Comparison of Canopy Closure Estimation of Plantations Using Parametric, Semi-Parametric, and Non-Parametric Models Based on GF-1 Remote Sensing Images
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Comparison of Canopy Closure Estimation of Plantations Using Parametric, Semi-Parametric, and Non-Parametric Models Based on GF-1 Remote Sensing Images
Authors
Keywords
-
Journal
Forests
Volume 11, Issue 5, Pages 597
Publisher
MDPI AG
Online
2020-05-25
DOI
10.3390/f11050597
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Estimating vertical canopy cover using dense image-based point cloud data in four vegetation types in southern Sweden
- (2017) Ann-Helen Granholm et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Assessing the performance of aerial image point cloud and spectral metrics in predicting boreal forest canopy cover
- (2017) M. Melin et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Comparison of Sentinel-2 and Landsat 8 in the estimation of boreal forest canopy cover and leaf area index
- (2017) Lauri Korhonen et al. REMOTE SENSING OF ENVIRONMENT
- The accuracy of large-area forest canopy cover estimation using Landsat in boreal region
- (2016) Hadi et al. International Journal of Applied Earth Observation and Geoinformation
- Comparison of Three Landsat TM Compositing Methods: A Case Study Using Modeled Tree Canopy Cover
- (2016) Bonnie Ruefenacht PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
- Canopy cover estimation in miombo woodlands of Zambia: Comparison of Landsat 8 OLI versus RapidEye imagery using parametric, nonparametric, and semiparametric methods
- (2016) James Halperin et al. REMOTE SENSING OF ENVIRONMENT
- Liana canopy cover mapped throughout a tropical forest with high-fidelity imaging spectroscopy
- (2016) David C. Marvin et al. REMOTE SENSING OF ENVIRONMENT
- Multi-criteria evaluation of topographic correction methods
- (2016) Ion Sola et al. REMOTE SENSING OF ENVIRONMENT
- Assessment of Forest Structure Using Two UAV Techniques: A Comparison of Airborne Laser Scanning and Structure from Motion (SfM) Point Clouds
- (2016) Luke Wallace et al. Forests
- Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation
- (2016) Panpan Zhao et al. Remote Sensing
- A review of radar remote sensing for biomass estimation
- (2015) S. Sinha et al. International Journal of Environmental Science and Technology
- Savannah woody structure modelling and mapping using multi-frequency (X-, C- and L-band) Synthetic Aperture Radar data
- (2015) Laven Naidoo et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Characterizing stand-level forest canopy cover and height using Landsat time series, samples of airborne LiDAR, and the Random Forest algorithm
- (2015) Oumer S. Ahmed et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Assessment of the mapping of fractional woody cover in southern African savannas using multi-temporal and polarimetric ALOS PALSAR L-band images
- (2015) Mikhail Urbazaev et al. REMOTE SENSING OF ENVIRONMENT
- Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest
- (2015) Martin Karlson et al. Remote Sensing
- Canopy closure, LAI and radiation transfer from airborne LiDAR synthetic images
- (2014) D. Moeser et al. AGRICULTURAL AND FOREST METEOROLOGY
- Evaluation of the spatial linear model, random forest and gradient nearest-neighbour methods for imputing potential productivity and biomass of the Pacific Northwest forests
- (2014) H. Temesgen et al. FORESTRY
- Bringing an ecological view of change to Landsat-based remote sensing
- (2014) Robert E Kennedy et al. FRONTIERS IN ECOLOGY AND THE ENVIRONMENT
- Topographic Correction of ZY-3 Satellite Images and Its Effects on Estimation of Shrub Leaf Biomass in Mountainous Areas
- (2014) Ming-Liang Gao et al. Remote Sensing
- Assessing woody biomass in African tropical savannahs by multiscale remote sensing
- (2013) Weicheng Wu et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Conterminous United States demonstration and characterization of MODIS-based Landsat ETM+ atmospheric correction
- (2013) D.P. Roy et al. REMOTE SENSING OF ENVIRONMENT
- A cross-comparison of field, spectral, and lidar estimates of forest canopy cover
- (2011) Alistair M.S. Smith et al. CANADIAN JOURNAL OF REMOTE SENSING
- Airborne discrete-return LIDAR data in the estimation of vertical canopy cover, angular canopy closure and leaf area index
- (2011) Lauri Korhonen et al. REMOTE SENSING OF ENVIRONMENT
- C-correction of optical satellite data over alpine vegetation areas: A comparison of sampling strategies for determining the empirical c-parameter
- (2011) Heather Reese et al. REMOTE SENSING OF ENVIRONMENT
- Retrieval of subpixel Tamarix canopy cover from Landsat data along the Forgotten River using linear and nonlinear spectral mixture models
- (2010) J.L. Silván-Cárdenas et al. REMOTE SENSING OF ENVIRONMENT
- Variation in properties ofPhlebiopsis gigantearelated to biocontrol against infection byHeterobasidionspp. in Norway spruce stumps
- (2009) H. Sun et al. FOREST PATHOLOGY
- Estimation of forest structural parameters using 5 and 10 meter SPOT-5 satellite data
- (2009) Peter T. Wolter et al. REMOTE SENSING OF ENVIRONMENT
- Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors
- (2009) Gyanesh Chander et al. REMOTE SENSING OF ENVIRONMENT
- Scaling-based forest structural change detection using an inverted geometric-optical model in the Three Gorges region of China
- (2008) Y ZENG et al. REMOTE SENSING OF ENVIRONMENT
- Large area mapping of southwestern forest crown cover, canopy height, and biomass using the NASA Multiangle Imaging Spectro-Radiometer
- (2008) Mark Chopping et al. REMOTE SENSING OF ENVIRONMENT
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started