RSC4Earth
RSC4Earth
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Teja Kattenborn
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Plant Trait Retrieval from Hyperspectral Data: Collective Efforts in Scientific Data Curation Outperform Simulated Data Derived from the PROSAIL Model
Deadtrees.Earth - An Open-Access and Interactive Database for Centimeter-Scale Aerial Imagery to Uncover Global Tree Mortality Dynamics
Earth System Data Cubes: Avenues for Advancing Earth System Research
Macrophenological Dynamics from Citizen Science Plant Occurrence Data
Biodiversity and Climate Extremes: Known Interactions and Research Gaps
AngleCam : Predicting the Temporal Variation of Leaf Angle Distributions from Image Series with Deep Learning
Citizen Science Plant Observations Encode Global Trait Patterns
Spatially Autocorrelated Training and Validation Samples Inflate Performance Assessment of Convolutional Neural Networks
Transfer Learning from Citizen Science Photographs Enables Plant Species Identification in UAV Imagery
Evaluating Different Methods for Retrieving Intraspecific Leaf Trait Variation from Hyperspectral Leaf Reflectance
Explaining Sentinel 2-Based dNBR and RdNBR Variability with Reference Data from the Bird's Eye (UAS) Perspective
Review on Convolutional Neural Networks (CNN) in Vegetation Remote Sensing
The Retrieval of Plant Functional Traits from Canopy Spectra through RTM-inversions and Statistical Models Are Both Critically Affected by Plant Phenology
Convolutional Neural Networks Accurately Predict Cover Fractions of Plant Species and Communities in Unmanned Aerial Vehicle Imagery
Mapping Forest Tree Species in High Resolution UAV-based RGB-imagery by Means of Convolutional Neural Networks
Detection of Xylella Fastidiosa Infection Symptoms with Airborne Multispectral and Thermal Imagery: Assessing Bandset Reduction Performance from Hyperspectral Analysis
TRY Plant Trait Database -- Enhanced Coverage and Open Access
Unmanned Aerial Vehicle-based Mapping of Turf-banked Solifluction Lobe Movement and Its Relation to Material, Geomorphometric, Thermal and Vegetation Properties
How Canopy Shadow Affects Invasive Plant Species Classification in High Spatial Resolution Remote Sensing
Convolutional Neural Networks Enable Efficient, Accurate and Fine-Grained Segmentation of Plant Species and Communities from High-Resolution UAV Imagery
Advantages of Retrieving Pigment Content [Mg/Cm2] versus Concentration [%] from Canopy Reflectance
Using Aboveground Vegetation Attributes as Proxies for Mapping Peatland Belowground Carbon Stocks
Proximal VIS-NIR Spectrometry to Retrieve Substance Concentrations in Surface Waters Using Partial Least Squares Modelling
UAV Data as Alternative to Field Sampling to Map Woody Invasive Species Based on Combined Sentinel-1 and Sentinel-2 Data
A Landsat-based Vegetation Trend Product of the Tibetan Plateau for the Time-Period 1990--2018
Radiative Transfer Modelling Reveals Why Canopy Reflectance Follows Function
Chlorophyll Content Estimation in an Open-Canopy Conifer Forest with Sentinel-2A and Hyperspectral Imagery in the Context of Forest Decline
Differentiating Plant Functional Types Using Reflectance: Which Traits Make the Difference?
PILOT STUDY ON THE RETRIEVAL OF DBH AND DIAMETER DISTRIBUTION OF DECIDUOUS FOREST STANDS USING CAST SHADOWS IN UAV-BASED ORTHOMOSAICS
Previsual Symptoms of Xylella Fastidiosa Infection Revealed in Spectral Plant-Trait Alterations
Estimating Stand Density, Biomass and Tree Species from Very High Resolution Stereo-Imagery -- towards an All-in-One Sensor for Forestry Applications?
Linking Plant Strategies and Plant Traits Derived by Radiative Transfer Modelling
Detecting the Spread of Invasive Species in Central Chile with a Sentinel-2 Time-Series
Building a Hybrid Land Cover Map with Crowdsourcing and Geographically Weighted Regression
Mapping Forest Biomass from Space -- Fusion of Hyperspectral EO1-hyperion Data and Tandem-X and WorldView-2 Canopy Height Models
Modeling Forest Biomass Using Very-High-Resolution Data—Combining Textural, Spectral and Photogrammetric Predictors Derived from Spaceborne Stereo Images
Automatic Single Tree Detection in Plantations Using UAV-based Photogrammetric Point Clouds
Potential of Unmanned Aerial Vehicle Based Photogrammetric Point Clouds for Automatic Single Tree Detection
Segmentation of Forest to Tree Objects
UAV-BASED PHOTOGRAMMETRIC POINT CLOUDS -- TREE STEM MAPPING IN OPEN STANDS IN COMPARISON TO TERRESTRIAL LASER SCANNER POINT CLOUDS
Forest Change Assessment and Corresponding Driver Analysis in the Magdalena Department, Colombia (1985-2010)
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