Google Didn’t Stop Obscuring Imagery of Russian Military Sites Because the Imagery Hadn’t Been Obscured in the First Place

Yesterday, reports that Google Maps had stopped obscuring satellite imagery of sensitive Russian military facilities spread like wildfire across Twitter. Only there was no official announcement from Google saying they’d done so, and while Ukrainian Twitter was seriously running with it, I wanted to see some confirmation from the mapping side. In the event, an update to Ars Technica’s story says that Google hadn’t stopped blurring the imagery—the imagery hadn’t been blurred in the first place. “A Google spokesperson told Ars that the company hasn’t changed anything with regard to blurring out sensitive sites in Russia, so perhaps none of us were looking closely until now.”

Mapping the Russian Invasion of Ukraine: Roundup #2

Content warning: Some of these links contain disturbing images: I’ve marked them with a †.

More on the question of whether theatre maps accurately reflect the ground situation. Nathan Ruser’s maps have been used to argue that Russian forces are controlling roads rather than territory, but Ruser complains that his maps are being misinterpreted: they were never meant to show territorial control, just troop movements. See also this Twitter thread from Jennifer Cafarella, in which she explains the methodology and reasoning behind her team’s maps.

3D models of bombing damage.† Satellite imagery and 3D photogrammetric data are used to create 3D models of bombing damage in Ukraine. [Maps Mania]

A map of attacks on civilian targets with photo and video documentation. [Nataliya Gumenyuk]

Where hot spots are literally hot spots. In a Twitter thread, Sotris Valkaniotis shows how military operations in Ukraine show up in Landsat spectral imagery: weapons fire turns up as hot spots showing “very high temperature in short-wave infrared band.”

A Ukrainian map of alleged Russian casualties† and where they were deployed from. [Michael Weiss]

A map of checkpoint traffic. More than two million Ukrainians have fled the Russian invasion. Overwhelmingly, they’re fleeing westward. This map shows how busy each border checkpoint is: Polish border crossings are extremely congested. [Kyiv Independent]

Meanwhile, Kenneth Field has been working on ways to map Ukraine’s refugees. Here’s his most recent iteration:

Ukraine’s population density. More than 41 million people live in Ukraine. This map from Airwars shows the population density per square kilometre. Which shows how many people in an area are affected by a particular military strike.

Apple says Crimea is Ukrainian. Mashable: “Apple’s Maps and Weather apps now mark Crimea as part of Ukraine when accessed outside of Russia. It appears the company has quietly updated its stance on the territorial dispute.” Apple had marked Crimea as Russian in 2019, which pissed Ukraine off at the time. [TechCrunch]

Finally, this striking bit of art:

The Rise and Fall of Hunga Tonga-Hunga Ha‘apai

A storymap from Esri’s Robert Waterman, based on Maxar satellite imagery, shows the rise and fall of Hunga Tonga and Hunga Ha‘apai from being two separate islands before a 2015 eruption combined them, through its time as an apparently stable but awkwardly compound-named single island until it got blown apart last month.

Previously: Hunga Tonga-Hunga Ha‘apai, Before and After.

Erin Davis’s Average Colours of the World

Map: Average Colors of the World (Erin Davis)
Erin Davis

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]

More on the Western U.S. Wildfires

NASA Earth Observatory

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.

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.

Red and Blue vs. Gray and Green

New York Times

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.

Blank Map Tiles Point to Locations of Xinjiang Detention Centres

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 Maps the Damage from the Beirut Explosion

NASA/JPL-Caltech/Earth Observatory of Singapore/ESA

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.

Himalayan Ice Loss Measured with Cold War Spy Photos

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]

Satellite Mode, Aerial Mode, Bird Mode

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]

Satellite Image Guide for Journalists and Media

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.