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.
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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>
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==Background Readings==
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==Online Courses and Course Materials==
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==Community==
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==Libraries and Tools==
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== Data ==
   
== Satellite imagery datasets ==
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=== Satellite imagery datasets ===
   
=== '''High-resolution RGB satellite images (for visual predictions)''' ===
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===='''High-resolution RGB satellite images (for visual predictions)'''====
 
Public datasets
 
==== Public datasets ====
 
   
 
* [https://earthexplorer.usgs.gov/ United States Geological Survey]
 
* [https://earthexplorer.usgs.gov/ United States Geological Survey]
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* [https://www.google.com/earth/ Google Earth] (permission needed for research use)
 
* [https://www.google.com/earth/ Google Earth] (permission needed for research use)
   
'''Commercial datasets'''
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Commercial datasets
   
 
*[https://www.digitalglobe.com/ DigitalGlobe] (up to 31cm resolution)
 
*[https://www.digitalglobe.com/ DigitalGlobe] (up to 31cm resolution)
 
*[https://www.planet.com/ Planet] (up to 72cm resolution)
 
*[https://www.planet.com/ Planet] (up to 72cm resolution)
   
=== '''Multispectral satellite images (5-13 visible and infrared bands)''' ===
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===='''Multispectral satellite images (5-13 visible and infrared bands)''' ====
 
Public datasets
 
==== Public datasets ====
 
   
 
* [https://www.copernicus.eu/en/access-data Copernicus (Sentinel satellites)]
 
* [https://www.copernicus.eu/en/access-data Copernicus (Sentinel satellites)]
 
* [http://bigearth.net/ BigEarthNet (Sentinel satellites)]
 
* [http://bigearth.net/ BigEarthNet (Sentinel satellites)]
   
==== Commercial datasets ====
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Commercial datasets
   
 
* [https://www.digitalglobe.com/ Digital Globe]
 
* [https://www.digitalglobe.com/ Digital Globe]
 
* [https://www.planet.com/ Planet]
 
* [https://www.planet.com/ Planet]
   
=== '''Hyperspectral satellite images (up to a few hundred visible and infrared bands)''': ===
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===='''Hyperspectral satellite images (up to a few hundred visible and infrared bands)''': ====
 
Public datasets
 
==== Public datasets ====
 
   
 
* [https://earthexplorer.usgs.gov/ United States Geological Survey (Hyperion data)]
 
* [https://earthexplorer.usgs.gov/ United States Geological Survey (Hyperion data)]
   
==== See also ====
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See also
   
 
* 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.
 
* 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.
   
== Street view datasets ==
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=== Street view datasets ===
   
 
* [https://www.openstreetmap.org/ OpenStreetMap]
 
* [https://www.openstreetmap.org/ OpenStreetMap]

Revision as of 19:54, 31 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]

Background Readings

Online Courses and Course Materials

Community

Libraries and Tools

Data

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.