New NAM Weather Forecast Data Now Available

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This week we’ve added an additional NAM weather forecast to the Planet OS Datahub, which now provides API access to seven North American Mesoscale Forecast System products:

NAM dataset provides a 60-hour forecast of pressure-level fields at 1-hourly and 3-hourly time steps and covers the contiguous United States at a 5 km resolution.

Researchers use NAM as a driver for complex air pollution simulations, but it is also used by public and private meteorologists to guide near-term weather forecasts within the United States. In a hierarchy of weather forecast models, it falls between the global medium range forecast GFS and the rapid refresh model HRRR.

Visit the Planet OS Datahub to access this dataset and over 2,100 variables from the world’s leading Earth Science data publishers. Interested in discussing different datasets and developer tools with researchers, developers and data scientists from around the world? Join our Slack community:

Planet OS Community on Slack

NASA Climate Data Webinar Resources

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On September 21, we hosted our very first Product Webinar with Dr. Sangram Ganguly (NASA Ames & BAERI) and myself, where we discussed How to Easily Analyze NASA Climate Models using the Planet OS OpenNEX Data Tool. I would now like to share some of the resources and materials we used during our session so that you could try them out yourself.

Please let me know at if you have questions or comments.

See you at the next #PlanetosWebinar!

Geospatial IoT Insights – September 28

Euroconsult published its forecast for satellite-based Earth Observation market growth through 2025. The commercial data market totaled $1.7 billion in 2015 and is anticipated to total $3 billion in 2025. The value-added services market reached $3.2 billion in 2015, and is growing at a faster rate than the data market alone (11% 5-year CAGR). Notably, the commercial data and value added services key markets are not overlapping. Defense represents 61% of the commercial data market, followed by maritime, infrastructure, and resources monitoring sectors. In these fields, most of the analytics is performed in-house. On the other hand, value added services market relies often on lower-cost, coarser resolution data. [GISuser]

What’s the Difference Between Consumer and Industrial IoT? A simple question, but not so easy to answer. Electronic Design has published a much needed comparison of different types of IoT, explaining where exactly the line is between Consumer IoT, Commercial IoT, and Industrial IoT. [Electronic Design]

A useful source worth looking at when you are planning to get started with your first IoT project: the Linux Foundation has listed 21 open source projects for IoT. If you are looking to get started with an IoT project, this is a good source to begin with. [The Linux Foundation].

Geospatial IoT Insights – September 21

Industrial IoT will score over consumer IoT. While until 2014, consumer-focused IoT solutions garnered a slightly higher share of total IoT investments, industrial IoT solutions attracted over 75% of funding in 2015 as compared to consumer IoT companies. This trend is expected to continue in 2016 by a larger order of magnitude—2-3 times more than consumer IoT. [Livemint]

NOAA has released its final Ocean Noise Strategy Roadmap, which will guide the agency in more effectively and comprehensively managing ocean noise effects on marine life during the next decade. This will create a demand for ocean noise related applications. To understand the importance of ocean noise, it’s good to read an interview we made with Dr. Christopher W. Clark when he joined us some years ago. [NOAA]

There is a continuous effort to improve climate models, and the researchers have now discovered how to make global weather and climate models to better capture the effect of clouds on climate. It’s just one example how data products can be improved by adding new data sources. Which again is one of the goals we are hoping to reach with Planet OS Datahub while making all environmental data easily findable and accessible via single, consistent API. [Earth & Space Science News]

High-Resolution Rapid Refresh (HRRR) and Precipitation Data


This week we added three new datasets to Datahub, including NOAA’s High-Resolution Rapid Refresh (HRRR) forecast for the contiguous United States.

High-Resolution Rapid Refresh (HRRR)
HRRR is a short range weather forecast that gives accurate estimates of the weather over the next few hours. Forecasted parameters are provided at a 3 kilometer spatial resolution, making it valuable for forecasters who can now investigate and monitor storm fronts with much greater detail. Having higher resolution short term data is important for better localized weather forecasts, and could also help pilots and air traffic controllers detect pockets of turbulence with greater accuracy.

In addition to HRRR, we’ve also added two precipitation datasets:

Precipitation analysis is essential in agriculture and forestry for estimating crop and fire hazard. Quantitative precipitation forecast is simple product based on ensemble forecast and giving the most accurate precipitation outlook for the next several days.

And in case you missed it, last week David Berlind from ProgrammableWeb shared his experiences working with the Planet OS API in his post How Dynamic Personalization of API Documentation Improves the Developer Experience.

“What makes [the documentation] great is how it already includes my actual API key (which I obfuscated for obvious reasons) which makes the entire string cuttable and directly pastable into my API calls whether they’re run from my source code in a language like Javascript or Python, or from the cURL utility at my command prompt.”

Thanks for the kind words David!

Photo courtesy of NOAA.

Investigate NASA Climate Data Using Planet OS Climate Data Access Tool


There used to be only two ways to work with climate models: run complex fluid dynamics code on a supercomputer or look at a picture or graph made by someone who did. NASA and Amazon have changed that by publishing the results of model runs from institutions around the world as part of their OpenNEX program. Anyone can now access these datasets for free, meaning that researchers, journalists, students, (quantitative) analysts, risk modelers, etc., can explore the conclusions of top climate change investigators.

Last week, our team at Planet OS announced the OpenNEX Data Access Tool that makes working with this data much easier. With an interactive web interface and transformation tools packaged using state-of-the-art container technology, doing hands-on work with climate model results is now convenient for all who are interested. The OpenNEX data tool is especially valuable for professionals from insurance, agriculture, energy, transportation and many other industries affected by climate.

Next Wednesday, September 21st, Dr. Sangram Ganguly and I will give a webinar where we demonstrate in very practical terms how to select and use this tool to access and use the results of the climate models.

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Geospatial IoT Insights – September 14

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In the wake of installing first U.S. offshore wind turbines, the White House has unveiled a national strategic plan that paves the way for construction of 86 GW of offshore wind by 2050. To put this into a context, as of June 2016 the global grid-connected offshore wind energy capacity was approximately 13 GW, as we concluded in the Planet OS offshore wind energy 2016 market report. [reNEWS]

The World Bank has released a new study on air quality, The Cost of Air Pollution: Strengthening the economic case for action. It comes with a huge infographic that emphasizes the risks and consequences of polluted air. Understanding what is happening with the air quality in different locations is essential to any human activity and so a few days ago we made air quality data also available via Planet OS API. [World Bank]

Our team at Planet OS has been building geospatial data software since 2012 and it has been quite a challenge as geospatial data is very diverse. However, if you’re passionate enough and have the skills, you can build your own geospatial data solution. You will still need the infrastructure. Geospatial World recently released a helpful overview on how to use Amazon Web Services for Geospatial. We can definitely recommend it since we’re long time customers of AWS. [Geospatial World]

Hello, World

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As a new member of the Planet OS community, I wanted to introduce myself and explain why I’m so excited to join the team. I’ve spent the last 30 years in the computer industry creating new emerging technology for enterprises, working for both large companies like Red Hat, NetApp and Hewlett Packard, as well as a number of startups. Most recently I led the Big Data initiative at Red Hat, and it became clear to me that every industry was about to go through a digital transformation whereby data would become the new foundation for competitive advantage and business innovation.

As I reflected on what role I wanted to play in this data-driven future, it became clear to me that I should follow my personal passion to repair the environment. During my research into how data could be used to improve the environment, I discovered Planet OS and their globally accessible programmatic database of geospatial environmental data. After meeting the team, it was a good fit and so I joined in June 2016. I am honored to be part of the driven Planet OS team and enthusiastic to help our customers use geospatial and IoT data to change the way data-driven decision are made to improve the bottom line and to build a better planet.

Feel free to reach out at

Air Quality Data: Ozone Concentration & Fine Particulate Matter

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We’ve just added two air quality datasets to Datahub. Ozone concentration and fine particulate matter are two of the five “criteria” pollutants regulated under the U.S. Clean Air Act. Now you can use the Planet OS API to get a 48-hour forecast for each.

While air quality in the United States has improved significantly since the 1970 Clean Air Act, poor air quality is still responsible for an estimated 80,000 premature deaths in the United States each year. In fact, a recent study reports that in 2013, 87% of the world’s population lived in areas exceeding the World Health Organization (WHO) Air Quality Guideline of 10 μg/m3 PM2.5 (annual average).

The National Air Quality Forecast System (AQFS) was developed in support of a Congressional mandate to implement an operational air quality forecast system that benefits public health. Through a partnership between the National Oceanic and Atmospheric Administration (NOAA) and Environmental Protection Agency (EPA), daily air quality forecast guidance is produced for a variety of pollutants and particulate matter.

Today we’ve added two of those Air Quality Forecast System products to Datahub, which can now be accessed via the Planet OS API:

Each of these datasets is updated twice daily and provides a 48-hour forecast at a 1-hour resolution with a spatial extent covering the contiguous United States.

Photo via Michael Davis-Burchat.

Geospatial IoT Insights – September 8


New high-resolution elevation data available for Alaska. The White House, the National Science Foundation, and the National Geospatial-Intelligence Agency have released the most accurate digital elevation maps of Alaska ever created. The new maps have a horizontal resolution of about 7 to 17 feet, versus more than a hundred feet for previously existing topographical maps. The data is available here. High-resolution elevation data for the rest of the Arctic will follow next year. [National Geographic]

The IoT growth estimates aren’t very useful. Regardless, if it’s 10 or 50 billion things connected to the internet by 2020, it’s clear that new market and new products will emerge to tackle the related challenges. However, this new survey tells us what benefits business leaders are expecting from IoT. Remarkably, the top expectation Cost savings from operational efficiencies matches with the results Planet OS Powerboard is already providing to its first customers. [Forbes]