An End-to-End Deep Fusion Model for Mapping Forests at Tree Species Levels with High Spatial Resolution Satellite Imagery

Deep learning in environmental remote sensing: Achievements and challenges

(2020) Qiangqiang Yuan et al.   REMOTE SENSING OF ENVIRONMENT

An Improved Res-UNet Model for Tree Species Classification Using Airborne High-Resolution Images

(2020) Kaili Cao et al.   Remote Sensing

Classification of Land Cover, Forest, and Tree Species Classes with ZiYuan-3 Multispectral and Stereo Data

(2019) Zhuli Xie et al.   Remote Sensing

Deep learning and process understanding for data-driven Earth system science

(2019) Markus Reichstein et al.   NATURE

Mapping Forest Type and Tree Species on a Regional Scale Using Multi-Temporal Sentinel-2 Data

(2019) Agata Hościło et al.   Remote Sensing

Deep Learning Approaches for the Mapping of Tree Species Diversity in a Tropical Wetland Using Airborne LiDAR and High-Spatial-Resolution Remote Sensing Images

(2019) Ying Sun et al.   Forests

Combining Sentinel-1 and Sentinel-2 Satellite Image Time Series for land cover mapping via a multi-source deep learning architecture

(2019) Dino Ienco et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Enhanced Fusion of Deep Neural Networks for Classification of Benchmark High-Resolution Image Data Sets

(2018) Grant J. Scott et al.   IEEE Geoscience and Remote Sensing Letters

A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification

(2018) Ce Zhang et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

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

Very Deep Convolutional Neural Networks for Complex Land Cover Mapping Using Multispectral Remote Sensing Imagery

(2018) Masoud Mahdianpari et al.   Remote Sensing

A Two-Branch CNN Architecture for Land Cover Classification of PAN and MS Imagery

(2018) Raffaele Gaetano et al.   Remote Sensing

Joint Deep Learning for land cover and land use classification

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

Fusion of Deep Convolutional Neural Networks for Land Cover Classification of High-Resolution Imagery

(2017) Grant J. Scott et al.   IEEE Geoscience and Remote Sensing Letters

Fully Convolutional Networks for Semantic Segmentation

(2017) Evan Shelhamer et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Learning multiscale and deep representations for classifying remotely sensed imagery

(2016) Wenzhi Zhao et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Assessing the utility WorldView-2 imagery for tree species mapping in South African subtropical humid forest and the conservation implications: Dukuduku forest patch as case study

(2015) Moses Azong Cho et al.   International Journal of Applied Earth Observation and Geoinformation

On combining multiscale deep learning features for the classification of hyperspectral remote sensing imagery

(2015) Wenzhi Zhao et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Nearest-neighbor diffusion-based pan-sharpening algorithm for spectral images

(2014) Weihua Sun et al.   OPTICAL ENGINEERING

Employing ground and satellite-based QuickBird data and random forest to discriminate five tree species in a Southern African Woodland

(2014) Samuel Adelabu et al.   Geocarto International

Object-Based Land-Cover Mapping with High Resolution Aerial Photography at a County Scale in Midwestern USA

(2014) Xiaoxiao Li et al.   Remote Sensing

Evaluating the Potential of WorldView-2 Data to Classify Tree Species and Different Levels of Ash Mortality

(2014) Lars Waser et al.   Remote Sensing

Object-Based Spatial Feature for Classification of Very High Resolution Remote Sensing Images

(2013) Penglin Zhang et al.   IEEE Geoscience and Remote Sensing Letters

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

(2012) Markus Immitzer et al.   Remote Sensing

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

Towards automated forest-type mapping – a service within GSE Forest Monitoring based on SPOT-5 and IKONOS data

(2009) C. Eisfelder et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Remote sensing imagery in vegetation mapping: a review

(2008) Y. Xie et al.   Journal of Plant Ecology