Continuous Wavelet Analysis of Leaf Reflectance Improves Classification Accuracy of Mangrove Species
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Continuous Wavelet Analysis of Leaf Reflectance Improves Classification Accuracy of Mangrove Species
Authors
Keywords
-
Journal
Remote Sensing
Volume 11, Issue 3, Pages 254
Publisher
MDPI AG
Online
2019-01-29
DOI
10.3390/rs11030254
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A Technique for Subpixel Analysis of Dynamic Mangrove Ecosystems With Time-Series Hyperspectral Image Data
- (2018) Somdatta Chakravortty et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Classification of tree species based on longwave hyperspectral data from leaves, a case study for a tropical dry forest
- (2018) D. Harrison et al. International Journal of Applied Earth Observation and Geoinformation
- A comparison of resampling methods for remote sensing classification and accuracy assessment
- (2018) Mitchell B. Lyons et al. REMOTE SENSING OF ENVIRONMENT
- Artificial Mangrove Species Mapping Using Pléiades-1: An Evaluation of Pixel-Based and Object-Based Classifications with Selected Machine Learning Algorithms
- (2018) Dezhi Wang et al. Remote Sensing
- Wavelet-Based Rust Spectral Feature Set (WRSFs): A Novel Spectral Feature Set Based on Continuous Wavelet Transformation for Tracking Progressive Host–Pathogen Interaction of Yellow Rust on Wheat
- (2018) Yue Shi et al. Remote Sensing
- Object-Based Mangrove Species Classification Using Unmanned Aerial Vehicle Hyperspectral Images and Digital Surface Models
- (2018) Jingjing Cao et al. Remote Sensing
- Discrimination of mangrove species and mudflat classes using in situ hyperspectral data: a case study of Indian Sundarbans
- (2018) K.R. Manjunath et al. GIScience & Remote Sensing
- Estimation of area- and mass-based leaf nitrogen contents of wheat and rice crops from water-removed spectra using continuous wavelet analysis
- (2018) Dong Li et al. Plant Methods
- Assessment of defoliation during the Dendrolimus tabulaeformis Tsai et Liu disaster outbreak using UAV-based hyperspectral images
- (2018) Ning Zhang et al. REMOTE SENSING OF ENVIRONMENT
- Evaluating the Performance of Sentinel-2, Landsat 8 and Pléiades-1 in Mapping Mangrove Extent and Species
- (2018) Dezhi Wang et al. Remote Sensing
- Discrimination of liana and tree leaves from a Neotropical Dry Forest using visible-near infrared and longwave infrared reflectance spectra
- (2018) J. Antonio Guzmán Q. et al. REMOTE SENSING OF ENVIRONMENT
- Prediction of Forest Structural Parameters Using Airborne Full-Waveform LiDAR and Hyperspectral Data in Subtropical Forests
- (2018) Xin Shen et al. Remote Sensing
- WREP: A wavelet-based technique for extracting the red edge position from reflectance spectra for estimating leaf and canopy chlorophyll contents of cereal crops
- (2017) Dong Li et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Improvements of the Vis-NIRS Model in the Prediction of Soil Organic Matter Content Using Spectral Pretreatments, Sample Selection, and Wavelength Optimization
- (2017) Z. D. Lin et al. Journal of Applied Spectroscopy
- Mapping urban tree species using integrated airborne hyperspectral and LiDAR remote sensing data
- (2017) Luxia Liu et al. REMOTE SENSING OF ENVIRONMENT
- UAV lidar and hyperspectral fusion for forest monitoring in the southwestern USA
- (2017) Temuulen Sankey et al. REMOTE SENSING OF ENVIRONMENT
- Tree-Species Classification in Subtropical Forests Using Airborne Hyperspectral and LiDAR Data
- (2017) Xin Shen et al. Remote Sensing
- Representative subset selection and outlier detection via isolation forest
- (2016) Wo-Ruo Chen et al. Analytical Methods
- The use of airborne hyperspectral data for tree species classification in a species-rich Central European forest area
- (2016) Ronny Richter et al. International Journal of Applied Earth Observation and Geoinformation
- Retrieval of forest leaf functional traits from HySpex imagery using radiative transfer models and continuous wavelet analysis
- (2016) Abebe Mohammed Ali et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data
- (2016) Gaia Vaglio Laurin et al. REMOTE SENSING OF ENVIRONMENT
- Evaluating the Effectiveness of Conservation on Mangroves: A Remote Sensing-Based Comparison for Two Adjacent Protected Areas in Shenzhen and Hong Kong, China
- (2016) Mingming Jia et al. Remote Sensing
- Classification of crops across heterogeneous agricultural landscape in Kenya using AisaEAGLE imaging spectroscopy data
- (2015) Rami Piiroinen et al. International Journal of Applied Earth Observation and Geoinformation
- The potential of Indonesian mangrove forests for global climate change mitigation
- (2015) Daniel Murdiyarso et al. Nature Climate Change
- Multiple statistical approaches for the discrimination of mangrove species ofRhizophoraceaeusing transformed field and laboratory hyperspectral data
- (2015) Kumar Arun Prasad et al. Geocarto International
- Textural–Spectral Feature-Based Species Classification of Mangroves in Mai Po Nature Reserve from Worldview-3 Imagery
- (2015) Ting Wang et al. Remote Sensing
- Monitoring Soil Salinization in Keriya River Basin, Northwestern China Using Passive Reflective and Active Microwave Remote Sensing Data
- (2015) Ilyas Nurmemet et al. Remote Sensing
- Mapping the distribution of mangrove species in the Core Zone of Mai Po Marshes Nature Reserve, Hong Kong, using hyperspectral data and high-resolution data
- (2014) Mingming Jia et al. International Journal of Applied Earth Observation and Geoinformation
- Combining EO-1 Hyperion and Envisat ASAR data for mangrove species classification in Mai Po Ramsar Site, Hong Kong
- (2014) Frankie K. K. Wong et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Detecting diurnal and seasonal variation in canopy water content of nut tree orchards from airborne imaging spectroscopy data using continuous wavelet analysis
- (2014) Tao Cheng et al. REMOTE SENSING OF ENVIRONMENT
- Can flowers provide better spectral discrimination between herbaceous wetland species than leaves?
- (2014) John W. Gross et al. Remote Sensing Letters
- Plant Species Discrimination in a Tropical Wetland Using In Situ Hyperspectral Data
- (2014) Kurt Prospere et al. Remote Sensing
- Separating Mangrove Species and Conditions Using Laboratory Hyperspectral Data: A Case Study of a Degraded Mangrove Forest of the Mexican Pacific
- (2014) Chunhua Zhang et al. Remote Sensing
- Mangrove Species Identification: Comparing WorldView-2 with Aerial Photographs
- (2014) Muditha Heenkenda et al. Remote Sensing
- Prediction of low heavy metal concentrations in agricultural soils using visible and near-infrared reflectance spectroscopy
- (2013) Junjie Wang et al. GEODERMA
- Understanding the optical responses of leaf nitrogen in Mediterranean Holm oak (Quercus ilex) using field spectroscopy
- (2013) Javier Pacheco-Labrador et al. International Journal of Applied Earth Observation and Geoinformation
- Deriving leaf mass per area (LMA) from foliar reflectance across a variety of plant species using continuous wavelet analysis
- (2013) Tao Cheng et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Comparing endmember selection techniques for accurate mapping of plant species and land cover using imaging spectrometer data
- (2012) Keely L. Roth et al. REMOTE SENSING OF ENVIRONMENT
- Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment
- (2011) Robert Gilmore Pontius et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Mangrove species and stand mapping in Gazi bay (Kenya) using quickbird satellite imagery
- (2011) G. Neukermans et al. Journal of Spatial Science
- Seasonal changes in leaf chlorophyll a content and morphology in a sub-tropical mangrove forest of the Mexican Pacific
- (2011) F Flores-de-Santiago et al. MARINE ECOLOGY PROGRESS SERIES
- Satellite remote sensing of mangrove forests: Recent advances and future opportunities
- (2011) Benjamin W. Heumann PROGRESS IN PHYSICAL GEOGRAPHY
- Remote Sensing of Mangrove Ecosystems: A Review
- (2011) Claudia Kuenzer et al. Remote Sensing
- Hyperspectral Data for Mangrove Species Mapping: A Comparison of Pixel-Based and Object-Based Approach
- (2011) Muhammad Kamal et al. Remote Sensing
- Canopy phylogenetic, chemical and spectral assembly in a lowland Amazonian forest
- (2010) Gregory P. Asner et al. NEW PHYTOLOGIST
- Continuous wavelet analysis for the detection of green attack damage due to mountain pine beetle infestation
- (2010) T. Cheng et al. REMOTE SENSING OF ENVIRONMENT
- Spectroscopic determination of leaf water content using continuous wavelet analysis
- (2010) T. Cheng et al. REMOTE SENSING OF ENVIRONMENT
- Evaluation of Morphological Texture Features for Mangrove Forest Mapping and Species Discrimination Using Multispectral IKONOS Imagery
- (2009) Xin Huang et al. IEEE Geoscience and Remote Sensing Letters
- Estimation of sugarcane leaf nitrogen concentration using in situ spectroscopy
- (2009) Elfatih M. Abdel-Rahman et al. International Journal of Applied Earth Observation and Geoinformation
- Distinguishing mangrove species with laboratory measurements of hyperspectral leaf reflectance
- (2009) Le Wang et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Continuous wavelets for the improved use of spectral libraries and hyperspectral data
- (2008) B. Rivard et al. REMOTE SENSING OF ENVIRONMENT
- Retrieval of chlorophyll concentration from leaf reflectance spectra using wavelet analysis
- (2007) G BLACKBURN 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 MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started