 18:2209–2223
Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation.
Remote Sens Environ 8:127–150
Turner DP, Ollinger SV, Kimball JS (2004) Integrating remote sensing and ecosystem process
models for landscape- to regional-scale analysis of the carbon cycle. Bioscience 54:573–584
Ulaby FT, Sarabandi K, McDonald K, Whitt M, Dobson MC (1990) Michigan Microwave
Canopy Scattering Model. Int J Remote Sens 11(7):1223–1253
Van der Werf GR, Randerson JT, Giglio L, Collatz GJ, Mu M, Kasibhatla PS, Morton DC
DeFries RS, Jin Y, and van Leeuwen TT (2010) Global fire emissions and the contribution of
3 Remote Sensing of Forest Biomass
97