Some nice pictures/visualizations of how deep learning works.
In this composite image you can see parts of New York City and New Jersey, imaged by the Operational Land Imager (OLI) with a thermal infrared overlay taken by the Thermal InfraRed Sensor (TIRS) aboard Landsat 8. The images were taken July 25th, 2015 at 3:39pm GMT.
When I processed this image I was surprised about the distribution of hot spots. I expected Central Park to be as cool as it is because dense vegetation prevents urban heat islands (https://goo.gl/X14sgO). But although the rest of Manhattan has a somewhat sparse vegetation the surface temperatures are cool in comparison to other areas. At first I thought I made a mistake yet when comparing this image to the infrared image in the article linked below they show a similar distribution of hot spots. Take a look here and read more about urban heat islands:
The area on Google Maps:
More on the features in the image:
For those interested, here the technical data for this image. The underlying image is a panchromatic OLI Band 8 image, the overlay is a combination of Thermal InfraRed Sensor (TIRS, https://goo.gl/bAzPDO) Bands 10 and 11 images. The resulting colors represent the surface temperature from purple-blue (cool) to yellow-red (warm). Image scale is 15 meters/pixel. Image resolution for the underlying image is 15 meters, the thermal infrared data has a resolution of 100 meters.
More images of Earth from Space:
More on Landsat 8:
Image credit: Landsat 8 data courtesy of U.S. Geological Survey / Processed by
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#science #newyork #newyorkcity #manhattan #ny #nyc #landsat #landsat8 #earth #space #satelliteimages #infrared #thermalinfrared #urbanheatislands
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