The Thermal InfraRed Sensor (TIRS) is a new instrument carried onboard the Landsat 8 satellite that is dedicated to capturing temperature-specific information.  Using radiation information from the two electromagnetic spectral bands covered by this sensor, it is possible to estimate the temperature at the Earth’s surface (albeit at a 100m resolution, compared to the 30m resolution of the other instrument, the Operational Land Imager).

I used data from the TIRS to estimate the surface temperature in the city-state of Delhi, India as of the 29th of May, 2013.  The relevant tarball file containing the data was downloaded using the United States’ Geological Survey’s (USGS) EarthExplorer tool; the area of interest was encompassed by [scene identifier: path 146 row 040] in the WRS-2 scheme. I think I’ll leave the specific explanations describing WRS-2, path/row values and the other miscellaneous small data-management operations for a later post. For now, I’ll let it be understood that these are important things to know when in the process of actually obtaining this data. When the tarball is unpacked fully, the bands from the TIRS instrument are bands 10 and 11;  the relevant .tif files are [“identifier”_B10.tif] and [“identifier”_B11.tif], and these were clipped to the administrative boundary of Delhi. There’s also a text file containing metadata: [“identifier”_MTL.txt] is essential for the math we’re going to do on these two bands.

 

Delhi as seen by Landsat 8 Band 10 (TIRS)
Delhi as seen by Landsat 8 Band 10 (TIRS)

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I planned to highlight ten maps each in month in this *Monthly Maps* series. The month of July, however, saw quite a few fabulous maps, and left me struggling to choose between them. Perhaps I will break the limit of ten maps a bit for this month.

July began with the awesome urban tweet topography maps by data visualisation scientist Nicolas Belmonte. These maps takes all the geo-tagged tweets from five cities — Buenos Aires, Istanbul, Moscow, New York, and San Francisco — and generate a three dimensional topography of these tweets with a higher contour line indicating a greater number of tweets from the place concerned. The image below is for Istanbul. Do visit the maps page to explore other cities and various thematic terrain shading, and the entire code is on GitHub too!

3d twitter topography

And Stamen came out with the *instgram for maps* – map stack. It lets you create a map by combining various basemap layers (including satellite imagery, terrain, road networks etc.), visually crafting the layers using detailed controls (e.g., masks, opacity and brightness), and to convert the final map into an image for sharing.

stamen - map stack

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