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

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[[Category: Online Data]][[Category: Forest Maps]][[File:GLAD_Leipzig_1200x627px.png|right|thumb|450px|Global Forest Map GLAD – Site South-East of Leipzig, Germany.]]
[[Category: Online Data]][[Category: Forest Maps]][[File:ETHZ_ForestHeights_Tobago.png|right|thumb|450px|Global Forest Map ETH in windPRO: Sample location at the central part of the Caribbean Island of Tobago.]]
[[File:GLAD_Coverage.png|right|thumb|450px|Coverage for GLAD Latitudes S52-N52.]][[File:GEDI_WaveForm.jpg|right|thumb|450px|GEDI: Canopy height and profile metrics derived from waveform data. Image Credit: University of Maryland - GEDI Experiment.]][[File:GEDI_Instrument.png|right|thumb|450px|GEDI’s 80 cm telescope. Image Credit: University of Maryland - GEDI Experiment.]]
[[Image:windpro_GlobalForestHeights_WestCoastOfHainanChina.png|right|thumb|450px|Global Forest Map ETH in windPRO: Sample location at the west coast of Hainan, China.]]
[[File:CoverageGlobalForestETH.png|right|thumb|450px|Full Global Coverage for Global Sentinel-2 10m Canopy Height ETH A total of 2651 tiles each 3x3 degrees in size.]][[File:GEDI_WaveForm.jpg|right|thumb|450px|GEDI: Canopy height and profile metrics derived from waveform data. Image Credit: University of Maryland - GEDI Experiment.]][[File:GEDI_Instrument.png|right|thumb|450px|GEDI’s 80 cm telescope. Image Credit: University of Maryland - GEDI Experiment.]]


== Introduction ==
== Introduction ==
The "Global Sentinel-2 10m Canopy Height (ETH Zurich)" is a high-resolution forest canopy height dataset with full global data coverage. The data is representative for the year 2020 and it was created by a team of ETH researchers by 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. .
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 ==
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* ''Pixel values:''
* ''Pixel values:''
** 0-254: tree height in meters
** 0-254: tree height in meters
** 255: no data value (not included in windPRO dataset)
** 255: no data value (not included in windPRO dataset)<br>(the 255 value is used to mask-out built-up areas, snow, ice and permanent water bodies)
** The 255 value is used to mask-out built-up areas, snow, ice and permanent water bodies
* ''Accuracy (see also Lang et al)'':  
* ''Accuracy (see Lang et al)'':  
** RMSE over all validation samples: 6.0m
** RMSE over all validation samples: 6.0m
** Bias over all validation samples: 1.3m
** Bias over all validation samples: 1.3m
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==  License and Acknowledgement ==
==  License and Acknowledgement ==
The map has been released according to the Createive Commons by Attribution 4.0 license:  
The map has been released according to the [https://creativecommons.org/licenses/by/4.0/ Creative Commons by Attribution 4.0 License]:  
The Global Land Analysis and Discovery Laboratory (GLAD) at the Department of Geographical Sciences at the University of Maryland has made the data available free of charge. We recommend using the following attribution when using the data:  
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:
<pre>
<pre>
Source:
Source:
Global forest height data from the Global Land Analysis and Discovery Laboratory (GLAD).
Dataset: A high-resolution canopy height model of the Earth (ETH Global Canopy Height 2020) by authors: Nico Lang, Walter Jetz, Konrad Schindler and Jan Dirk Wegner.
GLAD is at the Department of Geographical Sciences at the University of Maryland, USA.
Documentation: Available at arXiv: 2204.08322
Processing and distribution through EMD and windPRO.  
</pre>
</pre>


== External Links and References ==
== External Links and References ==
# Nico Lang, Walter Jetz, Konrad Schindler, and Jan Dirk Wegner. "A high-resolution canopy height model of the Earth." (arXiv:2204.08322 (2022)) - [https://arxiv.org/abs/2204.08322 here]
# Nico Lang, Walter Jetz, Konrad Schindler, and Jan Dirk Wegner. "A high-resolution canopy height model of the Earth." (arXiv:2204.08322 (2022)) - [https://arxiv.org/abs/2204.08322 here-html] or [https://arxiv.org/pdf/2204.08322.pdf here-pdf]
# ETH Zurich Newsletter - [https://ethz.ch/en/news-and-events/eth-news/news/2022/04/neural-network-can-read-tree-heights-from-satellite-images.html here]
# ETH Zurich Newsletter (Neural network can read tree heights from satellite images) - [https://ethz.ch/en/news-and-events/eth-news/news/2022/04/neural-network-can-read-tree-heights-from-satellite-images.html here]
# GEDI instrument overview - [https://gedi.umd.edu/instrument/instrument-overview/ here]
# GEDI instrument overview - [https://gedi.umd.edu/instrument/instrument-overview/ here]
# Global Sentinel-2 10m Canopy Height (ETH Zurich), 2020 - data home page - [https://samapriya.github.io/awesome-gee-community-datasets/projects/canopy/ here]
# Global Sentinel-2 10m Canopy Height (ETH Zurich), 2020 - data home page - [https://langnico.github.io/globalcanopyheight/ here]

Latest revision as of 11:59, 9 August 2022

Global Forest Map ETH in windPRO: Sample location at the central part of the Caribbean Island of Tobago.
Global Forest Map ETH in windPRO: Sample location at the west coast of Hainan, China.
Full Global Coverage for Global Sentinel-2 10m Canopy Height ETH – A total of 2651 tiles each 3x3 degrees in size.
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 Creative 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) by 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