Related references
Note: Only part of the references are listed.Comparison of Machine Learning Methods for Estimating Mangrove Above-Ground Biomass Using Multiple Source Remote Sensing Data in the Red River Delta Biosphere Reserve, Vietnam
Tien Dat Pham et al.
REMOTE SENSING (2020)
Modeling and mapping aboveground biomass of the restored mangroves using ALOS-2 PALSAR-2 in East Kalimantan, Indonesia
Mst Karimon Nesha et al.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2020)
Forest structure dependency analysis of L-band SAR backscatter
Yongjie Ji et al.
PEERJ (2020)
Assessment of multi-wavelength SAR and multispectral instrument data for forest aboveground biomass mapping using random forest kriging
Lin Chen et al.
FOREST ECOLOGY AND MANAGEMENT (2019)
Improving Forest Height Retrieval by Reducing the Ambiguity of Volume-Only Coherence Using Multi-Baseline PolInSAR Data
Zhanmang Liao et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2019)
Retrieving Secondary Forest Aboveground Biomass from Polarimetric ALOS-2 PALSAR-2 Data in the Brazilian Amazon
Henrique Luis Godinho Cassol et al.
REMOTE SENSING (2019)
THE WHEAT BIOMASS ESTIMATION BASED ON GENETIC ALGORITHM FEATURE SELECTION METHOD USING C-BAND POLSAR DATA
Kunpeng Xu et al.
2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019) (2019)
Predicting of the refractive index of haemoglobin using the Hybrid GA-SVR approach
Tajudeen A. Oyehan et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2018)
Tracking crop phenological development using multi-temporal polarimetric Radarsat-2 data
Francis Canisius et al.
REMOTE SENSING OF ENVIRONMENT (2018)
GA-SVM Algorithm for Improving Land-Cover Classification Using SAR and Optical Remote Sensing Data
Chanika Sukawattanavijit et al.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2017)
An improved scheme for rice phenology estimation based on time-series multispectral HJ-1A/B and polarimetric RADARSAT-2 data
Yang Zhi et al.
REMOTE SENSING OF ENVIRONMENT (2017)
A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems
Dengsheng Lu et al.
INTERNATIONAL JOURNAL OF DIGITAL EARTH (2016)
Metro Station Safety Status Prediction Based on GA-SVR
Zhenyu Zhang et al.
PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ELECTRICAL AND INFORMATION TECHNOLOGIES FOR RAIL TRANSPORTATION: TRANSPORTATION (2016)
GA-PARSIMONY: A GA-SVR approach with feature selection and parameter optimization to obtain parsimonious solutions for predicting temperature settings in a continuous annealing furnace
A. Sanz-Garcia et al.
APPLIED SOFT COMPUTING (2015)
Evaluation of GA-SVR method for modeling bed load transport in gravel-bed rivers
Kiyoumars Roushangar et al.
JOURNAL OF HYDROLOGY (2015)
RADARSAT-2 Polarimetric SAR Response to Crop Biomass for Agricultural Production Monitoring
Grant Wiseman et al.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2014)
Modeling Aboveground Biomass in Tropical Forests Using Multi-Frequency SAR Data-A Comparison of Methods
Sandra Englhart et al.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2012)
Polarimetric SAR feature selection using a genetic algorithm
Ataollah Haddadi G. et al.
CANADIAN JOURNAL OF REMOTE SENSING (2011)
Support Vector Regression for the Estimation of Forest Stand Parameters Using Airborne Laser Scanning
Jean-Matthieu Monnet et al.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2011)
Applying support vector regression to water quality modelling by remote sensing data
Xili Wang et al.
INTERNATIONAL JOURNAL OF REMOTE SENSING (2011)
Impact of spatial variability of tropical forest structure on radar estimation of aboveground biomass
Sassan Saatchi et al.
REMOTE SENSING OF ENVIRONMENT (2011)
Retrieval of forest attributes in complex successional forests of Central Indonesia: Modeling and estimation of bitemporal data
Arief Wijaya et al.
FOREST ECOLOGY AND MANAGEMENT (2010)
Fitting a two-component scattering model to polarimetric SAR data from forests
Anthony Freeman
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2007)
Robust support vector regression for biophysical variable estimation from remotely sensed images
Gustavo Camps-Valls et al.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2006)
The potential and challenge of remote sensing-based biomass estimation
Dengsheng Lu
INTERNATIONAL JOURNAL OF REMOTE SENSING (2006)
Estimating biomass for boreal forests using ASTER satellite data combined with standwise forest inventory data
P Muukkonen et al.
REMOTE SENSING OF ENVIRONMENT (2005)
Four-component scattering model for polarimetric SAR image decomposition
Y Yamaguchi et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2005)
A tutorial on support vector regression
AJ Smola et al.
STATISTICS AND COMPUTING (2004)
Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions
GM Foody et al.
REMOTE SENSING OF ENVIRONMENT (2003)
Retrieval of oceanic chlorophyll concentration using support vector machines
HG Zhan et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2003)