ENVI Analytics Symposium 2016 – Geospatial Signatures to Analytical Insights

HySpeed Computing is pleased to announce our sponsorship of the upcoming ENVI Analytics Symposium taking place in Boulder, CO from August 23-24, 2016.

EAS 2016

Building on the success of last year’s inaugural symposium, the 2016 ENVI Analytics Symposium “continues its exploration of remote sensing and big data analytics around the theme of Geospatial Signatures to Analytical Insights.

“The concept of a spectral signature in remote sensing involves measuring reflectance/emittance characteristics of an object with respect to wavelength. Extending the concept of a spectral signature to a geospatial signature opens the aperture of our imagination to include textural, spatial, contextual, and temporal characteristics that can lead to the discovery of new patterns in data. Extraction of signatures can in turn lead to new analytical insights on changes in the environment which impact decisions from national security to critical infrastructure to urban planning.

“Join your fellow thought leaders and practitioners from industry, academia, government, and non-profit organizations in Boulder for an intensive exploration of the latest advancements of analytics in remote sensing.”

Key topics to be discussed at this year’s event include Global Security and GEOINT, Big Data Analytics, Small Satellites, UAS and Sensors, and Algorithms to Insights, among many others.

There will also be a series of pre- and post-symposium workshops to gain in-depth knowledge on various geospatial analysis techniques and technologies.

For more information: http://harrisgeospatial.com/eas/Home.aspx

It’s shaping up to be a great conference. We look forward to seeing you there.

Constellations, Clouds & the Conundrum of Big Data Processing

HySpeed Computing is proud to be featured in the inaugural issue of UPWARD, the quarterly magazine of the ISS National Lab.

UPWARD

Constellations, Clouds & the Conundrum of Big Data Processing

“For millennia, humans have looked up to the sky to find constellations of stars, wondering what mysteries they hold. Today, we live in a world where constellations of satellites look down on us, hoping to unravel mysteries as well – by capturing highly complex images of Earth.

“In the commercial remote sensing market, the imaging of Earth from space has experienced a technical tsunami, giving rise to a population explosion of smaller but far more capable satellites with new sensing and communication capabilities. In the near future, constellations of nano-, micro-, and other small-sats will swarm low Earth orbit like drones filling the skies on Earth.”

See the full article beginning on page 10…

Conundrum of Big Data Processing

ENVI Analytics Symposium – Come explore the next generation of geoanalytic solutions

HySpeed Computing is pleased to announce our sponsorship of the upcoming ENVI Analytics Symposium taking place in Boulder, CO from August 25-26, 2015.

ENVI Analytics Symposium

The ENVI Analytics Symposium (EAS) will bring together the leading experts in remote sensing science to discuss technology trends and the next generation of solutions for advanced analytics. These topics are important because they can be applied to a diverse range of needs in environmental and natural resource monitoring, global food production, security, urbanization, and other fields of research.

The need to identify technology trends and advanced analytic solutions is being driven by the staggering growth in high-spatial and spectral resolution earth imagery, radar, LiDAR, and full motion video data. Join your fellow thought leaders and practitioners from industry, academia, government, and non-profit organizations in Boulder, Colorado for an intensive exploration of the latest advancements of analytics in remote sensing.

Core topics to be discussed at this event include Algorithms and Analytics, Applied Research, Geospatial Big Data, and Remote Sensing Phenomenology.

For more information: http://www.exelisvis.com/eas/HOME.aspx

We look forward to seeing you there.

Big Data and Remote Sensing – It’s all about information and applications

From the launch of the first Earth observing satellite, to today’s growing space industry, the volume of remote sensing data continues to grow at a remarkable rate. Furthermore, with the emerging utilization of drones, aka unmanned aerial vehicles, and deployment of low-cost satellite constellations, we are on the cusp of a momentous leap forward in data accessibility.

For example, consider the growth of private-sector drones, i.e., those used for scientific research, civil applications and business development. According to a March 2013 report from the Association for Unmanned Vehicle Systems International (AUVSI), assuming the FAA determines how drones fit within commercial airspace by 2015, it is expected that in just ten years the drone industry in the U.S. will generate more than 100,000 jobs and $80 billion of revenue. This includes an immense number of individual drones, on the order of hundreds of thousands, each generating their own streams of remote sensing data.

As another example, consider the pending growth of new low-cost commercial satellite constellations, such as those planned by Skybox Imaging and Planet Labs. Current plans include 28 satellites to be launched by Planet Labs and 24+ satellites to be launched by Skybox Imaging, where each constellation has the objective of achieving cost-effective, near real-time, high-resolution imaging of our planet’s surface. Planet Labs plans to launch its constellation in early 2014, and Skybox Imaging plans to begin launching later in 2013, so data from both companies will soon be available.

There are many questions associated with all of this growth: Where will all this data be stored? How will data be efficiently discovered, accessed and visualized? What types of processing and data management tools will be needed? How will this data be used? What new types of applications will be devised to leverage the information derived from this data?

Amongst these questions, we focus our discussion here on the applications. However, note that the challenges associated with data storage, discovery and dissemination are not trivial, and are equally critical to the success of this industry. But for now let’s consider some of applications that utilize information derived from this imagery.

The AUVSI report indicates a number of areas where drones are already being utilized, including: wildfire mapping, agricultural monitoring, disaster management, power line surveys, law enforcement, telecommunication, weather monitoring, aerial imaging/mapping, television and movies production, oil and gas exploration, freight transport, and environmental mapping. Similar application areas are also highlighted in informational material from Skybox Imaging and Planet Labs, as well as in discussions throughout the remote sensing industry.

To provide more specific examples, the following hypothetical applications were recently reported in an article on Skybox Imaging in Wired (06.18.13): “the number of cars in the parking lot of every Walmart in America; the number of fuel tankers on the roads of the three fastest-growing economic zones in China; the size of the slag heaps outside the largest gold mines in southern Africa; the rate at which the wattage along key stretches of the Ganges River is growing brighter.”

Other example applications include: lawn and vegetation greenness indices for marketing landscape maintenance; water surface conditions for commercial and recreational fishing; flooding and damage assessments for insurance claims; number of beach visitors for targeted advertising; crop health for precision agriculture and investment futures; and many more.

Even with these few examples we see a glimpse of the enormous economic potential for the growing remote sensing industry. A common theme throughout is the need to accurately and efficiently deliver information in a timely manner. To do so still requires the development and implementation of many new hardware and software solutions; however, in that regard there are also many opportunities. This is a significant time for remote sensing, and it will be exciting to see how the industry develops in the near future.

This is part 2 of a series on big data and remote sensing… visit part 1 here.

Big Data and Remote Sensing – Where does all this imagery fit into the picture?

There has been a lot of talk lately about “big data” and how the future of innovation and business success will be dominated by those best able to harness the information embedded in big data. So how does remote sensing play a role in this discussion?

We know remote sensing data is big. For example, the NASA Earth Observing System Data and Information System (EOSDIS), which includes multiple data centers distributed around the U.S., currently has more than 7.5 petabytes of archived imagery. Within the EROS data center alone there are over 3.5 million individual Landsat scenes totaling around 1 petabyte of data. And this is but a subset of all the past and currently operating remote sensing instruments. There are many more, particularly when considering the various international and commercial satellites, not to mention the array of classified military satellites and the many instruments yet to be launched. Remote sensing imagery therefore certainly satisfies the big data definition of size.

But what about information content? A significant aspect of the big data discussion is geared towards developing large-scale analytics to extract information and applying those results towards answering science questions, addressing societal needs, spurring further innovation, and enhancing business development. This is one of the key aspects – and challenges – of big data, i.e., not just improving the capacity to collect data but also developing the software, hardware and algorithms needed to store, analyze and interpret this data.

Remote sensing researchers have long been using remote sensing data to address localized science questions, such as assessing the amount of developed versus undeveloped land in a particular metropolitan area, or quantifying timber resources in a given forested area. Subsequently, as software and hardware capabilities for processing large volumes of imagery became more accessible, and image availability also increased, remote sensing correspondingly expanded to encompass regional and global scales, such as estimating vegetation biomass covering the Earth’s land surfaces, or measuring the sea surface temperatures of our oceans. With today’s processing capacity, this has been extended yet further to include investigations of large-scale dynamic processes, such as assessing global ecosystem shifts resulting from climate change, or improving the modeling of weather patterns and storm events around the world.

Additionally, consider the contribution remote sensing makes to the planning and development of transportation infrastructure in the northern hemisphere, where the opening of new trans-arctic shipping routes and changes to other existing high-latitude shipping routes are being predicted using models that depend on remote sensing data for input and/or validation. And also consider agricultural crop forecasting, which relies heavily on information and observations derived from remote sensing data, and can not only have economic impacts but also be used to indicate potential regions of economic and political instability resulting from insufficient food supplies.

Such examples, and others like them, represent a logical progression as research and applications keep pace with greater data availability and ongoing improvements in processing tools. But the field of remote sensing, and its associated data, is continuing to grow. What else can remote sensing tell us and how else can this immense volume of data be used? Are there relationships yet to be exploited that can be used to indicate consumer behavior and habits in certain markets? Are there geospatial patterns in population expansion that can be used to better predict future development and resource utilization?

There’s a world of imagery out there. What are your ideas on how to use it?