All Stories

  1. AngleCam V2: Predicting leaf inclination angles across taxa from daytime and nighttime photos
  2. Navigating challenges in spatial machine learning: Validation, uncertainty, algorithms, and reproducibility
  3. Leveraging remote sensing and crowd-sourced biodiversity data for enhanced plant functional trait mapping
  4. Uncertainty Assessment in Deep Learning-based Plant Trait Retrievals from Hyperspectral data
  5. 3Dtrees.earth - A platform for accessing, analyzing, and visualizing LiDAR data in forest environments
  6. Benchmarking Large-scale Forest Disturbance Products
  7. Combining satellite-derived forest deadwood estimates and vegetation modelling to predict drought impacts on Norway spruce forest biomass, timber harvest and carbon cycling in Central Europe
  8. DeepFeatures: Learning Latent Representations from Spectral Indices for Ecosystem Monitoring
  9. From Trees to Forest Inventories: Do End‑to‑End LiDAR Pipelines Really Work?
  10. Global shifts in Earth’s seasonal green wave
  11. Temporal dynamics of stress signal propagation across ecosystem scales during a hot and dry period: A multi-sensor analysis
  12. Tree Mortality in Boreal Primary Forests is Sensitive to Climate and Stand Structure: High-Resolution Evidence Across a Gradient of Protected Landscapes
  13. Nationwide deadwood mapping reveals rising mountain forests vulnerability
  14. Soil compaction by forest management creates hotspots of BVOC emissions in a temperate mixed forest
  15. The seismic fingerprint of wind-induced tree sway  
  16. Litter vs. Lens: Evaluating LAI from Litter Traps and Hemispherical Photos Across View Zenith Angles and Leaf Fall Phases
  17. Controls of spatio-temporal patterns of soil respiration in a mixed forest
  18. Strong toluene and p-cymene emission from waterlogged hotspots of a temperate mixed-forest soil
  19. Supplementary material to "Strong toluene and p-cymene emission from waterlogged hotspots of a temperate mixed-forest soil"
  20. Global, multi-scale standing deadwood segmentation in centimeter-scale aerial images
  21. Automated mask generation in citizen science smartphone photos and their value for mapping plant species in drone imagery
  22. Supplementary material to "The ECOSENSE forest: A distributed sensor and data management system for real-time monitoring of ecosystem processes and stresses"
  23. The ECOSENSE forest: A distributed sensor and data management system for real-time monitoring of ecosystem processes and stresses
  24. The seismic fingerprint of wind‐induced tree sway
  25. Unraveling the seasonality of functional diversity through remote sensing
  26. AngleCam V2: Predicting leaf inclination angles across taxa from daytime and nighttime photos
  27. Litter vs. Lens: Evaluating LAI from Litter Traps and Hemispherical Photos Across View Zenith Angles and Leaf Fall Phases
  28. Prediction in trait-based ecology: global simulations of specific leaf area using a trait-based dynamic vegetation model
  29. Supplementary material to "Uncertainty Assessment in Deep Learning-based Plant Trait Retrievals from Hyperspectral data"
  30. Uncertainty Assessment in Deep Learning-based Plant Trait Retrievals from Hyperspectral data
  31. Forest Dieback in Drinking Water Protection Areas—A Hidden Threat to Water Quality
  32. TreeAI: a global database for tree species annotations and high-resolution aerial imagery
  33. Anthropocene Plant Migration: Regional Shifts in Trait Patterns and Functional Diversity
  34. Deep learning for identification of 3D plant growth forms in Fractional Vegetation Cover
  35. Forest Dieback Poses a Hidden Threat to Drinking Water Quality
  36. From satellites to smartphones: harnessing citizen science and Earth observation to unlock global perspectives on plant functional diversity
  37. PlantTraitNet: A Multi-Modal, Multi-Task Approach to Learning Global Plant Trait Patterns Using Citizen Science Data and Noisy Labels
  38. Seasonal and Diurnal Dynamics of Sun-Induced Fluorescence and Photosynthesis in Fagus sylvatica and Tilia cordata.
  39. deadtrees.earth: tree mortality monitoring from local to global scales with AI and remote sensing
  40. Elucidating spatio-temporal throughfall dynamics with ULS derived forest structure density metrics
  41. Mapping Fractional Tree Mortality and Tree Cover at Global Scale Using Sentinel-1 and 2
  42. Mapping Tree Hydraulics and Assemblages at Continental Scale
  43. Plant macrophenological dynamics - variations in plant group behaviour revealed by citizen science data
  44. The Seismic Fingerprint of Tree Sway
  45. From Ground Photos to Aerial Insights: Automating Citizen Science Labeling for Tree Species Segmentation in UAV Images
  46. Large-scale remote sensing reveals that tree mortality in Germany appears to be greater than previously expected
  47. Plant trait retrieval from hyperspectral data: Collective efforts in scientific data curation outperform simulated data derived from the PROSAIL model
  48. Crowd-sourced trait data can be used to delimit global biomes
  49. Large-scale remote sensing reveals that tree mortality in Germany appears to be greater than previously expected
  50. Temporal dynamics in vertical leaf angles can confound vegetation indices widely used in Earth observations
  51. Forest dieback in drinking water protection areas – a hidden threat to water quality
  52. Macrophenological dynamics from citizen science plant occurrence data
  53. From simple labels to semantic image segmentation: leveraging citizen science plant photographs for tree species mapping in drone imagery
  54. DeepFeatures: Remote sensing beyond spectral indices
  55. High-resolution mapping of tree mortality in European forests
  56. Plant macrophenological dynamics - from individuals to plant group behaviour using citizen science data
  57. Global-scale plant trait-environment relationships based on sPlotOpen and TRY data
  58. deadtrees.earth - an open, dynamic database for accessing, contributing, analyzing, and visualizing remote sensing-based tree mortality data.
  59. Combining citizen science and Earth observation data to produce global maps of 31 plant traits
  60. How trees sway and what it tells us about their overall vitality
  61. Investigating Deep Learning Techniques to Estimate Fractional Vegetation Cover in the Australian Semi-arid Ecosystems combining Drone-based RGB imagery, multispectral Imagery and LiDAR data.
  62. Leveraging Crowd-sourced Biodiversity Data for an Enhanced Plant Functional Trait Mapping
  63. TRY - Plant Trait Database
  64. Crowd-sourced trait data can be used to delimit global biomes
  65. Supplementary material to "Crowd-sourced trait data can be used to delimit global biomes"
  66. Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches
  67. From simple labels to semantic image segmentation: Leveraging citizen science plant photographs for tree species mapping in drone imagery
  68. Biodiversity and climate extremes: known interactions and research gaps
  69. Pattern to process, research to practice: remote sensing of plant invasions
  70. Data Cubes for Earth System Research: Challenges Ahead
  71. Monitoring solifluction movement in space and time: A semi-automated high-resolution approach
  72. UAV-based reference data for the prediction of fractional cover of standing deadwood from Sentinel time series
  73. AngleCam - Tracking leaf angle distributions through time with image series and deep learning
  74. From spectra to functional plant traits: Transferable multi-trait models from heterogeneous and sparse data
  75. Transfer learning from citizen science photos enables plantspecies identification in UAV imagery
  76. Citizen science observations capture global patterns of plant traits
  77. Citizen science plant observations encode global trait patterns
  78. AngleCam : Predicting the temporal variation of leaf angle distributions from image series with deep learning
  79. Spatially autocorrelated training and validation samples inflate performance assessment of convolutional neural networks
  80. Review on Convolutional Neural Networks (CNN) in vegetation remote sensing
  81. The retrieval of plant functional traits from canopy spectra through RTM-inversions and statistical models are both critically affected by plant phenology
  82. Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks
  83. Convolutional Neural Networks accurately predict cover fractions of plant species and communities in Unmanned Aerial Vehicle imagery
  84. Unmanned aerial vehicle-based mapping of turf-banked solifluction lobe movement and its relation to material, geomorphometric, thermal and vegetation properties
  85. Deep Learning enables to identify plant species in aerial imagery
  86. Advantages of retrieving pigment content [μg/cm2] versus concentration [%] from canopy reflectance
  87. Using aboveground vegetation attributes as proxies for mapping peatland belowground carbon stocks
  88. UAV data as alternative to field sampling to map woody invasive species based on combined Sentinel-1 and Sentinel-2 data
  89. A Landsat-based vegetation trend product of the Tibetan Plateau for the time-period 1990–2018
  90. The functioning of plants determines how they reflect light
  91. Chlorophyll content estimation in an open-canopy conifer forest with Sentinel-2A and hyperspectral imagery in the context of forest decline
  92. Proximal VIS-NIR spectrometry to retrieve substance concentrations in surface waters using partial least squares modelling
  93. PILOT STUDY ON THE RETRIEVAL OF DBH AND DIAMETER DISTRIBUTION OF DECIDUOUS FOREST STANDS USING CAST SHADOWS IN UAV-BASED ORTHOMOSAICS
  94. Differentiating plant functional types using reflectance: which traits make the difference?
  95. Modis-Based Grassland Trends Within and Around the Kekexili Core Protection Zone of the Sanjiangyuan Nature Reserve
  96. Previsual symptoms of Xylella fastidiosa infection revealed in spectral plant-trait alterations
  97. Mapping plant species in mixed grassland communities using close range imaging spectroscopy
  98. Detecting the spread of invasive species in central Chile with a Sentinel-2 time-series
  99. Linking plant strategies and plant traits derived by radiative transfer modelling
  100. Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications?
  101. Linking plant strategies (CSR) and remotely sensed plant traits
  102. Corrigendum to “Mapping forest biomass from space – Fusion of hyperspectralEO1-hyperion data and Tandem-X and WorldView-2 canopy heightmodels” [Int. J. Appl. Earth Obs. Geoinf. Issue no. 35 (2015) 359-367]
  103. Building a hybrid land cover map with crowdsourcing and geographically weighted regression
  104. Mapping forest biomass from space – Fusion of hyperspectral EO1-hyperion data and Tandem-X and WorldView-2 canopy height models
  105. Modeling forest biomass using Very-High-Resolution data—Combining textural, spectral and photogrammetric predictors derived from spaceborne stereo images
  106. Automatic Single Tree Detection in Plantations using UAV-based Photogrammetric Point clouds
  107. Segmentation of Forest to Tree Objects