Object-based Vegetation Mapping in the Kissimmee River Watershed Using HyMap Data and Machine Learning Techniques

No abstract is available for this paper.

• Publication year

  2013

• Venue

  Wetlands (Wilmington, N.C.)

• Publication date

  2013-01-17

• Fields of study

  Computer Science, Environmental Science

• Identifiers
  DOI 10.1007/s13157-012-0373-x
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Data fusion and classifier ensemble techniques for vegetation mapping in the coastal Everglades

  2014influential reference
• Combining object-based texture measures with a neural network for vegetation mapping in the Everglades from hyperspectral imagery

  2012influential reference
• An assessment of the effectiveness of a random forest classifier for land-cover classification

  2012influential reference
• LIBSVM: A library for support vector machines

  2011cited by this paper
• Remote Sensing of Vegetation Pattern and Condition to Monitor Changes in Everglades Biogeochemistry

  2011cited by this paper
• Hyperspectral Data for Mangrove Species Mapping: A Comparison of Pixel-Based and Object-Based Approach

  2011cited by this paper
• Object based image analysis for remote sensing

  2010cited by this paper
• Assessing object-based classification: advantages and limitations

  2009cited by this paper
• Increasing hyperspectral image classification accuracy for data sets with limited training samples by sample interpolation

  2009cited by this paper
• Applying image transformation and classification techniques to airborne hyperspectral imagery for mapping Ashe juniper infestations

  2009cited by this paper
• Mapping of hyperspectral AVIRIS data using machine-learning algorithms

  2009influential reference
• The WEKA data mining software: an update

  2009influential reference
• Development of vegetation maps for assessing Everglades restoration progress

  2008cited by this paper
• A Practical Guide to Support Vector Classication

  2008cited by this paper
• Evaluation of random forest and adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery

  2008cited by this paper
• Mapping an inland wetland complex using hyperspectral imagery

  2008cited by this paper
• Classifying segmented hyperspectral data from a heterogeneous urban environment using support vector machines

  2007cited by this paper
• Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing

  2006cited by this paper
• Some issues in the classification of DAIS hyperspectral data

  2006cited by this paper
• Mapping invasive plants using hyperspectral imagery and Breiman Cutler classifications (RandomForest)

  2006cited by this paper
• Random Forests for land cover classification

  2006cited by this paper
• Investigation of the random forest framework for classification of hyperspectral data

  2005cited by this paper
• Kernel-based methods for hyperspectral image classification

  2005cited by this paper
• Hyperspectral remote sensing of marsh species and plant vigour gradient in the New Jersey Meadowlands

  2005cited by this paper
• Application of multiple endmember spectral mixture analysis (MESMA) to AVIRIS imagery for coastal salt marsh mapping: a case study in China Camp, CA, USA

  2005cited by this paper
• Classification of Iowa wetlands using an airborne hyperspectral image: a comparison of the spectral angle mapper classifier and an object-oriented approach

  2005cited by this paper
• Classification of hyperspectral remote sensing images with support vector machines

  2004cited by this paper
• Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy

  2004cited by this paper
• Mapping Coastal Vegetation Using an Expert System and Hyperspectral Imagery

  2004cited by this paper
• Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information

  2004cited by this paper
• Random forests of binary hierarchical classifiers for analysis of hyperspectral data

  2003cited by this paper
• Hyperspectral image data for mapping wetland vegetation

  2003cited by this paper
• An assessment of support vector machines for land cover classi(cid:142) cation

  2002cited by this paper
• An assessment of two classification methods for mapping Thames Estuary intertidal habitats using CASI data

  2002cited by this paper
• Random Forests

  2001cited by this paper
• The Nature of Statistical Learning Theory

  2000cited by this paper
• Support vector machines for hyperspectral remote sensing classification

  1999cited by this paper
• The Nature of Statistical Learning

  1995cited by this paper
• WETLANDS

  1995cited by this paper
• Hierarchy in Picture Segmentation: A Stepwise Optimization Approach

  1989cited by this paper
• A transformation for ordering multispectral data in terms of image quality with implications for noise removal

  1988cited by this paper
• A Quantitative Method to Test for Consistency and Correctness in Photointerpretation

  1983cited by this paper
• The measurement of observer agreement for categorical data.

  1977influential reference
• ISPRS Journal of Photogrammetry and Remote Sensing

  year unknowncited by this paper
• Isprs Journal of Photogrammetry and Remote Sensing ( ) – Isprs Journal of Photogrammetry and Remote Sensing Unsupervised Image Segmentation Evaluation and Refinement Using a Multi-scale Approach

  year unknowncited by this paper

• Mapping wetland vegetation associations in the Yellow River Delta: a phenology-based segmentation approach using dense Sentinel-2 time series

  2026cites this paper
• AI-based approaches for wetland mapping and classification: A review of current practices and future perspectives

  2025cites this paper
• Comparison of Machine-Learning Algorithms for SPOT 7 Multispectral Image Classification

  2025cites this paper
• Fast Semantic Segmentation of Ultra-High-Resolution Remote Sensing Images via Score Map and Fast Transformer-Based Fusion

  2024cites this paper
• High-Resolution Seagrass Species Mapping and Propeller Scars Detection in Tanjung Benoa, Bali through UAV Imagery

  2024cites this paper
• Evaluation of machine learning algorithm capability for Bosten Lake Wetland classification based on multi-temporal Sentinel-2 data

  2024cites this paper
• Comparison between Parametric and Non-Parametric Supervised Land Cover Classifications of Sentinel-2 MSI and Landsat-8 OLI Data

  2023cites this paper
• Integration of Vis–NIR Spectroscopy and Machine Learning Techniques to Predict Eight Soil Parameters in Alpine Regions

  2023cites this paper
• A comparative study of the performances of joint RFE with machine learning algorithms for extracting Moso bamboo (Phyllostachys pubescens) forest based on UAV hyperspectral images

  2023cites this paper
• Revealing the Structure and Composition of the Restored Vegetation Cover in Semi-Arid Mine Dumps Based on LiDAR and Hyperspectral Images

  2022cites this paper
• Short-time-series grassland mapping using Sentinel-2 imagery and deep learning-based architecture

  2022cites this paper
• Very High-Resolution Imagery and Machine Learning for Detailed Mapping of Riparian Vegetation and Substrate Types

  2022cites this paper
• Comparison of Random Forest and Support Vector Machine Classifiers for Regional Land Cover Mapping Using Coarse Resolution FY-3C Images

  2022influential citation
• Machine learning algorithm-based risk assessment of riparian wetlands in Padma River Basin of Northwest Bangladesh

  2021cites this paper
• Shallow-Water Benthic Habitat Mapping Using Drone with Object Based Image Analyses

  2021cites this paper
• Unlocking the potential of hyperspectral and LiDAR for above-ground biomass (AGB) and tree species classification in tropical forests

  2021cites this paper
• Comparison and assessment of different object-based classifications using machine learning algorithms and UAVs multispectral imagery: a case study in a citrus orchard and an onion crop

  2021cites this paper
• Object-Based Wetland Vegetation Classification Using Multi-Feature Selection of Unoccupied Aerial Vehicle RGB Imagery

  2021cites this paper
• Object-based classification of vegetation species in a subtropical wetland using Sentinel-1 and Sentinel-2A images

  2021cites this paper
• Unmanned Aircraft System Photogrammetry for Mapping Diverse Vegetation Species in a Heterogeneous Coastal Wetland

  2020cites this paper
• Accounting for training data error in machine 2 learning applied to Earth observations

  2020cites this paper
• THIS IS A POST PRINT Published

  2020cites this paper
• Comparison of machine learning classification algorithms for land cover change in a coastal area affected by the 2010 Earthquake and Tsunami in Chile.

  2020cites this paper
• PEMETAAN HABITAT BENTIK BERBASIS OBJEK MENGGUNAKAN CITRA SENTINEL-2 DI PERAIRAN PULAU WANGI-WANGI KABUPATEN WAKATOBI OBJECT BASED MAPPING ON BENTHIC HABITAT USING SENTINEL-2 IMAGERY OF THE WANGI-WANGI ISLAND WATERS OF THE WAKATOBI DISTRICT

  2020cites this paper
• Estimating the Growing Stem Volume of Chinese Pine and Larch Plantations based on Fused Optical Data Using an Improved Variable Screening Method and Stacking Algorithm

  2020cites this paper
• Mapping multiple tree species classes using a hierarchical procedure with optimized node variables and thresholds based on high spatial resolution satellite data

  2020cites this paper
• Discrimination of species composition types of a grazed pasture landscape using Sentinel-1 and Sentinel-2 data

  2020cites this paper
• Literature Review of Methodologies for Vegetation Identification and Removal from UAV-Based Photogrammetric DSMs for the Waste Isolation Pilot Plant

  2020cites this paper
• Mapping Vegetation and Seasonal Thaw Depth in Central Alaska Using Airborne Hyperspectral and LiDAR Data

  2020cites this paper
• Development of an Object-Based Interpretive System Based on Weighted Scoring Method in a Multi-Scale Manner

  2019cites this paper
• A Review of Remote Sensing Approaches for Monitoring Blue Carbon Ecosystems: Mangroves, Seagrasses and Salt Marshes during 2010–2018

  2019influential citation
• Critical Analysis of Urban Vegetation Mapping by Satellite Multispectral and Airborne Hyperspectral Imagery

  2019cites this paper
• Identification of most spectrally distinguishable phenological stage of invasive Phramites australis in Lake Erie wetlands (Canada) for accurate mapping using multispectral satellite imagery

  2019cites this paper
• High-Resolution Vegetation Mapping Using eXtreme Gradient Boosting Based on Extensive Features

  2019cites this paper
• Multitemporal Hyperspectral Data Fusion with Topographic Indices - Improving Classification of Natura 2000 Grassland Habitats

  2019cites this paper
• Hyperspectral Data Analysis for Arid Vegetation Species : Smart & Sustainable Growth

  2019cites this paper
• Accounting for Training Data Error in Machine Learning Applied to Earth Observations

  2019cites this paper
• Crop mapping and yield estimation of wheat in the Bekaa plain of Lebanon. (Cartographie et prédiction de la productivité du blé cultivé dans la Plaine de la Bekaa, Liban)

  2019cites this paper
• Urban vegetation mapping by airborne hyperspetral imagery; feasibility and limitations

  2018cites this paper
• Combining Earth Observation and predictive modelling for multi-scale and multi-level biodiversity assessment and monitoring

  2018cites this paper
• Classification of Expansive Grassland Species in Different Growth Stages Based on Hyperspectral and LiDAR Data

  2018cites this paper
• Urban vegetation mapping by airborne hyperspetral imagery; feasibility and limitations

  2018cites this paper
• Hyperspectral Remote Sensing of Forests: Technological advancements, Opportunities and Challenges

  2018cites this paper
• Urban Vegetation Mapping Using Hyperspectral Imagery and Spectral Library

  2018cites this paper
• Impact of ecological redundancy on the performance of machine learning classifiers in vegetation mapping

  2018cites this paper
• A Novel Approach for Mapping Wheat Areas Using High Resolution Sentinel-2 Images

  2018cites this paper
• Implementation of machine-learning classification in remote sensing: an applied review

  2018cites this paper
• A New Synergistic Approach for Monitoring Wetlands Using 1 Sentinels-1 and 2 data With Object-based Machine Learning 2 Algorithms 3

  2018cites this paper
• Classification of High-Mountain Vegetation Communities within a Diverse Giant Mountains Ecosystem Using Airborne APEX Hyperspectral Imagery

  2018cites this paper
• A new synergistic approach for monitoring wetlands using Sentinels -1 and 2 data with object-based machine learning algorithms

  2018cites this paper
• Mapping freshwater marsh species in the wetlands of Lake Okeechobee using very high-resolution aerial photography and lidar data

  2018cites this paper
• Hyperspectral satellite data analysis for pure pixels extraction and evaluation of advanced classifier algorithms for LULC classification

  2018cites this paper
• Applying time series Landsat data for vegetation change analysis in the Florida Everglades Water Conservation Area 2A during 1996-2016

  2017cites this paper
• Co-Orbital Sentinel 1 and 2 for LULC Mapping with Emphasis on Wetlands in a Mediterranean Setting Based on Machine Learning

  2017cites this paper
• Subalpine and alpine vegetation classification based on hyperspectral APEX and simulated EnMAP images

  2017cites this paper
• Phenology-based Spartina alterniflora mapping in coastal wetland of the Yangtze Estuary using time series of GaoFen satellite no. 1 wide field of view imagery

  2017cites this paper
• Opportunities and Constraints in Characterizing Landscape Distribution of an Invasive Grass from Very High Resolution Multi-Spectral Imagery

  2017cites this paper
• Evaluating an unmanned aerial vehicle-based approach for assessing habitat extent and condition in fine-scale early successional mountain mosaics

  2016cites this paper
• A Framework to Combine Three Remotely Sensed Data Sources for Vegetation Mapping in the Central Florida Everglades

  2016cites this paper
• Knowledge-Based Raster Mapping Approach to Wetland Assessment: a Case Study in Suzhou, China

  2016cites this paper
• Object-Based Tree Species Classification in Urban Ecosystems Using LiDAR and Hyperspectral Data

  2016cites this paper
• Channel bar feature extraction for a mining-contaminated river using high-spatial multispectral remote-sensing imagery

  2016cites this paper
• Tree Species Classification Using Hyperspectral Imagery: A Comparison of Two Classifiers

  2016cites this paper
• An object-based SVM method incorporating optimal segmentation scale estimation using Bhattacharyya Distance for mapping salt cedar (Tamarisk spp.) with QuickBird imagery

  2015cites this paper
• Applying data fusion techniques for benthic habitat mapping and monitoring in a coral reef ecosystem

  2015influential citation
• Prediction of water quality index in constructed wetlands using support vector machine

  2015cites this paper
• Object-Based Image Analysis in Wetland Research: A Review

  2015influential citation
• Data fusion and classifier ensemble techniques for vegetation mapping in the coastal Everglades

  2014cites this paper
• Combining Hyperspectral and Lidar Data for Vegetation Mapping in the Florida Everglades

  2014influential citation
• Fusing lidar and digital aerial photography for object-based forest mapping in the Florida Everglades

  2013influential citation
• Object-based benthic habitat mapping in the Florida Keys from hyperspectral imagery

  2013influential citation
• Accounting for training data error in machine learning applied to Accounting for training data error in machine learning applied to earth observations earth observations

  year unknowncites this paper