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>
Machine learning can be applied to remote sensing data to infer climate-relevant information. Some examples include:<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>

* Mapping power grids and solar panel locations.
* Mapping building footprints.
* Pinpointing occurrences of deforestation.
* [[Greenhouse Gas Emissions Detection|Creating an inventory of global greenhouse gas emissions]].
==Background Readings==
==Background Readings==
==Online Courses and Course Materials==
==Online Courses and Course Materials==