Mapping Tree Species Composition Using OHS-1 Hyperspectral Data and Deep Learning Algorithms in Changbai Mountains, Northeast China

A Spectral Feature Based Convolutional Neural Network for Classification of Sea Surface Oil Spill

(2019) Bingxin Liu et al.   ISPRS International Journal of Geo-Information

Optimal Combination of Predictors and Algorithms for Forest Above-Ground Biomass Mapping from Sentinel and SRTM Data

(2019) Lin Chen et al.   Remote Sensing

A Deep Learning Model for Automated Sleep Stages Classification Using PSG Signals

(2019) Ozal Yildirim et al.   International Journal of Environmental Research and Public Health

Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors

(2019) Zhiwei Li et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Signal Status Recognition Based on 1DCNN and Its Feature Extraction Mechanism Analysis

(2019) Shuzhan Huang et al.   SENSORS

Deep learning – Method overview and review of use for fruit detection and yield estimation

(2019) Anand Koirala et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Evaluation of ten machine learning methods for estimating terrestrial evapotranspiration from remote sensing

(2019) Corinne Carter et al.   International Journal of Applied Earth Observation and Geoinformation

Meta-analysis of deep neural networks in remote sensing: A comparative study of mono-temporal classification to support vector machines

(2019) Shahriar S. Heydari et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Tree species classification using plant functional traits from LiDAR and hyperspectral data

(2018) Yifang Shi et al.   International Journal of Applied Earth Observation and Geoinformation

Urban land-use mapping using a deep convolutional neural network with high spatial resolution multispectral remote sensing imagery

(2018) Bo Huang et al.   REMOTE SENSING OF ENVIRONMENT

An object-based convolutional neural network (OCNN) for urban land use classification

(2018) Ce Zhang et al.   REMOTE SENSING OF ENVIRONMENT

Fully Convolutional Networks for Multisource Building Extraction From an Open Aerial and Satellite Imagery Data Set

(2018)   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Estimation of Forest Above-Ground Biomass by Geographically Weighted Regression and Machine Learning with Sentinel Imagery

(2018) Lin Chen et al.   Forests

Evaluation of Different Machine Learning Algorithms for Scalable Classification of Tree Types and Tree Species Based on Sentinel-2 Data

(2018) Mathias Wessel et al.   Remote Sensing

Guided Stochastic Gradient Descent Algorithm for inconsistent datasets

(2018) Anuraganand Sharma   APPLIED SOFT COMPUTING

Towards rapid assessments of tree species diversity and structure in fragmented tropical forests: A review of perspectives offered by remotely-sensed and field-based data

(2018) Elias Ganivet et al.   FOREST ECOLOGY AND MANAGEMENT

Classification of Hyperspectral Imagery based on spectral gradient, SVM and spatial random forest

(2018) Zhao Chunhui et al.   INFRARED PHYSICS & TECHNOLOGY

A scale robust convolutional neural network for automatic building extraction from aerial and satellite imagery

(2018) Shunping Ji et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Mapping Forest Cover in Northeast China from Chinese HJ-1 Satellite Data Using an Object-Based Algorithm

(2018) Chunying Ren et al.   SENSORS

Deep learning based multi-temporal crop classification

(2018) Liheng Zhong et al.   REMOTE SENSING OF ENVIRONMENT

Joint Deep Learning for land cover and land use classification

(2018) Ce Zhang et al.   REMOTE SENSING OF ENVIRONMENT

A comparison of deep networks with ReLU activation function and linear spline-type methods

(2018) Konstantin Eckle et al.   NEURAL NETWORKS

A new perspective: Recognizing online handwritten Chinese characters via 1-dimensional CNN

(2018) Ji Gan et al.   INFORMATION SCIENCES

Stacked sparse autoencoder in hyperspectral data classification using spectral-spatial, higher order statistics and multifractal spectrum features

(2017) Xiaoqing Wan et al.   INFRARED PHYSICS & TECHNOLOGY

A new deep convolutional neural network for fast hyperspectral image classification

(2017) M.E. Paoletti et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Evaluating deep learning architectures for Speech Emotion Recognition

(2017) Haytham M. Fayek et al.   NEURAL NETWORKS

Prediction of Dominant Forest Tree Species Using QuickBird and Environmental Data

(2017) Azadeh Abdollahnejad et al.   Forests

Gated Convolutional Neural Network for Semantic Segmentation in High-Resolution Images

(2017) Hongzhen Wang et al.   Remote Sensing

One-Dimensional Convolutional Neural Network Land-Cover Classification of Multi-Seasonal Hyperspectral Imagery in the San Francisco Bay Area, California

(2017) Daniel Guidici et al.   Remote Sensing

Random forest in remote sensing: A review of applications and future directions

(2016) Mariana Belgiu et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

LiDAR waveform features for tree species classification and their sensitivity to tree- and acquisition related parameters

(2016) A. Hovi et al.   REMOTE SENSING OF ENVIRONMENT

Review of studies on tree species classification from remotely sensed data

(2016) Fabian Ewald Fassnacht et al.   REMOTE SENSING OF ENVIRONMENT

Tree Species Classification Using Hyperspectral Imagery: A Comparison of Two Classifiers

(2016) Laurel Ballanti et al.   Remote Sensing

First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe

(2016) Markus Immitzer et al.   Remote Sensing

Object-Based Urban Tree Species Classification Using Bi-Temporal WorldView-2 and WorldView-3 Images

(2015) Dan Li et al.   Remote Sensing

Deep Convolutional Neural Networks for Hyperspectral Image Classification

(2015) Wei Hu et al.   Journal of Sensors

Vehicle Detection in Satellite Images by Hybrid Deep Convolutional Neural Networks

(2014) Xueyun Chen et al.   IEEE Geoscience and Remote Sensing Letters

Comparison of Feature Reduction Algorithms for Classifying Tree Species With Hyperspectral Data on Three Central European Test Sites

(2014) Fabian E. Fassnacht et al.   IEEE Journal of Selected Topics in Applied Earth Observations and 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

Classification of Australian Native Forest Species Using Hyperspectral Remote Sensing and Machine-Learning Classification Algorithms

(2013) Xiao Shang et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales

(2013) Aniruddha Ghosh et al.   International Journal of Applied Earth Observation and Geoinformation

Object-oriented mapping of urban trees using Random Forest classifiers

(2013) Anne Puissant et al.   International Journal of Applied Earth Observation and Geoinformation

Tree crown delineation and tree species classification in boreal forests using hyperspectral and ALS data

(2013) Michele Dalponte et al.   REMOTE SENSING OF ENVIRONMENT

Investigating multiple data sources for tree species classification in temperate forest and use for single tree delineation

(2012) Johannes Heinzel et al.   International Journal of Applied Earth Observation and Geoinformation

Mapping tree species composition in South African savannas using an integrated airborne spectral and LiDAR system

(2012) Moses Azong Cho et al.   REMOTE SENSING OF ENVIRONMENT

Tree species classification in the Southern Alps based on the fusion of very high geometrical resolution multispectral/hyperspectral images and LiDAR data

(2012) Michele Dalponte et al.   REMOTE SENSING OF ENVIRONMENT

Classification of urban tree species using hyperspectral imagery

(2012) Ryan R. Jensen et al.   Geocarto International

Species-Level Differences in Hyperspectral Metrics among Tropical Rainforest Trees as Determined by a Tree-Based Classifier

(2012) Matthew L. Clark et al.   Remote Sensing

Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data

(2012) Markus Immitzer et al.   Remote Sensing

Object-oriented mapping of landslides using Random Forests

(2011) André Stumpf et al.   REMOTE SENSING OF ENVIRONMENT

A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery

(2011) Dennis C. Duro et al.   REMOTE SENSING OF ENVIRONMENT

Forest Cover Classification by Optimal Segmentation of High Resolution Satellite Imagery

(2011) So-Ra Kim et al.   SENSORS

Evaluation of classifiers for processing Hyperion (EO-1) data of tropical vegetation

(2010) Dhaval Vyas et al.   International Journal of Applied Earth Observation and Geoinformation

Assessing the utility of airborne hyperspectral and LiDAR data for species distribution mapping in the coastal Pacific Northwest, Canada

(2010) Trevor G. Jones et al.   REMOTE SENSING OF ENVIRONMENT

Synergistic use of QuickBird multispectral imagery and LIDAR data for object-based forest species classification

(2010) Yinghai Ke et al.   REMOTE SENSING OF ENVIRONMENT

Application of hyperspectral vegetation indices to detect variations in high leaf area index temperate shrub thicket canopies

(2010) Steven T. Brantley et al.   REMOTE SENSING OF ENVIRONMENT

Mapping Bush Encroaching Species by Seasonal Differences in Hyperspectral Imagery

(2010) Jens Oldeland et al.   Remote Sensing

A multi-resolution satellite imagery approach for large area mapping of ericaceous shrubs in Northern Quebec, Canada

(2009) Olivier R. van Lier et al.   International Journal of Applied Earth Observation and Geoinformation

Object based image analysis for remote sensing

(2009) T. Blaschke   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING