Category: Data visualization/Infographics

Colour me better: fixing figures for colour blindness

Read the full story in Nature.

Images can be made more accessible by choosing hues, shapes and textures carefully.

Publishers unite to tackle doctored images in research papers

Read the full story in Nature..

Eight major publishers have issued joint guidelines for how journal editors can spot and deal with suspicious images or data.

Public perception of scientific results distorted by colorful graphics

Read the full story from the Albert Ludwigs University of Freiburg.

Colorful maps and figures with rainbow-colored gradients from scientific papers often serve as eye-catchers in journals and are readily shared in social media. Hydrologist Dr. Michael Stölzle from the Institute of Earth and Environmental Sciences at the University of Freiburg and Dr. Lina Stein from the University of Bristol in England have investigated the frequency and properties of so-called “rainbow color maps.” In their study, the researchers note that using a rainbow color map in scientific visualizations distorts the data representation. In addition, people with color vision deficiencies cannot interpret such images correctly. Stölzle and Stein published their findings in the journal Hydrology and Earth System Sciences.

New Wolfram U course explores data visualization

Read the full story from Wolfram.

After a few months of brainstorming ideas, developing notebooks and scripts and refining videos through several rounds of editing and refilming, we are pleased to announce that the Visual Explorations in Data Science massive open online course (MOOC) is now available.

The two guiding principles of this course are visualization and an example-driven approach. We employ a hands-on methodology for teaching data science with examples that slowly introduce various technical features, all of which are supplemented with an emphasis on visualization. The course consists of a dozen case studies spanning geography to engineering and analyzing flag similarity to periodic trends.

Track wildfires in the West

View the map from the New York Times.

The map includes active and recent fires reported by the Wildland Fire Interagency Geospatial Services group. The locations of the fires on the map are approximate, derived from data reported by the NASA FIRMS satellite-based fire detection system, which makes observations multiple times a day. Areas marked in red indicate where active burning was detected within 24 hours of the most recent detections reflected on the map. The exact boundary of a fire may differ from the extent shown on the map by 500 meters or more.

Air quality data is derived from PurpleAir sensors. Colored squares show the average levels of particulate matter in the air — PM2.5, or particles that are 2.5 microns are smaller in diameter — where sensor data is available within a 10-mile radius of each square’s position. Readings have been adjusted to account for the properties of wood smoke. The quality levels are based on the Air Quality Index developed by the U.S. Environmental Protection Agency.

Population counts are rounded estimates. Totals are calculated using Global Human Settlements estimates from 2015 from the European Commission’s Joint Research Center.

This map lets you fly along the path of a drop of water from any place in the U.S.

Read the full story in Fast Company.

Click on any spot or enter an address, and it will show where the water is likely to flow. Good for both learning how pollution and plastic spreads, but also for an aerial visual ride of the country’s waterways.

Map data is shockingly easy to fake, from ‘Pokémon Go’ to satellite images

Read the full story in Fast Company.

Zhao and colleagues from Oregon State University and Binghamton University began to look into satellite imagery, a major source of geospatial data used in applications ranging from climate observation to global shipping. In a recent paper, they explore the potential—and, as they show, the very real threat—of people using artificial intelligence to create convincing but fabricated satellite imagery. Like AI systems that have been created to generate realistic faces or malicious pornographers who’ve used cruder systems to make fake explicit videos using the likenesses of celebrities, Zhao and his colleagues have shown that deepfake satellite imagery can also be made.

Deepfake satellite imagery poses a not-so-distant threat, warn geographers

Read the full story at The Verge.

When we think of deepfakes, we tend to imagine AI-generated people. This might be lighthearted, like a deepfake Tom Cruise, or malicious, like nonconsensual pornography. What we don’t imagine is deepfake geography: AI-generated images of cityscapes and countryside. But that’s exactly what some researchers are worried about.

Specifically, geographers are concerned about the spread of fake, AI-generated satellite imagery. Such pictures could mislead in a variety of ways. They could be used to create hoaxes about wildfires or floods, or to discredit stories based on real satellite imagery. (Think about reports on China’s Uyghur detention camps that gained credence from satellite evidence. As geographic deepfakes become widespread, the Chinese government can claim those images are fake, too.) Deepfake geography might even be a national security issue, as geopolitical adversaries use fake satellite imagery to mislead foes.

The new U.S. Climate Normals are here. What do they tell us about climate change?

Annual U.S. temperature compared to the 20th-century average for each U.S. Climate Normals period from 1901-1930 (upper left) to 1991-2020 (lower right).
Annual U.S. temperature compared to the 20th-century average for each U.S. Climate Normals period from 1901-1930 (upper left) to 1991-2020 (lower right). (NOAA NCEI)

Read the full story from NOAA. See also the story in the Washington Post.

Every 10 years, NOAA releases an analysis of U.S. weather of the past three decades that calculates average values for temperature, rainfall and other conditions.  

That time has come again.

Known as the U.S. Climate Normals, these 30-year averages — now spanning 1991-2020 — represent the new “normals” of our changing climate. They are calculated using climate observations collected at local weather stations across the country and are corrected for bad or missing values and any changes to the weather station over time before becoming part of the climate record.

Simply stated: The Normals are the basis for judging how daily, monthly and annual climate conditions compare to what’s normal for a specific location in today’s climate. 

New IU tool maps green infrastructure in Hoosier communities

Read the full story in the Indiana Environment Reporter.

Indiana Green City Mapper allows residents and city planners to see maps of urban green infrastructure and other climate change-related data to maximize resilience benefits.

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