Dr. Walter Scott, DigitalGlobe
Dr. Walter Scott is the founder of DigitalGlobe and currently serves as Executive Vice President and Chief Technical Officer. He is responsible for DigitalGlobe’s Platform and Services Business Units, as well as space system acquisition. Scott holds a Bachelor of Arts in Applied Mathematics, magna cum laude, from Harvard College and a Doctorate and Master of Science in Computer Science from the University of California, Berkeley.
VADM Robert B. Murrett (Ret)
Robert B. Murrett is a professor on the faculty of the Maxwell School of Citizenship and Public Affairs at Syracuse University. Previously, Murrett was a career intelligence officer in the U.S. Navy, serving in assignments throughout the Pacific, Europe, and the Middle East through his thirty-four years of duty, retiring in the grade of Vice Admiral. For the last ten years, he served as Vice Director for Intelligence, U.S. Joint Chiefs of Staff, Director of Naval Intelligence, and Director of the National Geospatial-Intelligence Agency (NGA).
Lawrie Jordan, Esri
Lawrie Jordan is the Director of Imagery for Esri, as well as Special Assistant to Jack Dangermond, President of Esri. Mr. Jordan has more than 30 years of experience as a leader in the field of image processing and remote sensing, including a long standing strategic partnership with Esri. His background education is in Landscape Architecture, with degrees from the University of Georgia and Harvard University.
Attendees will glean knowledge and ideas from other successful real-world analytical applications, all while sitting in the beautiful surroundings of the Brown Palace Hotel & Spa.
Attendance for the EAS is being limited to 200 people in order to provide high-quality interaction and participation.
The theme of the 2017 ENVI Analytics Symposium (EAS) is “Analytical Solutions in a Data-Rich World.” With the staggering volume of commercial and open-source data that is becoming available, organizations will need to quickly transition to new business and service models to be successful. Agility, technology, and innovation will separate the winners from the losers. Register to attend the 2017 EAS to keep your finger on the pulse of this fast-growing and dynamic market of commercial geospatial Big Data analytics.
The ENVI Analytics Symposium is being held at the Brown Palace Hotel and Spa in Denver, CO. The Brown Palace is a Forbes 4 Star hotel and is a legend among Downtown Denver hotels. Brown Palace guests enjoy access to timeless luxury with a unique sense of place, original experiences and world-class service and amenities. There's simply no better way to experience the Mile High City.
Registration is limited, so don't wait 'til it's too late.
We have multiple pricing options to best fit your needs. Click below to get the details.
Erik Arvesen is vice president and
general manager of Geospatial Solutions
within Harris Corporation’s Space and
Intelligence Systems segment.
Space and Intelligence Systems offers
complete Earth observation, weather,
geospatial, space protection, and
intelligence solutions from advanced
sensors and payloads, ground
processing, and information analytics.
The Geospatial Solutions business unit
encompasses geospatial products, content
management, and Harris’ IntelliEarth™
commercial geospatial solutions business.
Prior to joining Harris, Arvesen was vice
president of Cloud and Data Services
for Trimble Navigation, where he led a
staff of 150 global employees, including
three technical teams and two successful
start-up businesses in emerging markets.
Previously he was vice president and
general manager of Trimble’s Geospatial
Solutions division and was responsible
for the business transition from
hardware and simple data collection
to software solutions to better meet
customers’ evolving needs.
Arvesen also held technical and
management roles at TDG Aerospace,
a start-up avionics company, and
Arvesen holds a bachelor of science
degree in electrical engineering
from the University of California, Los
Angeles and a master’s degree in
business administration from Santa
Ursa Space Systems
Julie Baker is Co-founder and VP of Operations at Ursa Space Systems. Julie has 30 years’ experience in the software industry, including 15 years in various software engineering roles and 15 years in technical management. Prior to co-founding Ursa Space Systems, she was VP of Cyber Technology at Architecture Technology Corporation where she provided technical leadership and management of the company's research and development in the areas of cyber security, information management and reliable computing. Julie holds a Master of Science in Computer Science from Stanford University and a Bachelor of Music from the University of Texas at Austin.
Dr. Ursula Benz
Dr. Ursula Benz, COO of CloudEO, started her career at DLR (German Aerospace Center) where she led research for
on-board SAR data analysis and compression. As Managing Director at Definiens Imaging she was building up and
driving the global geo-spatial business. At Geosystems, she was responsible for business development of innovative
Stuart Blundell is the Director of strategy and business development for geospatial solutions within Harris Corporation’s Space and Intelligence Systems segment. Space and Intelligence Systems offers complete Earth observation, weather, geospatial, space protection, and intelligence solutions from advanced sensors and payloads, ground processing, and information analytics. The Geospatial Solutions business unit encompasses geospatial products, content management and Harris’ IntelliEarth™ commercial geospatial solutions business.
Blundell joined Harris with the company’s acquisition of Exelis, where he most recently served as general manager and director for commercial product sales for Geospatial Intelligence Solutions (GIS). In this capacity, he managed world-wide sales of flagship commercial products such as ENVI, Jagwire and related software modules used in the exploitation and visualization of remote sensing data.
Before joining Harris, Blundell was the vice president of geospatial products and solutions at Textron Systems Overwatch where he oversaw product lines in support of the NGA System for Geospatial-Intelligence (NSG). Previously he co-founded Visual Learning Systems (VLS), a nationally recognized Small Business Innovative Research company.
Blundell has a bachelor’s degree in geophysical engineering from Montana Tech and a master’s degree in geology from the University of Wyoming.
Dr. Lawrence Buja
Dr. Lawrence Buja is the Director of Climate Science and Applications Program at the National Center for
Atmospheric Research (NCAR) in Boulder, Colorado, which carries out interdisciplinary research on social,
economic, and political activities related to climate at local, regional, and global scales. Previously, Dr. Buja was
the scientific project manager for NCAR’s Climate Change and Prediction group, a member of NCAR’s core
climate modeling development and application team, and is a contributing author to both the 2001 IPCC Third
Assessment Report and the Nobel Prize winning 2007 IPCC Fourth Assessment Report. Dr. Buja works closely
with the World Bank, the InterAmerican Development Bank and other international agencies, applying NCAR’s
climate and regional model expertise to help inform sustainable development investment strategies throughout
the world. Dr. Buja was also a co-author of the recent National Academies “Models of the World” report for NGA.
Dr. May Casterline
Dr. May Casterline is a data scientist/image scientist/software developer with a background in satellite and
airborne imaging systems. Her research interests include deep learning, hyperspectral and multispectral imaging,
innovative applications of machine learning approaches to remote sensing data, multimodal data fusion, data
workflow design, high performance computing applications, and creative software solutions to challenging
geospatial problems. She holds a PhD and Bachelors of Science in Imaging Science from Rochester Institute of
Technology, with a focus on remote sensing. In industry she has acted as a product owner, technical lead, lead
developer, and image scientist on both research initiatives and development projects.
John Corbett, Ph.D., agricultural climatologist and aWhere, Inc. Co-Founder and Chief Science Officer, focused his career on applied agricultural meteorology and a scalable, enterprise, agricultural intelligence platform. aWhere maintains a global resource of high-resolution, current, daily observed and forecast agronomic weather data for localized ‘smart content’ planet-wide. With 25+ years working in agriculture, John leads a team of software experts, agricultural scientists, and business leaders leveraging technology for actionable, timely, location specific information meeting needs across the agricultural value chain. Prior to aWhere, John worked with Syngenta-Switzerland, Texas A&M- USA; with ICRAF – Kenya; and with CIMMYT – Mexico.
Brian Curtiss is one of the founders of ASD, Inc. and serves as Chief Technical Officer. He has over 30 years’ experience in the field of spectroscopy and optical sensing and holds a B.A. in Earth and Planetary Sciences from Washington University in St. Louis and a M.S. and Ph.D. in Geochemistry from the University of Washington. As a post-doctoral research fellow at CalTech, he assisted in the development of the field portable spectroscopic instrumentation. Prior to joining ASD, he held a research faculty position at the University of Colorado in Boulder. After co-foundering ASD Inc. in 1990, Dr. Curtiss served as principal investigator on seven NASA, NSF and DOE funded research projects. In his current position as ASD’s Chief Technical Officer, Dr. Curtiss applies his experience in the fields of spectroscopy and optical imaging to a diverse range of analytical problems in the natural resource industries.
Pieter Decker spent 25 years working designing, delivering, operating, and evolving our nations reconnaissance
systems. He is a known innovator with a number of successes in his portfolio. Since joining Harris Corporation
in June of 2015, he has relentlessly pursued automation and integration, partnering with small companies to
John has over 40 years of experience establishing enterprise architectures with video broadcast solutions, networking, asset management, video production, and geospatial enterprise systems. He was the chief architect for Harris platform solutions which have been deployed across the DOD and IC. He is currently the Co-Chair for the USGIF ABI Working Group.
John has extensive experience in cloud computing having been instrumental in the architecture of Harris H10 Multi-Domain Cloud Enterprise Architecture which leverages OGC Rest and SOAP services. He is also leading Harris Next Generation of Geospatial Enterprise solutions which will enable multi-source discovery, provide a commercial analytics marketplace, and model driven analysis platform.
Previous to joining Harris Geospatial business John was the Chief Strategy and Technology officer for Harris Commercial Broadcast Division. Throughout his career he led efforts to build the world’s first Digital AM and FM Radio systems, Digital Television, IP Video networks and implemented Harris Cross Platform Advertising Campaign Management Platform. He pioneered Harris FAMEtm Geospatial Digital Asset Management System, among the first digital geospatial video content management data models. He is also considered a leading expert in CDN distribution architectures, video encoding, video analytics, video networks and modern geospatial enterprises.
John is well known as a speaker on emerging technologies. He holds a BSEE in RF Engineering and BSEE in Broadcast Engineering, is a Graduate of Darden UV Executive Business Innovation Program, Graduate of Kellogg Executive Management Program.
Michael Ehrlich is a Senior Product Manager
at Harris Corporation in Space and Intelligence
Systems working within Geospatial Solutions.
Michael has been focused during the last 10
years on building geospatial products and
solutions for the Unmanned Aerial Systems
(UAS), Remote Sensing and Geospatial Intelligence (GEOINT)
communities with an emphasis on processing, discovery,
dissemination, and exploitation of complex data types. Michael’s
role within Harris Geospatial has most recently grown to include
leadership in the rapidly expanding deep learning initiatives as
well as advanced analytic platforms and solutions.
Lawrie Jordan is Director of Imagery and Remote Sensing for Esri, as well as Special Assistant to Esri founder and President, Jack Dangermond. Mr. Jordan has over 35 years of experience as a leader in the field of image processing and remote sensing, and played a key role in evolving a long standing strategic partnership with Esri. His background education is in Landscape Architecture, with degrees from The University of Georgia and Harvard University.
Lawrie is a member of the European Academy of Sciences and Arts, as well as the recipient of the Geospatial World Leadership Lifetime Achievement Award for his decades of contribution in the field of Image Processing and Earth Observation. He is also grateful to be the recipient of the U.S Government’s medal for Outstanding Support and Patriotism.
Nazlin Kanji is a Product Line Director at AeroVironment. She has more than 20 years of experience developing and deploying big data systems for the DoD and commercial industry, and is now leading AeroVironment’s commercial data programs focusing on agriculture, utilities, transportation and energy. She was the program manager on the first FAA-approved commercial unmanned aircraft operations over land and water in the North Slope region and had the pleasure of spending her summer in the Arctic supporting the operations. She has a BS in Computer Science from California State University, Northridge and earned an MBA at California Lutheran University.
Amazon Web Services
Mark Korver is the Geospatial Lead on the Specialist Team at Amazon Web Services (AWS). He has ten years of
experience building cloud solutions both as a customer and employee of AWS. Having founded companies with a
geospatial focus, Mark is comfortable speaking about both business development and technical architecture. Prior
to joining Amazon, Mark was CTO/Founder at SpatialCloud LLC, a geo-services startup running on AWS. Mark
holds a Master in City Planning from MIT with a specialization in Technology Transfer as it applies to international
development projects and is a native speaker of Japanese.
Rebecca Lasica is the Sr. Solutions Engineer Manager at Harris Corporation and has been immersed in software and remote sensing science for more than ten years. She is a University of MN alumni with industry expertise focused on satellite, airborne, and UAS image analytics.
Robert Laudati is the Managing Director of Commercial Products & Solutions at Harris Geospatial Solutions, responsible for the management of Harris’ portfolio of commercial geospatial offerings worldwide. Mr. Laudati has over twenty five years of experience in geospatial technology across a wide range of industries and organizations. Before joining Harris, he held business and technical leadership positions at Synchronoss Technologies Inc., Trimble Navigation Ltd., Autodesk, and GE Digital Energy. Mr. Laudati is a graduate of Brown University and Stanford University, and holds an MBA from the University of Denver. He currently serves as Harris’ representative to the OGC Planning Committee.
Daniela Moody Ph.D.
Daniela’s work at Descartes Labs focuses on developing improved feature extraction algorithms for multispectral satellite imagery that combine sensor fusion, adaptive signal processing, and machine learning techniques. She was at Los Alamos National Laboratory for 9 years prior to joining Descartes Labs, working on remote sensing and machine learning applications in various research areas, including space systems, astronomy, and nuclear non-proliferation. She received her M.S and Ph.D. in Electrical Engineering from the University of Maryland, College Park in 2012.
Robert B. Murrett
Robert B. Murrett is a professor on the faculty of the Maxwell School of Citizenship and Public Affairs at Syracuse University, and serves as the Deputy Director of the Institute for National Security and Counterterrorism (INSCT) at the University. He is also a member of the Board for the Institute for Veterans and Military Families, and is responsible for a series of ongoing research projects between the University and the Syracuse Veterans Administration Medical Center. He is on the adjunct staff of the RAND Corporation, the Institute for Defense Analyses, and chairs the MITRE Intelligence Advisory Board.
Previously, Murrett was a career intelligence officer in the U.S. Navy, serving in assignments throughout the Pacific, Europe, and the Middle East through his thirty-four years of duty, retiring in the grade of Vice Admiral. His duty stations included service as Operational Intelligence Officer for the U.S. Pacific Fleet, Assistant Naval Attaché at the U.S. Embassy in Oslo, Norway, and Director for Intelligence, U.S. Joint Forces Command. For the last ten years, he served as Vice Director for Intelligence, U.S. Joint Chiefs of Staff, Director of Naval Intelligence, and Director of the National Geospatial-Intelligence Agency (NGA). He holds an undergraduate degree from the University of Buffalo, and a masters degree from the Walsh School of Foreign Service at Georgetown University.
Paolo has been enjoying the last 25 years investigating the many aspects of extracting useful and reliable information from Synthetic Aperture RADAR imagery, developing algorithms and exploring different applications. After realizing in his years in the academia at Politecnico di Milano and University of Zurich that these goals are not just dreams, he co-founded sarmap to bring this experience into operation, leading the development of the SARscape software package.
Jesse Piburn is data scientist in the Computational Sciences and Engineering Division at Oak Ridge National
Laboratory. His work includes research and development in spatiotemporal analytics, data mining, and machine
learning. As a member of the Geographic Data Sciences team at ORNL for the past four years, he has had the
opportunity to work with multiple IC and DOD partners to provide innovative, scalable, and robust solutions
for cross-disciplinary applications across the GEOINT domain. Jesse has a background in spatial statistics and
geographic information science and an Masters of Science in Geography from the University of Tennessee.
Pedro Rodriguez is a Solutions Engineer at
Harris Geospatial Solutions with nine years
of professional experience. Previously, he
supported the DoD and IC as a Systems
Engineer and as an in-country FSR in
Afghanistan working directly with data
managers and image analysts during Operation Enduring Freedom.
Pedro has a BS in Electrical Engineering from the University of
Puerto Rico – Mayaguez, and is pursuing a MS in Systems
Engineering from Stevens Institute of Technology. He is a licensed
Professional Engineer (PE) and an INCOSE Certified Systems
Engineering Professional (CSEP). He is passionate about cutting-edge
technology in geospatial analytics, specifically in cloud computing
and deep learning, which will be critical to analyze large volumes
of data to solve national security problems.
Mark E. Romano
In his capacity as the Sr. Product Manager for the Harris Geospatial Solutions Division, Mr. Romano is responsible for commercialization of Geiger mode LiDAR and other space, air, land, and sea remote sensing capabilities and services. Mark has an extensive background with 30+ years’ experience working with defense, Fed/civil, and commercial communities as a recognized industry expert, leading development of innovative and disruptive remote sensing technologies. He has authored and co-authored numerous papers, journals, text books, and specifications for government and industry with active participation in panels and committees as a subject matter expert.
Dr. Walter S. Scott
As Executive Vice President and Chief Technical Officer of DigitalGlobe, Dr. Scott oversees the development of space systems, R&D, and DigitalGlobe’s Platform and Services Business Units.
Dr. Scott founded DigitalGlobe in 1992 as WorldView Imaging Corporation, which was the first company to receive a high resolution commercial remote sensing license from the U.S. Government (in 1993), under the 1992 Land Remote Sensing Policy Act. WorldView became EarthWatch Incorporated in 1995. Dr. Scott managed the development of all of the company’s commercial remote sensing satellites. He secured the first-ever export license for launch of U.S.-manufactured imaging spacecraft on Russian launch vehicles (Start-1 and Cosmos). The company became DigitalGlobe in 2001, and with the launch of the QuickBird-2 satellite that year, offered the world’s highest resolution commercial satellite imagery. Today, DigitalGlobe operates a 5-satellite imaging constellation with the best revisit and greatest capacity in the industry.
From 1986 through 1992, Dr. Scott was with Lawrence Livermore National Laboratory (LLNL). He began as Project Leader for Computer Aided Design Tools for the Laser Pantography Program, developing tools to aid in the design of wafer scale integrated circuits manufactured. In 1987, he joined a small team developing a concept for a highly distributed constellation of space based interceptors for the Strategic Defense Initiative, known as “Brilliant Pebbles.” In late 1987, Dr. Scott became Program Leader for this effort, responsible for creating a series of hardware prototypes and conducting flight experiments. During 1989, Dr. Scott led the program successfully through over 20 reviews of technical feasibility, system performance, military operability, and estimated cost, resulting in the adoption of Brilliant Pebbles for SDIO’s space segment in 1990. In late 1991, Dr. Scott was Assistant Associate Director of the Physics Department and was responsible for development of new space-related programs and identification of promising technologies.
Prior to joining LLNL, Dr. Scott founded and served as president of Scott Consulting, a UNIX systems and applications consulting firm. He developed Unix networking subsystems, and a pioneering email system that used public key encryption for message protection.
Dr. Scott holds a Bachelor of Arts in Applied Mathematics, magna cum laude, from Harvard College and a Doctorate and Master of Science in Computer Science from the University of California, Berkeley. He was a visiting student for a year at Edinburgh University in Scotland.
Dr. Scott was named Entrepreneur of the Year by Ernst & Young in 2004 for the Rocky Mountain Region in the Emerging Technology category.
He previously served on the National Research Council’s Committee on Earth Science and Applications from Space (CESAS) and is currently member of the board of directors of the Open Geospatial Consortium (OGC).
Alex Shih is Director of Product & Ecosystem at Planet. Planet designs and manufactures miniature satellites with the mission to image the entire world every day, and make global change visible, accessible, and actionable.
He brings experience from the SaaS, cloud, and mobile space, having previously led mobile partner products at Twitter and helped launch the enterprise partner program at Google for Google Apps.
Alex has degrees from MIT and Cornell University.
Ian Spence has over 25 years’ experience in the geospatial industry and leads Spacemetric’s satellite business sector,
which provides sensor data management and processing solutions to imaging satellite manufacturers, operators
and data distributors. He began his career in data processing development and user liaison for the ERS-1 radar
satellite, including a period at the European Space Agency, Italy. He then held commercial roles at the Swedish
Space Corporation and Airbus Defence & Space/Infoterra UK. Ian holds a Master of Science in Remote Sensing
from University College London and a Bachelors degree in Physics and Geology from Durham University.
Nicolas Stussi is Vice President, Business Development for the Intelligence division of Airbus Defence and
Space. Nicolas has over 20 years of experience in the satellite and geo-spatial information industry. He
is based in Silicon Valley, and leads the New Business team at Airbus, Intelligence, focusing on emerging
market trends and technologies. He is playing a key role in defining the go-to-market strategy for Airbus’
next generation of satellite assets and downstream services.
Dr. Robert Sundberg
Dr. Sundberg is President of Spectral Sciences, Inc. and previously served as the Vice President of Technology
Development (2011- 2002) and the Group Leader of Detection and Discrimination Group (2002-1998). He has
been involved in both the management and technical aspects of theoretical and data analysis projects. His
present research activities include: the development of hyperspectral scene simulation models; target detection and
identification algorithms; rapid real-time IR target imaging models; high-temperature optical models for hypersonic
vehicle ablation products; high-resolution line-by-line radiation transport models for calculating non-equilibrium
infrared vacuum core plume radiation; and, modeling of atmospheric infrared radiance phenomena.
MDA Information Systems
Dr. Douglas S. Way is Chief Scientist, MDA Information Systems Geospatial Solutions and Professor Emeritus at The Ohio State University. Prior to joining MDA Federal in 2004, Dr. Way was Professor and Department Chair at the Knowlton School of Architecture, Ohio State University and was previously Professor at the Harvard Graduate School of Design, Harvard University. His over 45 years of research and professional practice has focused upon remote sensing and geographic information systems spatial modeling applied to land use change dynamics and a wide variety of environmental and strategic issues related to U.S. national security. Dr. Way earned his B.S. at the University of Wisconsin, M.A at Harvard University and M.A. and PhD. in geography-geomorphology at Clark University and is author of the text Terrain Analysis.
University of California, Santa Barbara
Erin Wetherley is a doctoral candidate in the Geography Department at the University of California, Santa Barbara. Her work with Drs. Dar Roberts and Joe McFadden focuses on characterizing urban climate variability using imaging spectrometry, thermal imagery, climate modeling, and sub-pixel analyses. Additional research interests include mapping post-fire landscape recovery and measuring the spectral characteristics of vegetation drought response. Prior to her doctoral work, Erin earned a bachelors degree in Environmental Studies from Brown University, and worked for several years as a GIS and database manager at a Washington, D.C. non-profit organization.
Nicolas Stussi is Vice President, Business Development for the Intelligence division of Airbus Defence and Space. Nicolas has over 20 years of experience in the satellite and geo-spatial information industry. He is based in Silicon Valley, and leads the New Business team at Airbus, Intelligence, focusing on emerging market trends and technologies. He is playing a key role in defining the go-to-market strategy for Airbus’ next generation of satellite assets and downstream services.
Click here to view workshop titles and abstracts
Improving Outcomes with UAV and Airborne Data
Over the years, Harris Geospatial has worked with many customers that use data collected on UAV and airborne platforms. This session will dive into lessons we’ve learned with regard to:
Applied Machine Learning
Recently, “Machine Learning” has been the focus of many conversations in the remote sensing community. However, Machine Learning has had varying degrees of quality, testing, and ultimately results. Harris has developed a Machine Learning solution that is mature, deployable, and capable of scaling for large projects across modalities including multispectral, hyperspectral, and LiDAR. In this workshop, high-level principals of Machine Learning will be discussed and Machine Learning will be shown to be a leap over traditional pixel-based analytics for some features and data. Several use cases will be presented and there will be discussions about how you can take advantage of this technology.
Deploying to Partner Platforms
Harris is proud to partner with many of the leading data and platform providers who are important contributors to our industry as a whole. These partnerships enable us to deploy analytics in close proximity to the data, and expose them to user bases across several different industries. In this workshop, Harris will present several deployments of enterprise geospatial analytics on various partner platforms. This will be an engaging session where attendees will gain technical insight into how these analytics are deployed with hands-on opportunities to interact with the platforms.
Vegetation Analysis: Why it’s Hard and What You Can Do
Remote sensing of vegetation has been around for as long as remote sensing, but many are still confounded on how to observe vegetation condition, species, and change. This workshop will give a background on vegetation remote sensing, how to improve outcomes for observation, and modalities for best observing vegetation phenomenology. The new ENVI Crop Science product will be presented and there will be time for Q&A with vegetation experts from Harris.
Data Modalities, Sources, and Achieving the Best Results
Today, there is more data than ever before, and it is critical to derive meaningful and actionable information from this data. In this workshop, Harris will discuss recent data modalities that are now available such as small sats, weather sensors, and emerging commercial platforms. Some of these data are already available in cloud storage and delivery environments. We’ll show you how to ingest, work very large datasets efficiently, and describe potential best applications for the different sensors. This workshop will also discuss potential applications and delivery of machine learning.
Real-time Problem Solving for the Enterprise and Desktop
Bring your problem solving skills and geospatial expertise to this workshop for some hands-on ENVI analytics fun. Come ready to get creative and solve a real geospatial remote sensing problem, complete with access to data and ENVI tasks and workflows. Attendees should be somewhat familiar with remote sensing phenomenology and/or optical image analytics. Advanced users will have access to all the tools needed to solve these problems.The sky’s the limit.
Click on a title and speaker to get a more in-depth abstract of each presentation.
SESSION 1 : THE FUTURE OF EARTH OBSERVATION
Dr. Scott will speak about advances in cloud computing, automation and crowdsourcing that are enabling us to take full advantage
of the ever-increasing amount of geospatial data that is becoming available, and making the benefits accessible to a much
This presentation will discuss rapidly emerging trends in Earth
Observation and remote sensing in the context of a new generation
of users and consumers. Specifically, it will address major changes
in traditional workflows (i.e. dynamic versus static) as well as the
evolving profiles of industry market segments and the personas of
the professionals who represent them. This presentation will also
investigate the implications of these evolutionary trends on the
software tool developers, and the importance of continuous
innovation that delivers value and simplicity to an increasingly
digitally aware global society with near real-time expectations.
Airbus is a global leader in aeronautics, space, and related services. In this session, new insights will be discussed on plans to build,
launch, and operate a new set of imagery assets (both satellite and airborne platforms) from 2019 and beyond. These unique assets
will deliver state-of-the-art capabilities and push the boundaries in terms of monitoring and persistence services to address both
commercial and government market segments. Airbus continues to leverage and expand its portfolio to develop cutting-edge
technology and services to deliver customized imaging capabilities to its customers.
Planet designs, builds, and operates the world’s largest constellation of Earth-imaging satellites with the mission to image the entire
planet, every day, and make global change visible, accessible, and actionable. This year alone, Planet has launched 136 satellites,
bringing the total close to 200 satellites. Planet has created a global, automated satellite-to-software platform operation. The Planet
Platform today enables a simpler, faster, more powerful approach to handling large volumes of data from Planet’s own satellites and
a variety of other imagery providers. This presentation will dive into Planet’s expanding operational capacity and platform capabilities
– enabling cloud-first, scalable, machine learning, and computer vision analytics on imagery. Planet’s goal is to enable a community to
uncover new insights and actionable information from a unique view of the entire world every single day.
SESSION 2 : COMMERCIAL ANALYTIC PLATFORMS
It is our passion to not only make GeoServices successful in the market, but also MicroGeoServices, as we believe they both
are key to everyone benefitting from the wealth of Earth Observation data – or any type of geodata. Everything starts with
professionalism and ends in automation, with API-based access to imagery, analytics to retrieve the information from the images, and
accounting, metering, and revenue share with all contributors. This includes profound development of analytics, demand-focused
product design, reliable production, and service availability secured through the means of modern software and IT infrastructures.
And nothing works without easy access to those services for customers – easy in terms of technical access as well as in terms of legal
and pricing models. CloudEO has a 360° view. We help our partners through the entire process from development to successful online
sales. We understand the need of individual solutions, of manual steps in the production flow, and the demand of customer and
partner consultancy. But, we never stop looking at how we can make things faster and more affordable, both by automation, and by
taking away whatever overhead we can through the opportunities of our unique GeoMarketplace.
It’s well known that data must be well-curated to be useful. Getting access to, then preparing data is a taxing part of data science,
and is often a majority of the work. We also know that without access to both data and code that underlie scientific discoveries,
findings are difficult if not impossible to reproduce. When this work is done on-prem, the same big-data work is done repetitively,
and typically stays silo’d, the results remaining inaccessible to others. In contrast, the same work done in the cloud, can be securely
provisioned to anybody in the world regardless of their infrastructure. Other than a thin-client, tablet, or notebook, local hardware
is not required. In addition, data in the cloud sits right next to any amount of on-demand compute needed to extract value from
it. That compute can be run by the data owner, or others that the owner chooses to share data with. This talk will introduce the
Earth on AWS collection and take a peek at the simple, serverless methods that were used to process cloud-optimized GeoTIFFs for
the USDA NAIP data, supporting in-situ use of CONUS NAIP by anyone.
As we consider the future of geospatial intelligence, traditional (non-commercial) sensing sources only provide a portion of the intelligence information that is currently available. This is increasing the reliance on commercial data and OSINT providers to fill the void. Getting insights from satellite, aerial and OSINT data is harder than it should be due to a lack of interoperability. Critical challenges like monitoring threats, food availability, water resources, and sustainable urban and industrial systems depend on a commercial and OSINT data sources. The challenge is that these key data assets are not interoperable making them not easily discoverable or analytics-ready, leaving critical questions unanswered. This session will explore the role of supply chain management as an enabler to the future of automated production.
SESSION 3 : THE BUSINESS OF GEOSPATIAL ANALYTICS
The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We will present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information that scale with the high-rate and dimensionality of imagery being collected. We will focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready multi-sensor data platform enables quick prototyping of various satellite imagery analysis algorithms.
Over 80% of countries do not provide any official reporting of economic activity and multiple reports coming out of some countries, such as China, can sometimes imply conflicting results. This talk will cover how remote sensing and geospatial analytics can fill this gap for industry applications in the financial and energy sectors. Through access, aggregation, and analytics, Ursa is the first to deliver reliable weekly reports of 77% of China’s crude oil inventories. Ursa uses synthetic aperture radar (SAR) to deliver its timely reports and has access to all the world’s commercial SAR satellites. Aggregation of multiple satellites gives Ursa the ability to be SAR sensor-agnostic, creating a virtual constellation with a revisit rate of up to twice a day. Ursa’s image processing experts have developed geospatial analytics to work on multiple formats, multiple incidence angles, and multiple resolutions. Additional, proprietary research is incorporated to provide context, such as tank owner and storage type, for analytics results. Example use cases, such as macro-economic analysis, currency, and stock prediction, as well as other financial applications, will be presented. Data sources that provide reliable global economic intelligence are disrupting traditional energy and commodities paradigms.
Increased weather variability driven by a warming atmosphere impacts food production. Human security in some areas is already showing resource constraint pressure and this will only grow more intense. Monitoring agricultural production provides detailed localized information suitable to inform crises intervention efforts and optimize and target appropriate interventions.
Today, industry solutions that use remote sensing technologies span needs for multiple data sources, large infrastructure, and
fit-for-purpose analytics. Usually there are many moving parts to these solutions such that each part must fit seamlessly together
making the delivery of information seem effortless. When that happens, energy and focus can shift to interpreting answers and
developing action plans. See some examples of end-to-end industry solutions where workflow complexities are automated
making it possible to deliver only the information and answers that are relevant to emerging markets within our industry.
SESSION 4 : ANALYTIC INNOVATIONS AND REMOTE SENSING
The growing concentration of the global human population into cities has coincided with increasingly rich data from smart environments, social sensing, and the Internet of things. Fusing these data with maps of the built environment and urban vegetation has enormous potential to quantify urban energy and water use, improve urban planning, and target public health initiatives. Currently, fine spatial resolution imagery is prized for mapping urban materials because it can identify object edges. Yet this imagery doesn’t have enough spectral bands to discriminate important differences between urban materials, and it doesn’t provide global coverage. Near-future orbital imaging spectrometer missions could revolutionize our understanding of urban environments, measuring hundreds of reflected wavelengths from the visible through the shortwave infrared. However, these platforms will have pixel sizes > 30 meters, which means we need to develop methods to extract urban surface information at sub-pixel scales. I will present new results in which we used airborne imaging spectrometry to extract fractional estimates of key urban surface classes and urban vegetation condition, obtaining robust estimates across spatial scales. When such data become globally available from satellite platforms, there will be increasing opportunities to produce spatially explicit value-added products for utilities, municipalities, and green technologies.
Use of automated remote sensing techniques to map forest cover is important when modeling environmental quality. However, identifying forest cover with multispectral imagery (MSI) often results in confusion caused by similar spectral profiles between forest and other vegetation. Previous research in forest mapping has included integration of hyperspectral imagery and LiDAR data for tree detection and use of MSI to distinguish tree crowns from non-vegetated features. Since these sources are not widely available to most practitioners, a method was created to discriminate between forest and other land covers using commercial MSI. This research discusses two indices, the Forest Cover Index 1 and Forest Cover Index 2, which were developed to model forest in WorldView-2 satellite imagery of the Beltsville Agricultural Research Center in Maryland. The study site included mixed forest, agriculture, other vegetation, urban features, soil, and water. The tree cover indices exploited the product of either reflectance in red and red edge bands or the product of reflectance in red and near infrared bands. For two classes (trees vs. all other), overall classification accuracy was >85% for the four images that were acquired throughout the year.
This presentation will discuss recent improvements made to the Monte Carlo Scene (MCScene) code to enable low light situations
where the sun is near or below the horizon. MCScene is a high-fidelity model for full optical spectrum (UV through LWIR)
hyperspectral image or multispectral image geospatial simulation. MCScene provides an accurate, robust, and efficient means
to generate spectral scenes for algorithm validation. MCScene utilizes a Direct Simulation Monte Carlo (DSMC) approach for
modeling 3D atmospheric radiative transfer including full treatment of molecular absorption and Rayleigh scattering, aerosol
absorption and scattering, and multiple scattering and adjacency effects, as well as scattering from spatially inhomogeneous
surfaces, including surface bidirectional reflectance distribution function (BRDF) effects. The model includes treatment of land
and ocean surfaces, 3D terrain, 3D surface objects, and effects of finite clouds with surface shadowing. This session will provide
a brief overview of how real-time elements are incorporated into the Monte Carlo engine, and will also discuss the recent
additional of a polygonal earth cross-section (PEX) model which allows for long atmospheric path simulations such as those
found under twilight conditions and highly off-nadir or near horizontal viewing geometries.
SESSION 1 : ADVANCES IN GEOINT TRADECRAFT - GEOSPATIAL MODELING
This presentation deals with global security challenges in the present day, as well as projections for U.S. and allied nations’ responses
to ongoing developments throughout the globe. It provides an overview of geographic and transnational trends, including implications
for both government and industry. All of this is viewed with an emphasis on GEOINT matters, in response to evolving resource
decisions, operations, and strategy.
The most valuable resource in the world is no longer oil, it’s data. Like oil, data in its raw form is valuable not for what it is, but
what we can turn it into. For geospatial intelligence, data and predictive analytics can facilitate an increase in situational awareness
and allow analyst to have access to more information than ever before, but it is no panacea. Along with solutions it brings with
it new issues we must contend with as a tradecraft. Predictive analytics is an extraordinarily powerful tool to help us find new
answers. But, how do make sure we are asking the right questions?
Digital Elevation Models (DEM), regardless of origin and resolution, provide information on terrain elevation but applications require transforms to support analyses. Dr. Way has developed a suite of terrain concepts and models that can be applied to a wide range of applications from finding Karez features in the Middle East (utilizing 1 meter data), to quantifying the ability of the terrain to “hide” equipment or personnel. This presentation will summarize the geospatial concepts used to determine relative relief, terrain complexity (texture), terrain slope characterization, terrain slope characterization (uplands/lowlands), and terrain slope characterization (valleys), will be presented. A number of applications of these products will be shown including off-road vehicle mobility, generation of soil mapping, identifying potential sources of construction materials, ambush opportunity, and aerial concealment.
We have become planetary managers of a globally interconnected world. In this big data era, as we evolve from a data-scarce
to a data-rich world, remote sensing, modeling and data analytics at scale are transforming how environmental science is used
to understand and simulate the world. These models and data don’t stand alone, but rather exist in an environment of human
networks, decisions, and events that are critical for understanding the structure & dynamics of our complex coupled human/natural
systems. The decades of experience that the science community has with large-scale observational and numerical data analytics
sets the stage for a next generation of coupled socieo-enviro-technical models. From the emergence and spread of vector-borne
diseases, to assessments of globally networked insurance, commodity and supply-chain risk, to climate forced social instabilities
and migration, these next generation models will create the actionable data, information and knowledge products needed for
economic, environmental and national security decision making.
SESSION 2 : MACHINE LEARNING AT SCALE
The evolution of GPU technology has fueled breakthroughs in artificial intelligence. In particular, deep learning has powered innovations in language translation, image search, and driverless cars. Paired with the development of deep learning frameworks and software providers that integrate with NVIDIA’s CUDA platform, the technology has become more accessible to traditional researchers outside the computer science discipline. The result has been massive gains in automation while reducing the compute footprint and infrastructure. At the heart of deep learning approaches is a data-driven methodology to learning the patterns in large corpuses of information. While remote sensing data has always been ‘big data’, the amount of data that analysts and researchers will need to consume will only grow with the introduction of commercial satellite providers. The traditional exploitation algorithms of remote sensing data have relied on engineered, statistical approaches that require domain expertise to implement and deploy. These techniques have proven effective in the environments for which they were designed, however scale, access to domain expertise, and lack of model transferability remain challenges. The integration of deep learning techniques, and GPUs to power them, into GEOINT exploitation offers an exciting and tractable solution to automating some of the most challenging problems facing the community.
Harris Geospatial has long been recognized as a leader in the
remote sensing industry and on the forefront of innovation in
imagery analytics. A new deep learning initiative at Harris called
“MEGA”, continues that tradition. This presentation introduces
MEGA and describes why it is a unique and innovative approach to
applying deep learning to remotely sensed data. An overview of the
problem space being addressed and focus areas for MEGA will be
presented, along with a summary of the next set of challenges and
opportunities. Finally, Harris’ strategy and vision for evolving deep
learning as a critical solution for GEOINT analysis will be shared.
This presentation will review the application of deep learning
technology and techniques to automatically extract objects and
features from geospatial intelligence data sources including
high-resolution RGB and Pan imagery, high revisit rate imagery,
LiDAR point clouds and products, mosaics from drone imagery,
and full motion video.
SESSION 3 : INDUSTRY SOLUTIONS AND GEOSPATIAL ANALYTICS
A key challenge for all defence operations is the provision of timely and accurate intelligence to support decision making and improve situational awareness. With the availability of Intelligence, Surveillance, Target, Acquisition and Reconnaissance (ISTAR) assets growing, there are increasing volumes of data being collected. Today, the extraction of imagery intelligence (IMINT) still relies largely on its manual inspection by experienced analysts. This has led to the problem of data deluge where the flow of imagery can often overwhelm the capacity of the analysts.
In this talk we will describe the work done by the UK Defence Science and Technology Laboratory (Dstl) and Harris in developing an enterprise framework to extract content (geometries, objects and states) from multi-source image data. With Harris’ Geospatial Services Framework (GSF) at its core, the system will record these observations, allowing analysts to easily assess and visualise activities, changes over time, patterns and anomalies relating to targets of interest.
Operating with the highest levels of efficiency, reliability and safety is a top priority for utilities. The growth of distributed generation and diversification of power sources bring operational system challenges and an aging infrastructure and workforce is driving the need for asset renewal prioritization and knowledge capture. Using the combination of condition-based maintenance and predictive maintenance, utilities can effectively overcome these challenges and remain relevant in the changing energy marketplace. Incorporating the use of drones in an intelligent, condition-based, asset management program will provide utilities with the information needed to operate more efficiently, effectively, and safely, consequently allowing them to overcome some of these disruptive obstacles. Utilizing data collected from drones will lead to reduced truck roll outs and ensure the right assets and skill sets are deployed. Additionally predictive maintenance utilizing drones ensures assets remain in working order, reducing failures in the grid, especially where a potential asset failure could result in significant damage. The addition of drone data in the utilities industry has the potential to revolutionize the industry.
We will demonstrate how to use field reflectance spectra, collected for materials such as vegetation, as input into calibration models that can be applied to map quantitative information in hyperspectral images. For example, quantitative results from using this technique for vegetation can provide information about leaf chemical properties like canopy nitrogen and lignin content. The resulting calibrations for vegetation properties produced using this method can then be mapped to hyperspectral images. Indices like NDVI are useful, but they lack the ability to give detailed information on physiological processes, so this technique takes image analysis a step further. This type of analysis can be very important in many different applications in areas like precision agriculture, forestry, environmental monitoring, mining and defense and intelligence.
This session will look at how commercial Geiger-mode
technology differs from existing LiDAR systems and what it
means to the future of our industry. The presentation will
include a technology overview with current and future
applications as well as real project examples.
SESSION 4 : ADDING THE TEMPORAL DIMENSION TO GEOSPATIAL ANALYTICS
The possibility of providing, for any time and location in the world, operational services based on Earth Observation (EO) data very often faces very simple but fundamental issue: data availability in an affordable, timely and consistent manner. The Sentinel-1 constellation represents a solution. First, because SAR technology ensures all-time and all-weather acquisition capabilities, the Sentinal-1 has been designed to guarantee consistent coverage for any location in the world, with an average repeat between 6 and 12 days. Next, Sentinel-1 data are downloadable free of charge via a web interface and API. These data are hence ideal to build services that can be operated not only on-demand scheme, but on a routinely basis, for mapping as well as monitoring. Examples will be shown of different operational applications and services based on Sentinel-1 data, built on enterprise-level COTS software tools interfacing directly with the data archive. Finally, the complementarity of a Sentinel-1 based approach with data from other (very-high resolution) SAR as well as optical missions will also be discussed.
Easy access to a regular supply of free satellite imagery is enabling a range of new services based on monitoring and change detection. We will describe how generic products from Sentinel-2 are being used to plan follow-up actions for more detailed data (satellite and UAV) and on-site inspection in local government and forestry organizations. We will also explain how satellite imagery is made analytics-ready through the creation of Precision Datacubes; stacks of accurately co-registered data provide quality change information with minimal artifacts that allow limited resources to be used in an optimal way by significantly reducing false alarms.
Data integration and reduction is the biggest technical challenge and opportunity of our age. Our approach to consumption
and integration is almost entirely manual, forcing people to find, analyze, and correlate data. Unstructured data offers the
biggest challenge and must be indexed automatically, at scale, when created, and at machine speeds. Probabilistic data modeling
enables us to leverage low-specificity/low-sensitivity indicators to produce high-specificity/high-sensitivity insights by linking
large volumes of data from multiple sources. There are five basic steps needed to achieve automated integrated predictive data
models: Automatically index the content of all data; correlate data sources; develop models; develop conditional responses to
collection, action, and analysis; and, evolve. The tools to do this exist today, are ready for use, and can help us begin to understand
and use our data to its fullest potential. The culmination will be entirely new approaches to data.
The ENVI Analytics Symposium is being held at the Brown Palace Hotel and Spa in Denver, CO. The Brown Palace is a Forbes 4 Star hotel and is a legend among Downtown Denver hotels.
Guests enjoy access to timeless luxury with a unique sense of place, original experiences and world-class service and amenities. There's simply no better way to experience the Mile High City.
Discounted pricing for the ENVI Analytics Symposium is no longer available. For current rates, please check the Brown Palace Hotel & Spa Website.
There are a variety of ways you can get from DIA to the Brown Palace:
Super Shuttle provides transportation from the airport for $25 per person one way and $46 round trip. To make arrangements with Super Shuttle, call 1-800-BLUE-VAN. You can also visit their website: www.supershuttle.com.
A one-way taxi ride from the airport to The Brown Palace is approximately $75.
We would like to thank the following sponsors for their support of the 2017 ENVI Analytics Symposium:
Esri, the leader in geospatial technology, offers imagery tools and content to see the world, find the patterns and share with others. Esri’s ArcGIS platform includes means to manage and serve large collections of imagery for use in ArcGIS and other software such as ENVI. ArcGIS Online provides access to large collections of imagery such as Landsat GLS collection, as well as global elevation datasets.
Sharing data on Amazon Web Services (AWS) makes it accessible to a large and growing community of users who use the AWS cloud for research, new product development, and education. When data is shared in the cloud, anyone can analyze it without having to download it or store it themselves, which lowers the cost of new product development, reduces the time to scientific discovery, and accelerates innovation.
Planet designs, builds and operates the world's most capable constellation of Earth-imaging satellites. Planet's mission is to image the entire Earth, every day, and make global change visible, accessible, and actionable. With the complementary RapidEye constellation, Planet has an image archive from 2009 and a network of more than one hundred partners around the world. See change. Change the world.
Learn more at www.planet.com, or follow us on Twitter (@planetlabs).
NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI -- the next era of computing -- with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world.
DigitalGlobe is a leading global provider of commercial high-resolution earth imagery solutions. Sourced from our advanced satellite constellation, our geospatial offerings support a wide variety of uses within defense and intelligence, civil agencies, mapping and analysis, environmental monitoring, oil and gas exploration, infrastructure management, Internet portals and navigation technology.
The Intelligence Programme Line of Airbus has unrivalled expertise in satellite imagery acquisition, data processing, and dissemination. Airbus provides customized solutions across all markets, and based upon exclusive access to optical and radar satellites, the company delivers an extensive portfolio spanning the entire geo-information value chain.
ASD is a world leader in spectroscopy solutions for remote sensing. Researchers at universities and institutions across the globe trust our portable, rugged and easy-to-use instruments and software solutions for research-critical measurements in the field. To rapidly collect spectra to ground truth hyperspectral and multispectral imaging data, choose ASD.
SARmap's mission is to build and provide an innovative, sophisticated yet simple remote sensing software product, dedicated to the generation of digital information for a better management and risk assessment of Earth's natural/environmental resources.
CloudEO teams with world-leading content and software providers to offer to you a unique geo-infrastructure as a Service bringing together data, software and processing power.
HySpeed Computing’s mission is to evolve the science and business of managing our planet’s resources through development of innovative applications for deriving information from geospatial imagery.