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.
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.
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.
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.
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]
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]
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.)
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.
Landsat observations have charted the erosion of the banks of the ever-changing Padma River, a major distributary of the Ganges in Bangladesh. This is vividly shown in this animation produced by NASA Earth Observatory, which “shows 14 false-color images of the Padma river between 1988 and 2018 taken by the Landsat 5 and 8 satellites. All of the images include a combination of shortwave infrared, near infrared, and visible light to highlight differences between land and water.” More on the erosion of the Padma River here.