Satellites: environmental monitors
Back when founder John Amos started SkyTruth in 2000, only a handful of civilian earth-observation satellites were orbiting the planet. Today, there are dozens of companies and governments operating fleets of satellites that beam down thousands of images every day.
Our new challenge is sifting through these vast quantities of data and imagery using the latest technology, and analyzing them in a way that reveals otherwise hidden environmental damage. We then make these images, data, and maps available to the public for free, enabling citizens, researchers, journalists and others to hold industries and governments accountable for their actions.
Satellite imagery has revolutionized the whole way we analyze things; it’s transformed the way the Earth is pictured.
SkyTruth uses remote sensing, satellite imagery and digital mapping to alert citizens, journalists, researchers, policymakers and conservation groups to the harmful impacts of human activities on the environment.
Remote sensing is a broad term that refers to studying the Earth without being in physical contact with it. At SkyTruth, we specialize in analyzing images captured by satellites and aircraft, and processing data picked up by the satellite’s sensors. Imagery provides a unique perspective on environmental issues, allowing us to display the vastness of certain impacts (such as mines), changes on the landscape over time (such as the growth of oil and gas fields), or other realities that simply can’t be perceived from the ground (such as bilge dumping). Satellites have global coverage, which allows us to observe events around the world without ever leaving home. Aerial photography is another form of remote sensing that gives us a bird’s-eye view of environmental impacts with detail much greater than publicly available satellite imagery. For example, we use NAIP (National Agricultural Imagery Program) run by the U.S. Department of Agriculture to explore fracking and map other impacts.
When it comes to remote sensing, the hardware tends to steal the show. So here is more detail about the instruments we use. We get much of our data from the following major satellites:
Landsat - 8
This is the eighth satellite in the Landsat program, which is the longest-running program that acquires satellite imagery of Earth. This satellite collects visible and infrared images of the Earth’s surface at 30 meter resolution, adding to the nearly 5 million other Landsat satellite images available to the public from previous Landsat satellites. We typically access Landsat imagery through Google Earth Engine.
SUOMI NATIONAL POLAR-ORBITING PARTNERSHIP
This is a weather satellite with five different sensors that orbits the Earth about 14 times per day. The sensor we rely on most frequently is the Visible Infrared Imaging Radiometer Suite, or “VIIRS,” that collects infrared and visible light data to observe weather, climate, oceans, nightlight, wildfires, ice, and changes in vegetation. We access this dataset through Google Earth Engine.
TERRA AND AQUA
The Terra and Aqua satellites collect low-resolution images of every spot on the planet, twice a day. Each satellite is equipped with a Moderate Resolution Imaging Spectroradiometer – or “MODIS” for short – designed to measure large-scale global dynamics of the Earth’s oceans, landscapes, and atmosphere. We access this dataset through Google Earth Engine.
SENTINEL-1A and 1B
This pair of satellites is operated by the European Space Agency. They carry a C-band synthetic-aperture radar instrument which can penetrate clouds and collect data in any weather, day or night. We access this dataset through Google Earth Engine.
SENTINEL-2A and 2B
This is another pair of satellites operated by the European Space Agency. They collect high resolution optical imagery (between 10 meters and 60 meters detail) over land and coastal waters every 5 days. We access this dataset through Google Earth Engine.
This is a commercial Earth observation satellite owned by the company DigitalGlobe. It was launched in 2014 as DigitalGlobe’s sixth satellite in orbit, joining several other satellites whose imagery we’ve also used: Ikonos, QuickBird, WorldView-1, GeoEye-1, and WorldView-2. WorldView-3’s 1.24m multispectral spectral imagery is some of the highest resolution that SkyTruth is able to use.
Planet’s Doves make up the world’s largest constellation of Earth-imaging satellites. The Dove satellites are only about the size of a loaf of bread, which means that Planet can quickly improve on their designs, and can build and launch satellites frequently — enough to capture an image of the entire Earth at roughly three meters every single day. This data set is accessed through Planet’s Explorer platform.
This is Planet’s third constellation, and it is made up of 15 satellites. They can be “tasked” to image any spot on Earth in high resolution (72 centimeters). They can even capture video for up to 90 seconds. This data set is also accessed through Planet’s Explorer platform.
Our analysts apply a variety of tools and approaches to satellite data to illuminate environmental impacts.
IMAGE PROCESSING AND ANALYSIS
This activity includes searching the catalogs of satellite images available for certain geographic areas; identifying which satellite sensor we want to access; and specifying the date range, seasonal restrictions, and other factors that allow an analyst to hone in on areas and features of interest. An analyst might then throw out the cloudy imagery that hides features on the ground. Analysis of the image varies and often depends on software to help illuminate features. Processing may also include enhancing the appearance of the image. Analysis today can include machine learning to identify patterns and features of interest. We then present the outputs in format that can be used by anyone in a digital mapping system.
We create our own interactive maps using the data so that users of all skill levels can see, use and understand what we’ve found.
Today, much processing occurs in the Cloud — that is, the network of remote servers hosted on the internet to store, manage, and process data — rather than on a local server or personal computer.
Not all data picked up by satellites or produced by people on the ground is easy to understand, so we use geographic information systems (GIS) to interpret and map information relevant to our mission. GIS is a framework for integrating many different types of data. It uses geographic locations and organizes layers of different information about a location in visual formats (such as maps or 3D scenes) to reveal patterns, relationships and situations that otherwise might remain unrecognized.
For example, the U.S. Coast Guard annually receives around 30,000 pollution reports from industry and citizens through the National Response Center (NRC). Few people have the time or patience to sort through thousands of text-only reports, so we devised a tool to collect all of these reports, pull out the important information, and plot it on a map for anyone to access. We turned this map into our SkyTruth Alerts tool, a free subscription that notifies users by email whenever pollution is reported in their subscription area. We have added information on oil and gas drilling activities in many states and are always looking for new ways to keep you informed about what is happening in the places you care about.
AUTOMATIC IDENTIFICATION SYSTEM (AIS)
AIS is a system used by ocean-going vessels worldwide to identify other ships in their area. The International Maritime Organization requires vessels over a certain size to use AIS systems to prevent collisions and to help ports manage vessel traffic. AIS broadcasts, via radio frequency, vessels’ identification, position, course, and speed. This information allows SkyTruth, and our partners at Global Fishing Watch, to monitor cargo vessels, fishing vessels, tankers and other vessels for illegal activity related to bilge dumping, fishing, or more.
Artificial Intelligence refers to the development of computer systems to perform tasks that normally require human thinking.
Machine learning is a form of Artificial Intelligence that trains computers to recognize certain features on the landscape, so that they can scan thousands of images quickly and flag features or activities of concern. You can learn more about our approach to machine learning here.
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