PE&RS January 2016 - page 49

Mas, J.F., and J.J. Flores, 2008. The application of arti cial
neural networks to the analysis of remotely sensed data,
International Journal of Remote Sensing, 29(3):617–663: doi:
10.1080/01431160701352154.
Minh, D.H.T., T. Le Toan, F. Rocca, S. Tebaldini, M.M. d'Alessandro,
and L. Villard, 2014. Relating P-band synthetic aperture radar
tomography to tropical forest biomass, IEEE Transactions on
Geoscience and Remote Sensing, 52(2):967–979.: doi: 10.1109/
TGRS.2013.2246170.
Mitchard, E.T.A., S.S. Saatchi, I.H. Woodhouse, G. Nangendo, N.S.
Ribeiro, M. Williams, C.M.
Ryan, S.L. Lewis, T.R. Feldpausch, and P. Meir, 2009. Using
satellite radar backscatter to predict above-ground woody
biomass: A consistent relationship across four different African
landscapes, Geophysical Research Letters, 36(23):1–6: doi:
10.1029/2009GL040692.
Monnet, J.M., J. Chanussot, and F. Berger, 2011. Support vector
regression for the estimation of forest stand parameters
using airborne laser scanning, IEEE Transactions on
Geoscience and Remote Sensing, 8(3):580–584: doi: 10.1109/
LGRS.2010.2094179.
Mountrakis, G., J. Im, and C. Ogole, 2011. Support vector machines
in remote sensing: A review, ISPRS Journal of Photogrammetry
and Remote Sensing, 66(3):247–259: doi: 10.1016/j.
isprsjprs.2010.11.001.
Ormsby, J.P., B.J. Blanchard, and A.J. Blanchard, 1985. Detection
of lowland flooding using active microwave systems,
Photogrammetric Engineering & Remote Sensing, 51(3):317–328.
Pal, M., and G.M. Foody, 2012. Evaluation of SVM, RVM and
SMLR for accurate image classification with limited ground
data, IEEE Journal of Selected Topics in Applied Earth
Observations and Remote Sensing, 5(5):1344–1355: doi: 10.1109/
JSTARS.2012.2215310.
Peregon, A., and Y. Yamagata, 2013. The use of ALOS/PALSAR
backscatter to estimate above-ground forest biomass: A case
study in Western Siberia, Remote Sensing of Environment,
137:139–146: doi: 10.1016/j.rse.2013.06.012.
Rabe, A., S. van der Linden, and P. Hostert, 2009. Simplifying support
vector machines for regression analysis of hyperspectral imagery,
Proceedings of the IEEE 1st Workshop on Hyperspectral Image
and Signal Processing - Evolution in Remote Sensing, 26–28
August 2002, Grenoble, France.
Saatchi, S., K. Halligan, D. Despainn and R. Crabtreen, 2007.
Estimation of forest fuel load from radar remote sensing, IEEE
Transactions on Geoscience and Remote Sensing, 45(6):1726–
1740: doi: 10.1109/TGRS.2006.887002.
Sader, S., 1987. Forest biomass, canopy structure, and species
composition relationships with multipolarization L-band
synthetic aperture radar data, Photogrammetric Engineering &
Remote Sensing, 55:193–202.
Sandberg, G., L.M.H. Ulander, J.E.S. Fransson, J. Holmgren, and T.
Le Toan, 2011. L- and P-band backscatter intensity for biomass
retrieval in hemiboreal forest, Remote Sensing of Environment,
115(11):2874–2886: doi: 10.1016/j.rse.2010.03.018.
Santos, J., M. Lacruz, L. Araujo, and M. Keil, 2002. Savanna and
tropical rainforest biomass estimation and spatialization
using JERS-1 data, International Journal of Remote Sensing,
23(7):1217–1229: doi: 10.1080/01431160110092867.
Sartori, L.R., N.N. Imai, J.C. Mura, E.M.L.M. Novo, and T.S.F. Silva,
2011. Mapping macrophyte species in the Amazon floodplain
wetlands using fully polarimetric ALOS/PALSAR data, IEEE
Transactions on Geoscience and Remote Sensing, 49(12):4717–
4728: doi: 10.1109/TGRS.2011.2157972.
Sharifi, A., and J. Amini, 2015. Forest biomass estimation using
synthetic aperture radar polarimetric features, Journal of Applied
Remote Sensing, 9(1):097695: doi:10.1117/1.JRS.9.097695
Sharifi, A., J. Amini, and F. Pourshakouri, 2015. Development of an
allometric model to estimate above-ground biomass of forests
using MLPNN algorithm case study: Hyrcanian forests of Iran,
Caspian Journal of Environmental Sciences, Accepted.
Sharifi, A., J. Amini, J.T.S. Sumantyo, and R. Tateishi, 2015. Speckle
reduction of PolSAR images in forest regions using Fast ICA
algorithm, Journal of the Indian Society of Remote Sensing,
43(2):339-346: doi: 10.1007/s12524-014-0423-3.
Shimada, M., O. Isoguchi, T. Tadono, and K. Isono, 2009. PALSAR
radiometric calibration and geometric calibration, IEEE
Transactions on Geoscience and Remote Sensing, 47(12):3915–
3932: doi: 10.1109/TGRS.2009.2023909.
Simard. M., K. Zhang, V.R.M.S. Rivera-Monroy, P.L. Ruiz, R.R.
Castalieda-Moya, and E. Rodriguez, 2006. Mapping height and
biomass of mangrove forests in the Everglades National Park
with SRTM elevation data, Photogrammetric Engineering &
Remote Sensing, 72(3):299–312.
Soja, M.J., G. Sandberg, and L.M.H Ulander, 2013. Regression-
based retrieval of boreal forest biomass in sloping terrain using
P-band SAR backscatter intensity data, IEEE Transactions on
Geoscience and Remote Sensing, 51(5):2646–2665: doi: 10.1109/
TGRS.2012.2219538.
Sumantyo, J.T.S., and J. Amini, 2008. A model for removal of speckle
noise in SAR images (ALOS PALSAR), Canadian Journal of
Remote Sensing, 34(6):503–515: doi: 10.5589/m08-069.
Tanasea, M.A., R. Pancieraa, K. Lowella, S. Tiana, J.M. Hackerb, and
J.P. Walker, 2014. Airborne multi-temporal L-band polarimetric
SAR data for biomass estimation in semi-arid forests,
Remote Sensing Environment, 145:93–104: doi: 10.1016/j.
rse.2014.01.024.
Thayananthan, A., R. Navaratnam, B. Stenger, P.H.S. Torr, and R.
Cipolla, 2006. Multivariate relevance vector machines for
tracking, Proceedings of the European Conference on Computer
Vision, 07–13 May, Graz, Austria.
Ticehurst, C., A. Held, and S. Phinn, 2004. Integrating JERS-1
imaging radar and elevation models for mapping tropical
vegetation communities in far north Queensland, Australia,
Photogrammetric Engineering & Remote Sensing, 70(11):1259–66.
Tipping, M.E., 2001. Sparse Bayesian learning and the relevance
vector machine, Journal of Machine Learning Research, 1:211–
244: doi: 10.1162/15324430152748236.
Townsend, P.A., 2001. Mapping seasonal flooding in forested
wetlands using multi-temporal Radarsat SAR, Photogrammetric
Engineering & Remote Sensing, 67(7):857–864.
Wang, K., J. Jufeng, G. Shi, Q. Wang, 2008. An expanded training set
based validation method to avoid overfitting for neural network
classifier, Proceedings of the Fourth International Conference on
Natural Computation, 18–20 October, Jinan, China, pp. 83–87:
doi: 10.1109/ICNC.2008.571.
Watanabe, M., M. Shimada, A. Rosenqvist, T. Tadono, M. Matsuoka,
S.A. Romshoo, K. Ohta, R. Furuta, K. Nakamura, and T.
Moriyama, 2006. Forest structure dependency of the relation
between L-band σ^0 and biophysical parameters, IEEE
Transactions on Geoscience and Remote Sensing, 44(11):3154–
3165: doi: 10.1109/TGRS.2006.880632.
West, P.W., 2009. Tree and Forest Measurement, Springer Press,
Lismore, Australia, 192 p.
Woodhouse, I.H., 2005. Introduction to Microwave Remote Sensing,
CRC Press, Boca Raton, Florida, 400 p.
(Received 16 January 2015; accepted 19 June 2015; final ver-
sion 23 July 2015)
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January 2016
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