Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China
Published 2016 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China
Authors
Keywords
-
Journal
SENSORS
Volume 16, Issue 6, Pages 834
Publisher
MDPI AG
Online
2016-06-07
DOI
10.3390/s16060834
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Mapping forest biomass from space – Fusion of hyperspectral EO1-hyperion data and Tandem-X and WorldView-2 canopy height models
- (2015) Teja Kattenborn et al. International Journal of Applied Earth Observation and Geoinformation
- Spatio-temporal prediction of leaf area index of rubber plantation using HJ-1A/1B CCD images and recurrent neural network
- (2015) Bangqian Chen et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa
- (2015) Timothy Dube et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Radarsat-2 Backscattering for the Modeling of Biophysical Parameters of Regenerating Mangrove Forests
- (2015) Michele Cougo et al. Remote Sensing
- Estimation of floodplain aboveground biomass using multispectral remote sensing and nonparametric modeling
- (2014) İnci Güneralp et al. International Journal of Applied Earth Observation and Geoinformation
- Estimating montane forest above-ground biomass in the upper reaches of the Heihe River Basin using Landsat-TM data
- (2014) Xin Tian et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Above ground biomass estimation in an African tropical forest with lidar and hyperspectral data
- (2014) Gaia Vaglio Laurin et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass
- (2014) F.E. Fassnacht et al. REMOTE SENSING OF ENVIRONMENT
- Airborne multi-temporal L-band polarimetric SAR data for biomass estimation in semi-arid forests
- (2014) Mihai A. Tanase et al. REMOTE SENSING OF ENVIRONMENT
- Estimating Forest Aboveground Biomass by Combining ALOS PALSAR and WorldView-2 Data: A Case Study at Purple Mountain National Park, Nanjing, China
- (2014) Songqiu Deng et al. Remote Sensing
- Improving the Estimation of Above Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran)
- (2014) Sara Attarchi et al. Remote Sensing
- Improved Mapping of Tropical Forests With Optical and SAR Imagery, Part II: Above Ground Biomass Estimation
- (2013) Tuomas Hame et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2
- (2013) Shuai Gao et al. International Journal of Applied Earth Observation and Geoinformation
- Estimating tropical forest biomass more accurately by integrating ALOS PALSAR and Landsat-7 ETM+ data
- (2013) Tyas Mutiara Basuki et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Retrieval of forest growing stock volume by two different methods using Landsat TM images
- (2013) Sheng Zheng et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm
- (2012) Onisimo Mutanga et al. International Journal of Applied Earth Observation and Geoinformation
- Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa
- (2012) Gaia Vaglio Laurin et al. International Journal of Applied Earth Observation and Geoinformation
- Evaluating the potential to monitor aboveground biomass in forest and oil palm in Sabah, Malaysia, for 2000–2008 with Landsat ETM+ and ALOS-PALSAR
- (2012) Alexandra C. Morel et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Evaluation of most similar neighbour and random forest methods for imputing forest inventory variables using data from target and auxiliary stands
- (2012) Hooman Latifi et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Estimating aboveground carbon stocks of a forest affected by mountain pine beetle in Idaho using lidar and multispectral imagery
- (2012) Benjamin C. Bright et al. REMOTE SENSING OF ENVIRONMENT
- Understanding the relationship between aboveground biomass and ALOS PALSAR data in the forests of Guinea-Bissau (West Africa)
- (2012) João M.B. Carreiras et al. REMOTE SENSING OF ENVIRONMENT
- Comparison of precision of biomass estimates in regional field sample surveys and airborne LiDAR-assisted surveys in Hedmark County, Norway
- (2012) Erik Næsset et al. REMOTE SENSING OF ENVIRONMENT
- Achieving accuracy requirements for forest biomass mapping: A spaceborne data fusion method for estimating forest biomass and LiDAR sampling error
- (2012) P.M. Montesano et al. REMOTE SENSING OF ENVIRONMENT
- Retrieval of tropical forest biomass information from ALOS PALSAR data
- (2012) M. Mahmudur Rahman et al. Geocarto International
- A Review of Remote Sensing of Forest Biomass and Biofuel: Options for Small-Area Applications
- (2011) Colin J. Gleason et al. GIScience & Remote Sensing
- Support Vector Regression for the Estimation of Forest Stand Parameters Using Airborne Laser Scanning
- (2011) Jean-Matthieu Monnet et al. IEEE Geoscience and Remote Sensing Letters
- Multioutput Support Vector Regression for Remote Sensing Biophysical Parameter Estimation
- (2011) D. Tuia et al. IEEE Geoscience and Remote Sensing Letters
- Forest stand biomass estimation using ALOS PALSAR data based on LiDAR-derived prior knowledge in the Qilian Mountain, western China
- (2011) Qi-Sheng He et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- L- and P-band backscatter intensity for biomass retrieval in hemiboreal forest
- (2011) G. Sandberg et al. REMOTE SENSING OF ENVIRONMENT
- Measuring biomass changes due to woody encroachment and deforestation/degradation in a forest–savanna boundary region of central Africa using multi-temporal L-band radar backscatter
- (2011) E.T.A. Mitchard et al. REMOTE SENSING OF ENVIRONMENT
- Impact of spatial variability of tropical forest structure on radar estimation of aboveground biomass
- (2011) Sassan Saatchi et al. REMOTE SENSING OF ENVIRONMENT
- Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3
- (2011) Jochem Verrelst et al. REMOTE SENSING OF ENVIRONMENT
- Non-parametric prediction and mapping of standing timber volume and biomass in a temperate forest: application of multiple optical/LiDAR-derived predictors
- (2010) H. Latifi et al. FORESTRY
- Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment
- (2010) Barbara Koch ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques
- (2010) Sudhanshu Sekhar Panda et al. Remote Sensing
- Importance of biomass in the global carbon cycle
- (2009) R. A. Houghton et al. JOURNAL OF GEOPHYSICAL RESEARCH
- Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser
- (2008) Erik Næsset et al. REMOTE SENSING OF ENVIRONMENT
- Non-parametric and parametric methods using satellite images for estimating growing stock volume in alpine and Mediterranean forest ecosystems
- (2008) Gherardo Chirici et al. REMOTE SENSING OF ENVIRONMENT
- Regional aboveground forest biomass using airborne and spaceborne LiDAR in Québec
- (2008) J BOUDREAU et al. REMOTE SENSING OF ENVIRONMENT
- Lidar remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers
- (2008) Kaiguang Zhao et al. REMOTE SENSING OF ENVIRONMENT
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now