Erin Davis has created maps showing the average colour of each country of the world (plus maps showing the average colour of each U.S. state and county). She derived the average colour from Sentinel-2 natural-colour satellite imagery; she appends the process and the code to the end of her post. [My Modern Met]
NASA Earth Observatory has had several stories on the western U.S. wildfires, gathered here. This story summarizes the situation; satellite images of the smoke generated by the fires can be seen here, here and here.
In today's Sunday edition of @washingtonpost pic.twitter.com/qHosujRKrG
— Lauren Tierney (@tierneyl) September 13, 2020
Marena Brinkhurst of Mapbox has a comprehensive list of open data sources relating to the wildfires, smoke, and air quality.
Mark Altaweel at GIS Lounge looks at how GIS is being used to map wildfires, smoke and air pollution.
Previously: California Wildfires, 2020 Edition.
The New York Times uses the colours in aerial images as a proxy for political leanings: rather than red-and-blue electoral maps, the political landscape, Tim Wallace and Krishna Karra argue, is more green and gray.
The pattern we observe here is consistent with the urban-rural divide we’re accustomed to seeing on traditional maps of election results. What spans the divide—the suburbs represented by transition colors—can be crucial to winning elections. […] At each extreme of the political spectrum, the most Democratic areas tend to be heavily developed, while the most Republican areas are a more varied mix: not only suburbs, but farms and forests, as well as lands dominated by rock, sand or clay.
This is a generalization, to be sure, but so are most political maps, and the notion that urban areas tend to vote Democratic while rural areas tend to vote Republican isn’t what I’d call a revelation. Still.
As part of their investigation into China’s practice of detaining Uighur and other Muslim minorities in Xinjiang, Buzzfeed News journalists compared blanked-out areas in Baidu Maps with uncensored imagery from Google Earth and satellite data providers, and, after sorting through some 50,000 possible locations using custom web tools, built a database of some “428 locations in Xinjiang bearing the hallmarks of prisons and detention centers.” This article explains the methodology.
Blurring or removing map data to prevent people from seeing something important or sensitive is a pretty loud signal that there’s something important or sensitive to see there. Some five million Baidu Maps tiles were masked in Xinjiang alone—there’s a lot the Chinese government considers sensitive—which made the unmasking considerably harder. But not impossible.
NASA has released a map of the likely extent of damage from Tuesday’s explosion in Beirut.
Synthetic aperture radar data from space shows ground surface changes from before and after a major event like an earthquake. In this case, it is being used to show the devastating result of an explosion.
On the map, dark red pixels—like those present at and around the Port of Beirut—represent the most severe damage. Areas in orange are moderately damaged and areas in yellow are likely to have sustained somewhat less damage. Each colored pixel represents an area of 30 meters (33 yards).
The map is based on data from the European Space Agency’s Copernicus Sentinel program, and was analyzed by NASA’s Advanced Rapid Imaging and Analysis team and the Earth Observatory of Singapore.
CNN has satellite images, taken both before and after the explosion, showing the extent of the damage caused by the explosion in Beirut last Tuesday. [Boing Boing]
A nice, accessible (if overboosterish) history and overview of Google Earth—which despite its deprecation on the desktop is still a thing—from Sarvish Mathi at OneZero. [GIS Lounge] Related: this Google blog post on their imagery, how they get it and how it’s processed.
Satellite imagery only goes back so far. To measure the rate of ice loss across the Himalayan glaciers, researchers turned to recently declassified spy satellite photos from 1975. The photos were used to create a digital elevation model (above) which was compared with more recent data. They concluded that the rate of ice loss was accelerating: it was twice as much from 2000 to 2016 than it was from 1975 to 2000. Columbia University, Science News. [Geography Realm]
In The Atlantic’s May 2019 issue, Frank Portnoy looks at an unexpected use of satellite imagery: stock analysts counting cars in retail parking lots, among other things, to predict a company’s revenues.
Here’s a silly Google Maps origin story about how “Satellite” was almost named “Bird Mode” pic.twitter.com/wj7CRJUEyx
— Bret Taylor (@btaylor) February 23, 2019
A lot of what we refer to on online maps as “satellite imagery” actually isn’t: the high-resolution stuff is usually taken from airplanes. This can be a point of confusion for some—and, according to this Twitter thread from Google Maps co-creator Bret Taylor, also a point of contention for the Google Maps team before it launched. Some engineers felt that calling the layer “Satellite” was factually incorrect—because of that aerial imagery—and therefore shouldn’t be used; others argued for “Satellite” based on label size and usability studies. It nearly got called “Bird Mode” as a compromise. [Boing Boing]
Pierre Markuse’s Satellite Image Guide for Journalists and Media:
So you would like to use a satellite image in your article and you would like to explain it to your viewers? Here is a short guide covering some of the most frequently asked questions and giving some general explanations on satellite images. It by no means covers all aspects, as there are far too many types of satellite images, but should give you a good start to find out more on your own and maybe motivate you to create your own images, which has become quite easy and quick even with no prior knowledge of it.
Complete with examples of imagery, examples of how to use it properly, and links to resources.
The San Francisco Chronicle’s 2018 California Fire Tracker is an interactive map of ongoing and contained wildfires—notably, at this moment, the Camp and Woolsey fires. It includes fire perimeter and air quality data. (Note: it’s glitchy on desktop Safari.)
Two Esri maps: a general wildfire map and a map of smoke from wildfires [Maps Mania]. Add to that a map of field damage reports in the area hit by the Camp Fire [Maps Mania].
The Jet Propulsion Laboratory has produced a map of the damage from the Camp Fire based on satellite radar images. NASA Earth Observatory has maps and animations showing the impact of the Camp Fire on air quality and satellite images of the Woolsey Fire burn scar.
The New York Times has a map tracking air quality in California. Smoke from the fires has reached the east coast: an outcome predicted by atmospheric models (see above map).
This interactive map from NBC News that superimposes the Camp Fire on any location to help people outside California get a sense of how big these fires are. [Maps Mania]
NASA Earth Observatory published a Landsat 8 image, dated 8 November, of the massive Camp Fire in northern California. Meanwhile, Maps Mania links to several California wildfire-related maps and resources.
Last week a magnitude-7.5 earthquake struck the Indonesian island of Sulawesi, triggering a tsunami that struck the city of Palu with far more force than expected. The New York Times has multiple maps and aerial images of the damaged areas; NASA Earth Observatory has before-and-after Landsat imagery.
Smoke from the British Columbia wildfires (previously) has blanketed the Canadian prairie provinces and can be seen from space, CBC News reports. The above image was taken by the Suomi NPP satellite on 15 August.
