The realms of industry and academia can often feel like separate worlds. On one hand, industry can offer the promise …
In the last two years, we applied Planet OS data sets to visualize the snow conditions before Christmas. This year, …
On October 27th, the most severe storm in over the past 50 years struck South-Eastern Estonia. Falling trees, flying roofs, …
On August 24, 2019, a tropical wave in the Central Atlantic developed into an extremely powerful, long-lived cyclone, Hurricane Dorian. …
This past Earth Day Weekend, a group of more than one hundred students and young professionals joined forces to apply climate and environmental data towards addressing increasingly pressing climate concerns.
Since March 19th, heavy rains and flash floods have inundated Iran. Over 1900 cities, towns, and villages across 25 provinces have been overrun by this historic downpour.
Amid dramatic ice melt in the Arctic, transportation networks, ecologies, and geographical boundaries have transformed. Just last year, shrinking ice in the north opened a new shipping route from Europe to East Asia.
Last year’s headlines were marred by stories of forest fires around the world. The 2018 California wildfires and Eastern Australia bushfires collectively devastated nearly four million acres. Yet, many will be surprised to know that while these fires have been contained and extinguished, the loss of life and property caused by these events has continued today.
The GDPR has established strict rules for how organizations must approach processing of personal data. One of the law’s key requirements is to implement Data Protection by Design (DPbD). DPbD essentially compels organizations to adopt a Privacy by Design (PbD) approach to the design phases of their technologies and business processes. If your organization has not yet done so, you’re nearly a year too late - GDPR turns one year old on May 25th.
In the US Midwest, low-temperature records were broken thanks to a polar vortex from the Arctic. Chicago was especially affected, with officials warning residents of the risk of “instant frostbite” should they venture outside.
Humankind has been trying to predict the shifting patterns of the world around us for centuries. Weather forecasting, our way of predicting the conditions of atmosphere for a given location and time, is one of the critical tools employed to do so. As long as we have had these tools, our “environmental psychism” has propelled us forward.
At Planet OS, we know that building data-driven applications requires reliable and consistent programmatic access to premium datasets — this is our mission and why we exist. In operating our platform, we occasionally discover that among the 100 datasets we maintain, specific data sources are no longer available. When this happens, we do our best to replace the old with the new, or in the absence of a newer version a similar dataset.
With digital interactions continuing to consume an ever-increasing portion of our personal and professional lives, the ability to determine the validity and authenticity of data is of critical importance. This week on State of Identity I sit down with the founder of Intertrust’s new project that utilizes a combination of blockchain technology and trusted assertions to create a digital trust infrastructure capable of scaling globally to meet this incredible challenge.
As we step into 2019, let us take a look back at the eventful year of 2018. For Planet OS, our Datahub team, and the global climate overall, 2018 was filled with a series of significant events. In the midst of the Winter Olympics, unprecedented natural disasters, and revolutions in renewable energy, Planet OS has continued its mission to deliver high-quality environmental data.
Last year we applied Planet OS data to visualize the snow conditions during Christmas. This year, we decided to take a look a bit sooner to project whether or not we will have a snow-filled holiday season. For this analysis, we used a high-quality snow cover dataset and the Planet OS API.
It’s no secret that present technologies have rapidly evolved as we try to push the limits of computing. While these advancements are often most apparent in the releases of the newest smartphone or self-driving car, our numerical weather prediction models have undergone exciting advancements as well.
Either on TV or in real life, we have all seen a beautiful scene of the ocean where the waves roll smoothly from sea to shore. There are often even surfers trying to catch these large waves to experience the ocean’s power. However, have you ever considered where these waves come from or what distances they travel to reach the shore?
In 2017, Hurricane Harvey inundated Houston, Texas, causing many to lose their lives, property and faith in their emergency response services. A little more than a year later, towns across the Southern part of the United States experienced untold devastation; first from Hurricane Florence, then from Hurricane Michael. The frequency and severity of hurricanes and their profound effect on communities cannot not be disentangled from the wider pattern of warming that is changing our planet. The new reality is that extreme weather events will become more common and will require new levels of data-driven preparations. This week, our data integration engineer Eneli Toodu uses the NOAA OISST and the Planet OS Datahub API to derive a comparison between Hurricane Michael and Hurricane Florence.
This past month, Governor Jerry Brown signed a historic executive order to make California carbon free by 2045. The recently passed bill aims to take dramatic steps towards reducing the negative impacts of climate change, and will require the entirety of California’s electricity come from clean, carbon free sources.
This past summer, weather and climate-caused events have dominated the news and impacted the day to day lives of many. Each year, across the globe, heatwaves are getting hotter, while cold days are fewer. This summer, the United States alone surpassed nine all-time temperature records, with an additional ten records tied so far.
It was only last December when we analyzed the pollution spike from the Thomas Fire, one of the largest wildfires in California’s history. Now, only half a year later, California and other states are combatting large wildfires once again.
During the past few weeks, in conjunction with the AWS Public Dataset Program, we have been working to bring reanalysis data to AWS. Today we are excited to announce that an initial subset of ECMWF ERA5 data is now available in Amazon S3.
As the planet gets warmer and warmer, the frequency of uncontrollable, devastating fires is on the rise. Fueled by weather, wind, and dry underbrush, hundreds of thousands of wildfires burn millions of hectares of land every year.
Over the last few years, the amount of data generated by consumer oriented sensors rose significantly. Everything from smart watches, thermostats, to cars and public transport are producing some form of numerical output.