Difference between revisions of "Global Sentinel-2 10m Canopy Height ETH"

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== Introduction ==
 
== Introduction ==
The "Global Sentinel-2 10m Canopy Height (ETH Zurich)" is a high-resolution forest canopy height dataset with full global data coverage and the data being representative for the year 2020. It was created by a team of ETH researchers using an artificial neural network (by fusing the two data-sources of GEDI and Sentinel 2 using a probabilistic deep learning model). Further documentation is available from an arXiv paper: Nico Lang, Walter Jetz, Konrad Schindler, and Jan Dirk Wegner. "A high-resolution canopy height model of the Earth" ([https://arxiv.org/abs/2204.08322 arXiv:2204.08322 (2022)]), see more below.
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The "Global Sentinel-2 10m Canopy Height (ETH Zurich)" is a high-resolution forest canopy height dataset with full global data coverage and the data being representative for the year 2020. It was created by a team of ETH researchers using an artificial neural network (by fusing the two data-sources of [https://gedi.umd.edu/instrument/instrument-overview/ GEDI] and [https://sentinel.esa.int/web/sentinel/missions/sentinel-2 Sentinel 2] using a probabilistic deep learning model). Further documentation is available from an arXiv paper: Nico Lang, Walter Jetz, Konrad Schindler, and Jan Dirk Wegner. "A high-resolution canopy height model of the Earth" ([https://arxiv.org/abs/2204.08322 arXiv:2204.08322 (2022)]), see more below.
  
 
== Data Applicability and Availability within windPRO ==
 
== Data Applicability and Availability within windPRO ==

Revision as of 15:59, 8 August 2022

Note: This dataset is being integrated in windPRO. Expected release is mid august 2022.
Global Forest Map GLAD – Site South-East of Leipzig, Germany.
Coverage for GLAD – Latitudes S52-N52.
GEDI: Canopy height and profile metrics derived from waveform data. Image Credit: University of Maryland - GEDI Experiment.
GEDI’s 80 cm telescope. Image Credit: University of Maryland - GEDI Experiment.

Introduction

The "Global Sentinel-2 10m Canopy Height (ETH Zurich)" is a high-resolution forest canopy height dataset with full global data coverage and the data being representative for the year 2020. It was created by a team of ETH researchers using an artificial neural network (by fusing the two data-sources of GEDI and Sentinel 2 using a probabilistic deep learning model). Further documentation is available from an arXiv paper: Nico Lang, Walter Jetz, Konrad Schindler, and Jan Dirk Wegner. "A high-resolution canopy height model of the Earth" (arXiv:2204.08322 (2022)), see more below.

Data Applicability and Availability within windPRO

The forest height data are used as input for the dedicated sub-models in windPRO which includes the forest impact on the wind flow. These sub-models are the Displacement Height Calculator and the Objective Roughness Approach (ORA) tool; both models are available from windPRO 3.2+. The forest data is accessed from the online-services from the ‘Elevation Grid Object’ with data-type set to ‘Heights above terrain (a.g.l) for elements’. The data can be accessed from the online-services in the 'Elevation Grid Object' in the following way.

  1. Open the 'Elevation Grid Object'
  2. Set ‘Data type’ to ‘Digital Object Model - representation of the object heights (e.g. forest height)
  3. Click ‘Add Layer from Online Data‘

Technical Details

  • Format: Geotiff
  • Pixel values: Canopy top-height 2020 (m)
    (RH98: the relative height where 98% of the energy has been returned, derived from GEDI L1B waveforms)
  • Spatial resolution: 0.0000833 degree (approximately 10 m)
  • Geographical coverage: Full coverage of the globe
  • Coordinate system: WGS84 geographic coordinates (in original data)
  • Pixel values:
    • 0-254: tree height in meters
    • 255: no data value (not included in windPRO dataset)
      (the 255 value is used to mask-out built-up areas, snow, ice and permanent water bodies)
  • Accuracy (see also Lang et al):
    • RMSE over all validation samples: 6.0m
    • Bias over all validation samples: 1.3m

Usage Notes

  1. This mapping has focused on a correct mapping of tall trees.
  2. Low canopy heights are slightly over-estimated

License and Acknowledgement

The map has been released according to the Createive Commons by Attribution 4.0 License: The ETH Global Canopy Height 2020 product is provided free of charge, without restriction of use. Publications, models and data products that make use of these datasets must include proper acknowledgement, including citing the datasets and the journal article as in the following citation:

Source:
Dataset: A high-resolution canopy height model of the Earth (ETH Global Canopy Height 2020).
Authors: Nico Lang, Walter Jetz, Konrad Schindler and Jan Dirk Wegner.
Documentation: Available at arXiv: 2204.08322

External Links and References

  1. Nico Lang, Walter Jetz, Konrad Schindler, and Jan Dirk Wegner. "A high-resolution canopy height model of the Earth." (arXiv:2204.08322 (2022)) - here-html or here-pdf
  2. ETH Zurich Newsletter (Neural network can read tree heights from satellite images) - here
  3. GEDI instrument overview - here
  4. Global Sentinel-2 10m Canopy Height (ETH Zurich), 2020 - data home page - here