With the new powerful Earth observation satellites continuously launching, new improved data products emerge on almost weekly basis. The rapid increase in quality and quantity of Earth data products lays a framework for high value data analytics in virtually every industry, and also in climate analysis.

“With this launch we are taking another step toward advancing the Copernicus programme, which is the most sophisticated Earth observation system in the world. And we are planning to add two more satellites to the constellation in the next months: with Sentinel-5P and Sentinel-3B.”

— Jan Woerner, ESA Director General

Sentinel-2B satellite launched

The identical twin of operational Sentinel-2A satellite was launched on March 7, doubling the coverage of high-resolution optical imaging in the Sentinel-2 mission for the EU Copernicus environmental monitoring system. Besides imaging in high resolution and in different wavelengths, the key to assessing change in vegetation is to image the same place frequently.

The Sentinel-2 mission is based on a constellation of two satellites orbiting 180° apart, which along with their 290 km-wide swaths, allows Earth’s main land surfaces, large islands, inland and coastal waters to be covered every five days. This is a significant improvement on earlier missions in the probability of gaining a cloud-free look at a particular location, making it easier to monitor changes in plant health and growth.

First images from GOES-16 Lightning Mapper

The multifunctional GOES-16 satellite has delivered first images from its Geostationary Lightning Mapper. This kind of data has never before been available. It provides continuous data on lightning flashes in the Western Hemisphere, so forecasters know when a storm is forming, intensifying and becoming more dangerous.

Accurate tracking of lightning and thunderstorms over the oceans will support safe navigation for aviators and mariners, as it’s not visible for land-based radars and in some cases also for other satellites.

The Geostationary Lightning Mapper also detects in-cloud lightning, which occurs five or more minutes before potentially deadly cloud-to-ground strikes. This means more time to provide early warnings to those involved in outdoor activities in the storm areas.

Tracking Deforestation by Measuring the Distance to the Nearest Forest

Using satellite images, researchers established a method of calculating the distance between any point in the US and the nearest forested area. They tracked this data using information from 1992, and again in 2001. The average distance to the nearest forest increased by a third of a mile. This new measuring tool is being called the forest attrition distance. This metric not only takes the quantity of the forest into question, but the quality as well.

Interactive 3D Earth shows most polluted places in the world

AirVisual has created the real-time visualization of global air quality. The mesmerizing globe uses satellite imagery, US government meteorological data, and billions of data points daily from government air-quality monitoring stations in the US, Singapore, Canada, China, Japan, and elsewhere.

Other Earth data news

• Mapping in R just got a whole lot easier
• How an energy operator missed a coming heatwave because it relied on data from just two urban weather stations
• China’s second-generation weather satellites has sent its first collection of images and data
• Statistical technique for automatically cleaning erroneous data from weather-balloon observations
• Three new global Land Surface Analysis Satellite Applications Facility data products available: Land Surface Temperature, Albedo, and Snow Cover
• Big data may revolutionize climate science
• 5 Awesome things about Google Earth Engine

Thanks for reading! Are you using weather / climate / environmental data? In Planet OS we have built a open data catalog and APIs for discovering and accessing sensor data. I suggest to give a look, especially if you’re thinking to build your own data-driven application.

Pro tip: My team distributes these blog posts once a week also via email. Simply add yourself to the list and find the next issue in your mailbox.

Previous post → “World’s Largest Wind Mapping Project”

Data-Driven Planet #34 — A Flood Of New Satellite Data was originally published in Planet OS (by Intertrust) on Medium, where people are continuing the conversation by highlighting and responding to this story.

Wind dynamics is far more complex than it might seem at first glance. The experiment in Portugal is a first attempt to push large-scale wind mapping down to resolutions of 100–500 meters. 54 masts, outfitted with sensors, measure a wide range of variables 20 times per second, and 22 instruments will study small-scale wind flow in three dimensions using LIDAR. The outcome should benefit onshore wind power industry globally.

“Europe gets 11% of its total energy from wind. But just a 10% shift in wind speed can change the amount of energy produced by up to 30%”

— Jakob Mann, a wind-energy researcher at the Technical University of Denmark.

World’s largest wind-mapping project

An unprecedented arsenal of meteorological equipment will study speed, direction and other characteristics for the world’s most detailed wind-mapping project in Portugal.

The aim is to understand fundamental properties of wind flow over complex terrain, to help researchers improve atmospheric computer models and enable engineers to decide where to put wind turbines to get the most energy from them. Most importantly, the findings can be applied in other locations.

92% of us are breathing unsafe air

World Health Organization has released a new interactive map showing where are the places affected worst and least by air pollution.

Large areas of developed countries including the US, Canada, Australia, New Zealand and Scandinavian nations meet safety guidelines. But, as the map shows, much of Europe is breathing dirty air.

This research is its most detailed to date on outdoor air pollution by country. It shows around 3 million deaths globally are linked to pollution from vehicles, power generation and industry.

This WHO map screenshot shows global ambient air pollution:

Annual mean ambient on this map is PM2.5 (µg/m3), and the scale of the colors is below the map.

Oceans of data from the world’s offshore wind farms

Offshore wind turbines in remote locations make it harder to fix turbines if something goes wrong, so monitoring turbines’ data has a key role in avoiding costly failures.

Sensors on the turbines generate vast amounts of data on a turbine’s operational condition. Using AI and machine learning, it’s possible to make forecasts and models regarding turbines’ future behavior and optimize their own operation.

AI-based software in wind turbines not only helps predict problems but can tell wind farms how much power to produce, changing the output minute by minute.

New climate data product on water

A new Climate Data Record aggregates several types of water data to provide a clearer, broader picture of Earth’s climate. This long-term record of complementary hydrological data by NOAA National Centers for Environmental Information includes total precipitable water, surface temperature, rainfall, sea ice, and snow. It can be used for forecasting trends and changes within these observations.

Other Earth data news

• Geospatial analytics market worth $73.91 billion by 2021
• Creating a a data-enriched city
• Know how remote sensing is useful for development

Thanks for reading! Are you using weather / climate / environmental data? In Planet OS we have built a open data catalog and APIs for discovering and accessing sensor data. I suggest to give a look, especially if you’re thinking to build your own data-driven application.

Pro tip: My team distributes these blog posts once a week also via email. Simply add yourself to the list and find the next issue in your mailbox.

Previous post → “How Air Pollution Is Predicted”

Data-Driven Planet #33 — World’s Largest Wind Mapping Project was originally published in Planet OS (by Intertrust) on Medium, where people are continuing the conversation by highlighting and responding to this story.

We all share the air we breathe, and this week we take a look at the latest advancements in predicting air pollution. The last 25 years have completely changed the way we predict environmental events, and the next step will be smart systems telling us what to do in order to reduce damage.

“Much of the analysis of the model results — what they meant, how they compared to measured data, etc. — was done manually with human intelligence, reams of printouts, and various custom scripts.”

— Jay Hardikar, IBM researcher, on how data analysis was done 25 years ago.

Advances in technology have completely changed the way we predict air pollution

Ninety-two percent of the world’s population lives in areas with unhealthy air. With the recent news on the devastating effects of air pollution, it’s more important than ever to be able to predict and combat air pollution.

For years, IBM researchers have been working on an intelligent system that is capable of learning to predict the severity of air pollution, with the end goal of providing specific recommendations for how to reduce pollution to an acceptable level.

This is what makes the title story by IBM researcher, Jay Hardikar, such a fascinating read. He explains how he used to work on predicting air pollution 25 years ago and compares it to how it is done in the current age of cloud computing, big data analytics, and the IOT, providing insight into the methods that can be implemented for various types of environmental analysis.

The Global Geospatial Industry Outlook

Geospatial Media and Communications has released a free report highlighting the trends and directions of the global geospatial industry along with an index on the geospatial readiness of 50 countries across the globe.

There is also a shorter summary of the report focusing on what cross linkages geospatial has with other technologies.

How energy-data-as-a-service is enabling innovation

Thanks to the increasing number of energy sources and growth in energy-related data, energy is no longer considered a line item cost, but a resource that can be optimized and reduced with benefit to the enterprise. But the energy market is fragmented, and different utilities have widely different data formats and release cycles. This requires a lot of data integration effort from the enterprise customers who are looking to benefit from data analytics.

Given the substantial opportunities that advanced energy management provides, the aggregation and accessibility of energy data is a growing business. Therefore, the energy-data-as-a-service model holds great promise for the industry. It enables various industry players to focus on the core offerings and let a third party provide the foundational energy data that enables them to deliver their products and services. Energy optimization and energy procurement are some of the examples of existing services within the energy industry that could benefit from a single source of energy data.

USGS releases JavaScript library for plotting water data

A new library, called GWIS (Graphing Water Information System), can create time-series plots of information measured at U.S. Geological Survey hydrologic data collection sites across the United States. This is a particularly timely announcement given the recent rainstorms in California and elsewhere.

The main GWIS plot features include interactive zoom and legend, custom controls, multiple data series support, and more.

Other Earth data news

• New weather satellites can spot floods before they happen.
• Recent advances in ground-penetrating radar data analysis could help reveal aquifer structure in unprecedented detail.
• Geoengineering solutions to climate change?
• European Marine Observation and Data Network launched a data ingestion portal.

Thanks for reading! Are you a fan of weather / climate / environmental data? In Planet OS we have built a open data catalog and APIs for discovering and accessing sensor data. I suggest to give a look, especially if you’re thinking to build your own data-driven application.

Pro tip: My team distributes these blog posts once a week also via email. Simply add yourself to the list and find the next issue in your mailbox.

Previous post → “How Weather Data Boosts Retail”

Data-Driven Planet #32 — How Air Pollution Is Predicted was originally published in Planet OS (by Intertrust) on Medium, where people are continuing the conversation by highlighting and responding to this story.

This week, we’re exploring how data science is transforming the retail industry and improving retailers’ ability to cope with the always changing weather.

“Just as consumers now expect more from retailers, retailers should expect more from their data. Using location as a pivot point for decision making, retailers can put their data to work for them the way it was always intended to be.”
— Gary Sankary

Data drives retail more than any other business. A blog post by Gary Sankary illustrates how external data impacting sales, such as weather forecasts, can be very useful in business decisions when integrated and visualized properly. Mapping weather and CRM data together, gives retailers the insight to precisely adjust their sales forecasts. Aggregating data from different sources provides insight about how can an approaching weather event impact your stores, your customers, and your staff.

Sentinel 3 data access for beginners. Sentinel 3 data enables a wide range of use cases: ocean monitoring, water quality, sea ice charting, ship routing, climate monitoring, land use, vegetation state, height of rivers and lakes, wildfire monitoring, and more. Andrew Cutts, an EO system architect at CGI, has written up a simple tutorial on how to get started analyzing Sentinel 3 data. He recommends utilizing the Sentinel hub. As a main tool for processing the data, the ESA built Science Toolbox Exploitation Platform is the best option with which to start.

Hidden value of water data. Today approximately 1.8 billion people around the world lack access to safe drinking water, and nearly 2 billion people to sanitation. Extreme weather events worldwide, including droughts, are provoking migration and dislocations with widespread consequences. This is why many countries treat water data as a matter of national security, unwilling to share it. But collecting global weather and climate data and correlating it with relevant social data would help to create early warning systems to help predict and plan for water-related crises. The above gives a high priority to innovation in the field of gathering water data and creating new data products.

Race to provide commercial weather data heats up. Spire and its competitor GeoOptics are participating in a pilot project, announced by NOAA, to determine whether it can cut costs by using commercial weather data. The commercial satellites provide radio occultation data, which can be used to create precise temperature profiles of the atmosphere to feed into weather-forecasting and climate models. Weather forecasters around the world feed about 40 million environmental measurements into their models each day. Only 2,100 come from radio occultation, but that data has an oversized impact on the overall accuracy.

GOES-R satellite has submitted its first images. On January 15th, GOES-16 (its updated callsign) started to send back pictures. Compared to the previous generation of GOES satellites, it has three times the spectral channels capturing images at four times the resolution, with five times the efficiency. NOAA has already published a gallery listing the best images from the brand new satellite.

Thanks for reading! Are you a fan of weather / climate / environmental data? In Planet OS we have built a open data catalog and APIs for discovering and accessing sensor data. I suggest to give a look, especially if you’re thinking to build your own data-driven application.

Pro tip: My team distributes these blog posts once a week also via email. Simply add yourself to the list and find the next issue in your mailbox.

Previous post → “How Clouds Really Impact Solar Energy”

Data-Driven Planet #31 — How Weather Data Boosts Retail was originally published in Planet OS (by Intertrust) on Medium, where people are continuing the conversation by highlighting and responding to this story.

Scientists recently discovered that we have overestimated the negative impact of some types of clouds on solar energy. Studies have typically looked at just one cloud type: warm, low clouds. This leaves out a great diversity of clouds made of both water and ice, such as massive, heaped thunderheads. A recent study addressed this gap.

“Icy clouds may actually increase, not decrease, the amount of solar energy that reaches Earth.”

— Emily Underwood, Earth & Space Science News

Some clouds may not reflect as much sunlight as previously thought. On average, 70 percent of the world is cloud-covered. Considering a rising share of solar energy, it’s important to understand how clouds affect the efficiency of PV panels. Thanks to NASA’s “A-Train”, a constellation of six satellites that flies in formation, researchers were able to estimate the extent to which aerosols in different cloud types affect albedo and thermal infrared radiation. It turns out some types of clouds — like convective clouds and clouds with icier tops — reflect less solar radiation than previously thought.

Growth in renewable energy installation despite the smaller investments. In 2016, investment in clean energy fell to $287.5B, an 18% drop from a record $348.5B in 2015. However, despite this drop in investment, new build of clean energy projects increased–partly due to cost-competitiveness improvements in solar and wind equipment–meaning that more can be installed for the same price. These are important dynamics to understand when evaluating impact of future investments to the renewable energy total output such as China’s announcement to invest further $100 billion in wind power by 2020.

How blockchain can disrupt the utility industry. The utility industry is risk-averse to innovation because of its premise to provide stable, secure, and reasonably priced access to electricity. Blockchain, at its heart, is a self-sustaining, peer-to-peer database technology for managing, reducing, and eliminating intermediaries, and recording transactions with no central clearinghouse involvement. Seyi Fabode has written an easy-to-read story about how blockchain technology can improve utilities by speeding up the whole supply chain, while bringing down the operational costs.

Businesses harnessing climate data to sustain profits. Climate changes much more slowly than the seasons, but in a similar way it affects many industries. The greater impact of change and the availability of better data has made climate change risk assessments part of everyday business strategies. State Street, one of the biggest investment funds, is pressing its portfolio companies to disclose more information about how they are preparing for the impact of climate change on their businesses since it can have a material long-term impact on a company’s ability to generate returns.

Have you ever wondered how weather forecasts are created? Planet OS engineer Andres Luhamaa created a nice demonstration showing how to quickly build a weather forecast notebook with GFS model data by using the free Planet OS API. You will be able to go from raw data to animated weather maps and graphs with just a few simple commands. Accessing the raw data means that you are not limited to just creating weather forecasts, but you can run your own dedicated analysis or models on top of the data. If you are willing to learn more about using Python for processing weather data, you should look at the recently published Python Data Science Handbook, which is is freely available on Github.

Thanks for reading! In Planet OS we provide big data infrastructure that helps renewable energy companies improve their business results. To keep the industry engaged, each week we publish a carefully curated list of news we find important. Focused on the intersection of big data, Earth science, energy, and IoT, the Data-Driven Planet newsletter includes the week’s most notable developments in the market.

Start to follow our blog on Medium to be notified of the next update.

Previous post → “Why Energy Is The New Internet”

Data-Driven Planet #30 — How the Clouds Really Impact Solar Energy was originally published in Planet OS (by Intertrust) on Medium, where people are continuing the conversation by highlighting and responding to this story.

This week, TechCrunch published a wake-up call to draw attention to the revolution happening in the energy industry. The economic opportunities behind the changing energy industry are so big, that at first, they’re even hard to grasp.

“It goes well beyond Tesla. There is a long list of innovators emerging. They are building nanogrids, microgrids, distributed energy resources and virtual power plants; deploying new networks and intelligence that are driving down costs and improving services.”

— Brian Lakamp, Crunch Network contributor

Why energy is the new internet. A dynamic, distributed, redundant and multi-participant energy network built around clean energy generation, storage and delivery, is creating a new kind of healthy, robust economy — just like the Internet did in the 90s. It’s the foundation for smart-city technology.

The World Bank Group launched Global Solar Atlas. The primary aim of the Global Solar Atlas is to provide quick and easy access to solar resource data. The tool is really easy to use, automatically generating a detailed report after selecting a location on the map. The report provides long term and daily averages for different types of solar irradiation (horizontal, normal, tilted), and also estimated photovoltaic power output for a system of size, angle and tilt defined by the user.

The European Copernicus Earth Observation program released a comprehensive market report. A must-read for everyone involved in the Earth Observation and geospatial data industries. The 97-page document explains the key needs and benefits of all related businesses. For example, the European data-generating satellite program is helping to generate 50% more benefits to solar energy producers than traditional forecasts. It also helps to reduce the costs of precision farming service by 70% and to obtain a 5% productivity gain for fish farmers.

How can we predict the climate when we can’t predict the weather? Climate models can be pretty accurate, whereas everyone has felt the frustration caused by flawed daily weather forecasts. The story by Fast Company explains the relationship between the weather and climate data and how, over time, predictions are becoming more precise.

Using R with GIS Software. Although R started as mainly a statistical package, its use has grown to include a number of areas and has become one of the best languages to quickly and easily visualize geospatial data. Tom Faulhaber gives an example of using R on NASA OpenNEX climate data in a Planet OS webinar, available on Youtube. The mentioned demo starts around 28 minutes into the video. R can read and handle a variety of vector and raster data, including shapefiles, NetCDF, and GDAL supported formats. The power of R is increasingly supported by the GIS software providers, who are integrating R-based visualization and analytical tools into their GIS packages.

Thanks for reading! In Planet OS we provide big data infrastructure that helps renewable energy companies improve their business results. To keep the industry engaged, each week we publish a carefully curated list of news we find important. Focused on the intersection of geospatial data, earth science, energy, and IoT, the Data-Driven Planet newsletter includes the week’s most notable developments in the market.

Subscribe to our publication to be notified of the next update.

Previous post → “Sentinel 2 Doubles Down”

Data-Driven Planet #29 — Why Energy Is The New Internet was originally published in Planet OS (by Intertrust) on Medium, where people are continuing the conversation by highlighting and responding to this story.

European Space Agency (ESA) just announced that its Sentinel-2B satellite is set to launch in less than two months. Offering ‘color vision’ for Europe’s Copernicus program, the mission involves twin satellites, Sentinel-2A and 2B, combining high-resolution and novel multispectral capabilities. Sentinel-2A has been in the orbit already since June 2015. The launch is scheduled for 7 March at 01:49 GMT.

“We are off to a flying start and eager to get our baby into orbit so that it can join its twin and do the job of continuously delivering images to monitor our changing world.”

– Paolo Laberinti, ESA’s launch campaign manager

In this week’s Data-Driven Planet:

Sentinel-2B prepared for liftoff on 7 March. Sentinel-2B is designed to work in tandem with the Sentinel-2A, launched in June 2015. Just a month ago, the next set of Sentinel-3 altimeter data was made available and assimilated into models, helping to improve the determination and prediction of ocean currents, significant wave height, wind speed and sea ice thickness.

Data is a key aspect to wind turbine performance optimization. SgurrEnergy has assessed over 4.2 GW of wind farm capacity and come to the conclusion that turbines typically under perform expected power curves by about 2%. Capturing the actual wind conditions at the site is the most critical external data source which enables the highly valuable data analytics and the consecutive performance improvement. The importance of big data in wind is also supported by the prediction that wind farm operations and management optimization will require service contracts that allow operators to leverage big data and predictive maintenance tools to maximize returns on investments.

Using Earth Observation data without ever looking at a satellite image. We all know that the Earth Observation data is only a raw material for deriving the information — we need to make the decisions. Andrew Cutts, an EO systems architect, makes a good example in his blog post regarding how ESA Proba-V satellite imagery is used to generate a vegetation data product.

Connecting Earth Observations in Europe. The European ConnectinGEO project has mapped existing Earth Observation networks with science, private sector and with GEOSS and Copernicus stakeholders. The goal of the analysis was to understand the gaps in different Earth Observation themes and variables. By theme, the biggest gaps are in climate and ocean data, and by type, temporal resolution and extent are the main shortcomings of the existing data products.

Thanks for reading! As a part of our continued commitment to deliver operational intelligence to our customers, each week we publish a carefully curated list of news we find important. Focused on the intersection of geospatial data, earth science, energy, and IoT, the Data-Driven Planet newsletter includes the week’s most notable developments in the market.

Subscribe to this Medium Channel to be notified of the next update.

Previous post → “Boosting Wind With Supercomputers”

Data-Driven Planet #28: Sentinel 2 Doubles Down was originally published in Planet OS (by Intertrust) on Medium, where people are continuing the conversation by highlighting and responding to this story.

Researchers at the National Oceanic and Atmospheric Administration (NOAA) are performing supercomputer simulations in order to improve wind predictions. The utility operators can soon start trusting the forecasts so that on windy days they could rely completely on wind power and turn off the coal plants.

“To make wind predictions that are sufficiently accurate for utility operators, Olson said they need to model physical parameters at a 750-m resolution — about one-sixth the size of Central Park, or an average wind farm.”
 — Joe Olson, the Lead Model Developer of NOAA

In this week’s Data-Driven Planet:

Predicting wind accurately becomes more necessary as the share of the wind in the total energy mix continues growing. To give utility operators better forecasts that would help to make the cost of wind energy a little cheaper, NOAA is developing numerical weather prediction models that can provide more accurate wind forecasts in regions with complex terrain.

Freely available Sentinel remote sensing data is useful for agriculture, energy, environmental, insurance, and others industries. Short revisit times, multi-spectral coverage and high resolution make it an unique data product. There is a growing number of sources and tools to work with Sentinel data and this curated list is a nice place to get started.

What are the 5 predictions on what the new year will bring for renewable energy in 2017? Solar growth, net metering, utility-scale growth, increasing corporate demand, and a boost from policies. Beyond mainstream renewable energy sources, it’s worth to keep an eye on the promising new energy sources.

Coal is receding because of renewable energy. As a milestone in Europe, for the first time in history the UK generated more energy from wind than from burning coal. On a related note, this map shows real-time CO2 emissions of the European electricity generation. As you can see, Poland’s coal and Estonia’s oil shale make them distinctively stand out among the others.

What’s the value of an accurate weather forecast? Spire, the weather satellite company, says businesses will lose globally due to bad weather a staggering $2.8 trillion in 2017. Many organizations around the world are working on solving this problem, and a group of researchers are planning to create reference datasets to improve weather satellite data quality.

As a part of our continued commitment to deliver operational intelligence to our customers, each week we publish a carefully curated list of news we consider to be important. Focused on the intersection of geospatial data, earth science, energy, and IoT, the Data-Driven Planet newsletter includes the week’s most notable developments in the market. Subscribe to this Medium Channel to be notified of the next update.

Data-Driven Planet #27: Boosting Wind With Supercomputers was originally published in Planet OS (by Intertrust) on Medium, where people are continuing the conversation by highlighting and responding to this story.

It’s been a busy week, despite the New Year’s celebrations. Michael Liebreich, founder of Bloomberg New Energy Finance, wrote a gloomy renewable energy poem, the meaning of which depends on the direction of reading. At the same time, The International Renewable Energy Agency (IRENA) came out with an in-depth perspective on the global energy transition forecast that, among other things, states that to meet the Paris Agreement goal, renewable energy deployment must happen six times faster than it is today. Strikingly, it turns out that doubling renewables will save up to 15 times more than it costs!

Wind would be the largest source of power capacity with the Renewable Energy Roadmap Options, just ahead of natural gas, followed by coal.

— IRENA REmap: Roadmap for a Renewable Energy Future, 2016 Edition.

In this week’s Data-Driven Planet:

• Wind could be the largest source of power by 2030. The International Renewable Energy Agency (IRENA) has published its annual report ‘Roadmap For a Renewable Energy Future’ providing a plan how the world can double the share of renewable energy in the energy mix by 2030, reducing global CO₂ emissions from energy use by notable 35%, while making wind the largest source of power capacity.
• India has silently become the innovation leader in adapting renewable energy technologies to its economy. The world’s largest solar farm followed by the world’s first industrial plant capturing the CO2 emissions from a coal boiler and using the CO2 to make valuable chemicals. Most importantly, it’s all been done without subsidy.
• A noteworthy warning from the Greentech Media’s forecast ‘5 Trends Utilities Need to Watch in 2017’: utilities should pay close attention to technology companies. If they don’t bother to integrate suite of different services into their leading technology platforms via APIs, they’ll soon fall behind in competition.
• A growing number of traditional offshore energy companies are expanding into the renewable energy sector. Major operators like Eni and Statoil are leading the way and as a consequence, new opportunities open up for a variety of service companies.
• Have you ever wondered how satellite data is transformed into weather forecasts? Read the fairly technical insight into a NASA project that removes the gap between research and operations, introducing new composites of satellite imagery to weather forecasters.

As a part of our continued commitment to deliver operational intelligence to our customers, each week we publish a carefully curated list of news we consider to be important. Focused on the intersection of geospatial data, earth science, energy, and IoT, the Data-Driven Planet newsletter includes the week’s most notable developments in the market. Subscribe to this Medium Channel to be notified of the next update.

Data-Driven Planet #26: Deep Dive Into the World’s Energy Revolution was originally published in Planet OS (by Intertrust) on Medium, where people are continuing the conversation by highlighting and responding to this story.

MIT just released a comprehensive, 300+ page report titled ‘Utility of the Future’. The study evaluates economic, regulatory, and technical impacts of the ongoing evolution of the power sector worldwide.

“Information and communications technologies are rapidly decreasing in cost and becoming ubiquitous, enabling more flexible and efficient consumption of electricity, improved visibility of network use, and enhanced control of power systems.”

— MIT study

The suggestions in the study include that better utilization of existing assets and smarter energy consumption hold great potential for cost savings; conflicts of interest within the industry must be minimized; and the wholesale market design must incorporate distributed resources.

In this week’s Data-Driven Planet:

Learn what it takes for businesses to realize the full potential of their data, and how researchers envision a super-connected, smart city of the future.

• MIT’s comprehensive study on the Utility of the Future.
• Renewables make nearly a third of Germany’s electricity in 2016.
• Blockchain underpins Germany’s new 4.0 100% renewable energy plan.
• Harward Business Review: Why you’re not getting value from your data science.
• Infographic: 2016 — A record year for the clean energy business.
• The future of super-connected, green and resilient smart cities.

As a part of our continued commitment to deliver operational intelligence to our customers, each week we publish a carefully curated list of news we consider to be important. Focused on the intersection of geospatial data, earth science, energy, and IoT, the Data-Driven Planet newsletter includes the week’s most notable developments in the market. Subscribe to this Medium Channel to be notified of the next update.

Data-Driven Planet #25: Utility Of The Future was originally published in Planet OS (by Intertrust) on Medium, where people are continuing the conversation by highlighting and responding to this story.