Remote Sensing: Difference between revisions

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Machine learning can be applied to remote sensing data to infer climate-relevant information such as global greenhouse gas emissions, building footprints, solar panel locations, or occurrences of deforestation.<ref>{{Cite web|title=Tackling climate change in the EU|url=http://dx.doi.org/10.1163/9789004322714_cclc_2017-0189-005|website=Climate Change and Law Collection}}</ref> Some general-purpose remote sensing datasets are listed below.
TODO starting page for remote sensing
 
   
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== Satellite imagery datasets ==
* '''High-resolution RGB satellite images (for visual predictions)''':
 
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** Public
 
 
=== '''High-resolution RGB satellite images (for visual predictions)''' ===
*** United States Geological Survey
 
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*** Copernicus dataset (Sentinel satellites)
 
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==== Public datasets ====
*** NASA Worldview
 
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** Public, but permission needed for research use
 
 
* [https://earthexplorer.usgs.gov/ United States Geological Survey]
*** Google Earth
 
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* [https://www.copernicus.eu/en/access-data Copernicus (Sentinel satellites)]
** Commercial
 
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* [https://worldview.earthdata.nasa.gov/ NASA Worldview]
*** DigitalGlobe (up to 31cm resolution)
 
 
* [https://www.google.com/earth/ Google Earth] (permission needed for research use)
*** Planet (up to 72cm resolution)
 
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* '''Multispectral satellite images (5-13 visible and infrared bands)''':
 
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'''Commercial datasets'''
** Public
 
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*** Copernicus dataset (Sentinel satellites)
 
 
*[https://www.digitalglobe.com/ DigitalGlobe] (up to 31cm resolution)
*** BigEarthNet dataset (Sentinel satellites)
 
 
*[https://www.planet.com/ Planet] (up to 72cm resolution)
** Commercial
 
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*** Digital Globe
 
 
=== '''Multispectral satellite images (5-13 visible and infrared bands)''' ===
*** Planet
 
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* '''Hyperspectral satellite images (up to a few hundred visible and infrared bands)''':
 
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==== Public datasets ====
** See Table 1 of this survey of hyperspectral earth observation satellites for comparisons between sources.
 
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** Public
 
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* [https://www.copernicus.eu/en/access-data Copernicus (Sentinel satellites)]
*** United States Geological Survey (Hyperion data)
 
 
* [http://bigearth.net/ BigEarthNet (Sentinel satellites)]
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==== Commercial datasets ====
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* [https://www.digitalglobe.com/ Digital Globe]
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* [https://www.planet.com/ Planet]
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=== '''Hyperspectral satellite images (up to a few hundred visible and infrared bands)''': ===
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==== Public datasets ====
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* [https://earthexplorer.usgs.gov/ United States Geological Survey (Hyperion data)]
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==== See also ====
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* Table 1 of the review "Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context"<ref>{{Cite journal|last=Transon|first=Julie|last2=d’Andrimont|first2=Raphaël|last3=Maugnard|first3=Alexandre|last4=Defourny|first4=Pierre|date=2018-01-23|title=Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context|url=http://dx.doi.org/10.3390/rs10020157|journal=Remote Sensing|volume=10|issue=3|pages=157|doi=10.3390/rs10020157|issn=2072-4292}}</ref> for comparisons between sources.
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== Street view datasets ==
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* [https://www.openstreetmap.org/ OpenStreetMap]
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== References ==

Revision as of 04:12, 28 August 2020

Machine learning can be applied to remote sensing data to infer climate-relevant information such as global greenhouse gas emissions, building footprints, solar panel locations, or occurrences of deforestation.[1] Some general-purpose remote sensing datasets are listed below.

Satellite imagery datasets

High-resolution RGB satellite images (for visual predictions)

Public datasets

Commercial datasets

Multispectral satellite images (5-13 visible and infrared bands)

Public datasets

Commercial datasets

Hyperspectral satellite images (up to a few hundred visible and infrared bands):

Public datasets

See also

  • Table 1 of the review "Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context"[2] for comparisons between sources.

Street view datasets

References

  1. "Tackling climate change in the EU". Climate Change and Law Collection.
  2. Transon, Julie; d’Andrimont, Raphaël; Maugnard, Alexandre; Defourny, Pierre (2018-01-23). "Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context". Remote Sensing. 10 (3): 157. doi:10.3390/rs10020157. ISSN 2072-4292.