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A.J. Rohn

A.J. is a recent graduate of the Geography and Environmental Studies programs at the University of Wisconsin-Madison with a passion for writing and interests in areas ranging from ecology to geosophy to geopolitics. He enjoys the geography of Wisconsin, be it the north woods or city life in Madison. He loves to read research papers in geography, books by scholars like Yi-Fu Tuan and Bill Cronon (both at UW-Madison), as well as classic fiction writers like Thomas Pynchon and Fyodor Dostoevsky. He is very much inspired by the work of all the people he encountered in Madison’s geography department, so expect a wide range of topics when reading his articles here and on GeoLounge.com.
Deforestation within Tambopata National Reserve between July (left panel) and September (right panel) 2016. Red circles highlight areas of major deforestation. Source: MAAP.

Using Remote Sensing to Understand the Correlation Between Deforestation and Forest Fires

by A.J. Rohn

MAAP has used remote sensing to discover a correlation between deforestation and forest fires in Tampbopata, Peru.

Categories Spatial Analysis Tags deforestation, remote sensing
Screenshot of the mapping application from Disappearing West.

New Project Maps the Loss of Natural Spaces in American West

by A.J. Rohn

At DisappearingWest.org, you can actively monitor the loss of natural land as the American West continues to be developed with maps, statistics, and explanations for this trend.

Categories Spatial Analysis Tags GIS data download, natural land loss
The examples on the left are the query photos. In response, PlaNet will output a probability distribution on the map. In these three examples, the Eiffel Tower (a) is confidently assigned to Paris, the model believes that the fjord photo (b) could have been taken in either New Zealand or Norway. For the beach photo (c), PlaNet assigns the highest probability to southern California (correct), but some probability mass is also assigned to places with similar beaches, like Mexico and the Mediterranean. The authors use a model with a much lower spatial resolution than the full model for visualization purposes. Source: Weyand, Kostrikov, & Philbin, 2016.

Google’s PlaNet: Geolocating Photos Using Artificial Intelligence

by A.J. Rohn

Google and researchers at the Rheinisch­Westfälische Technische Hochschule Aachen University have developed an artificial intelligence system capable of identifying locations more consistently accurately than a human is able to do.

Categories GIS Learning Tags artificial intelligence, geolocation, PlaNet

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