GeoBytes are free online seminars presented by ASPRS, in cooperation with CaGIS and our new partner AAGS.

Next year Geobytes will cover a wide range of topics including geodesy, precision agriculture, standards, Big Data and more. Also, in support of the National Park Service (NPS) Centennial celebration we have organized a couple of GeoBytes highlighting their geospatial activities: “A Geospatial Approach to Mapping Environmental Sound Levels across the United States” and “Designing National Park Service Visitor Maps”.

Schedule

Fusion of Geodesy and GIS at NOAA's National Geodetic Survey
Brian Shaw, NGS
January 29th, 2016

The mission of NOAA’s National Geodetic Survey (NGS) is to define, maintain, and provide access to the National Spatial Reference System (NSRS), the foundation for navigation, mapping, and surveying in the United States. For most of its over 200 year history, NGS has largely met its mission objectives without GIS...until now. NGS has developed a GIS toolbox that includes survey tools that create attribute-rich GIS features for GNSS and geodetic leveling networks directly from NGS software output (including OPUS-Projects), and a grid conversion tool that generates standard GIS rasters from NGS grids, such as geoid models. The GIS tools were created using the Python scripting language and are accessed through the Esri ArcToolbox. This workshop describes these new NGS GIS products and services and shows how they are being used. The new tools provide better access to the NSRS and leverage the power of GIS for display and analysis of geodetic data. By developing such tools, NGS better meets the needs of our growing and diverse customer base of surveyors, GIS practitioners, and other geospatial professionals.

Brian Shaw is a Geodesist at NOAA’s National Geodetic Survey. He began his career at NGS in 2002 after earning a BS in Computer Science with minors in Mathematics, Geography and History from Radford University. He earned an MS in Geographic Information Systems from the University of Redlands in 2005. Brian serves as the NGS representative to the National States Geographic Information Council and is the leader of the NGS GIS team. He also actively supports NOAA's Science On a Sphere serving as a docent and the National Ocean Service advisor.

Webinar ID: 143-514-931

Beyond NDVI … 2016
Jack Paris
February 26th, 2016

Geospatial maps for agricultural mapping and monitoring uses have been made for many decades based on the well-known Normalized Difference Vegetation Index (NDVI) formula, which was first proposed in the late 1960s as a better way to combine two bands of multispectral (MS) digital image values when making sets of vegetation-vigor condition indicator values as vegetation vigor varies spatially over an area of interest and/or temporally over a given span of time. The simplicity of the NDVI formula has made it and continues to make it very attractive as an algorithm vegetation vigor mapping and monitoring.

However, in the late 1980s, a better, physical understanding was gained about how electromagnetic radiation interacts with vegetation and soils. This led to the Soil Adjusted Vegetation Index (SAVI) formula and its many variants as ways to make vegetation-vigor maps that are physically-based and hence that are better than those maps that are made by the NDVI formula.

Nevertheless, the use of the NDVI formula is still dominant today. Unfortunately, many NDVI map vendors use poor-quality and often uncalibrated MS images when making an NDVI map. And, since each NDVI map is based on only two spectral bands … usually a red-light band and a near-infrared pair of images, information in other MS bands is left behind. This is especially true when the source of MS imagery includes many more than just the NDVI-related pair of spectral bands.

As the number of imaging systems have increased dramatically and as this expansion is set to expand even more so in 2016 and as the spatial resolutions of these sources are getting smaller and smaller … even down to centimeter sizes, a challenge exists regarding how best to take advantage of these many bands and frequent revisits. Dr. Paris will be presenting information about the history of vegetation and soil mapping with the hope that better standards will be adopted by the whole remote-sensing community and that better information maps will be made for customers … Beyond NDVI … in 2016.

Dr. Paris’ background includes undergraduate studies at Texas A&M University (physics and mathematics, B.S., 1962) and at the University of Washington (atmospheric sciences, B.S., 1963). After four years as a Weather Officer in the USAF, he returned to Texas A&M University for graduate work (meteorology, Ph.D., 1971). However, this doctoral degree was really a degree in remote sensing (dissertation topic: Thermal microwave applications for atmospheric and ocean mapping and monitoring). Since 1972, Dr. Paris has been a remote sensing scientist and educator until his retirement from California State University (CSU) in 2002. He worked for Lockheed Electronic Company, the University of Houston at Clear Lake, NASA (Houston), JPL, CSU Fresno, and CSU Monterey Bay. Since 2002, Dr. Paris has been working for commercial companies including MicroImages, Inc., DigitalGlobe, Inc., EarthMap Solutions, Inc., the Monsanto Company, C3 Consulting LLC, and Trimble. Most of this experience has been as a consulting. In 2009, Dr. Paris formed his own consulting company, Paris Geospatial, LLC. Currently, Dr. Paris is involved with the development of better image processing algorithms … beyond NDVI … for Landsat 8 data, RapidEye data, data from several pilot-on-board aircraft imaging systems, and data from remotely-operated aircraft mapper systems. He is also working on algorithms for data from new systems such as Planet Labs and MicaSense RedEdge cameras. Dr. Paris writes customized processing algorithms using the SML scripting language in TNT (MicroImages) software and is the author of “Scripts by Jack” and “FAQs by Jack” that are posted on the MicroImages Web site.

A Geospatial Approach to Mapping Environmental Sound Levels Across the United States
Dan Mennitt, NPS
Kurt Fristrup, NPS
March 25th, 2016

To support the conservation of natural and cultural sounds, and outstanding opportunities to hear them, the National Park Service works to protect, maintain, or restore acoustical environments throughout the National Park System. The National Park Service has a unique challenge due the vast quantity of land to manage, the diversity of acoustical environments therein, and the high standards to which these resources are upheld. Soundscapes have direct implications for visitor experience and wildlife ecology, and are often complex due to a multitude of acoustic sources and sound propagation effects. While physical modeling of acoustic propagation is a mature science, the diversity of contributions to environmental sound levels and prevalence of spatiotemporal patterns suggests a statistical approach to modeling. Using 1.5 million hours of acoustical data from hundreds of sites across the United States, geospatial models were developed to interpret and predict sound levels. The models utilize random forest, a tree based machine learning algorithm, which does not explicitly incorporate any apriori knowledge of acoustic propagation mechanics. Instead, the models rely on spatial representations of biological, geophysical, climatic, and anthropogenic factors to assess expected contributions to the existing sound pressure level from both anthropogenic and natural sources. This method enables mapping of sound levels at regional and national scales. Environmental noise is widespread across the United States and chronic exposure brings with it adverse consequences to terrestrial organisms. Assessments of noise exposure are essential to understand the extent of impact as well as inform land use planning and noise abatement strategies.

Dan Mennitt is a research scientist in the Department of Electrical and Computer Engineering at Colorado State University. Dan works in partnership with the National Park Service's Natural Sounds and Night Skies Division to provide outstanding opportunities for people to experience the restorative quality, extraordinary sounds, and simply remarkable nature of wilderness. His current research interests include remote sensing, spatiotemporal patterns of sound on landscape scales, and acoustic horn dynamics.

Kurt Fristrup is the Branch Chief for Science and Technology in the Natural Sounds and Night Skies Division of Natural Resource Stewardship and Science, a directorate within the U. S. National Park Service. He has overseen monitoring of acoustical conditions at more than 600 sites in national parks and other protected natural areas. Kurt previously worked at Woods Hole Oceanographic Institution and the Cornell Laboratory of Ornithology, where his research interests included evolutionary theory, marine mammal ecology and behavior, the effects of noise on wildlife, environmental acoustical monitoring, and wildlife radio telemetry.

Designing National Park Service Visitor Maps
Tom Patterson, NPS
April 29th, 2016

The look of National Park Service maps, which have had a familiar design dating back to the 1970s, recently has undergone modernization to better serve the 300 million people who visit the parks each year. My talk will discuss the scope of these design changes, why we did them, and how they build upon and enhance previous map design standards.

Tom Patterson is the Senior Cartographer at the US National Park Service, Harpers Ferry Center. He has an MA in geography from the University of Hawai‘i at Mānoa. Tom previously worked as Cartographic Laboratory Manager at the University of Utah. Cartographic relief presentation is his passion. He maintains the ShadedRelief.com website and is the co-developer of the Natural Earth cartographic dataset. Tom is a former president of the North American Cartographic Information Society and is active in the International Cartographic Association, Commission on Mountain Cartography.

CyberGIS: Foundations and Principles
Eric Shook, Kent University
May 27th, 2016

CyberGIS combines advanced cyberinfrastructure with geographic science and systems (GIS) and spatial analysis and modeling as a next-generation GIS enabling researchers and practitioners to tackle challenges that push GIS beyond the computational limits of a desktop PC. Beyond a technology, cyberGIS is emerging as an interdisciplinary field that combines a number of domains ranging from computational, geospatial, and domain sciences to begin tackling fundamental challenges including those revolving around the rapid growth in volume, variety, and velocity of big spatial data. This presentation will provide background and a big picture overview of cyberGIS, explore the various components, technologies, and principles of cyberGIS, highlight recent examples in using cyberGIS and related geospatial technologies, and discuss opportunities and challenges moving forward.

Eric Shook is an Assistant Professor in the Department of Geography and Director of the High-Performance Computing and GIS (HPCGIS) Laboratory at Kent State University. His research interests focus on advancing the state-of-the-art in geospatial technologies that underpin geographic information science (GIScience) thus opening new areas of scientific inquiry. To address various computational challenges, he often employs cyberinfrastructure-based geographic information systems (CyberGIS) and supercomputer-based spatial modeling to investigate large- and multi-scale geospatial phenomena. He is past-chair of the AAG Cyberinfrastructure Specialty Group and is the Extreme Science and Engineering Discovery Environment (XSEDE) Campus Champion for Kent State University.

Getting more from remote sensing data using OGC standards
George Percivall, OGC
July 22th, 2016

For remote sensing, data comes from measurements made by sensors. Information derived from remote sensing data and subsequent application is achieved with mathematical or experience-based algorithms. Standards play an essential role in the process of deriving information and knowledge from remote sensing data, as they are a necessary prerequisite for reliable and efficient science. Much has been done by OGC and other standards developing organizations to establish standards that enable during knowledge generation from remote sensing data. This GeoBytes session will provide a summary of relevant standards for remote sensing information systems. Multiple examples of standards-based applications using remote sensing data will be provided.

George Percivall is Chief Engineer and CTO of the Open Geospatial Consortium (OGC). He is responsible for the OGC Interoperability Program and the OGC Compliance Program. His roles include articulating OGC standards as a coherent architecture, as well as addressing implications of technology and market trends on the OGC baseline. He holds a BS in Engineering Physics and an MS in Electrical Engineering from the University of Illinois - Urbana.

Aqueduct Global Flood Analyzer – a web tool to estimate global flood risks for current and future scenarios
Tianyi Luo, WRI
August 5th, 2016

Floods affect more people than any other natural disaster. River floods cause as much or more damage in some countries as rising sea level and storm surges. Additionally, both the frequency and intensity of floods is expected to increase due to climate change in many areas, according to the latest science. However, lack of access to flood data makes it hard for decision makers to mitigate future lives lost and economic losses.

The World Resources Institute’s Aqueduct Global Flood Analyzer utilizes global flood risk models and IPCC future scenarios to estimate physical characteristics of floods and their associated socio-economic damages and impacts for current and future conditions at the global scale. The Analyzer is best suited for regional flood risk estimation, hotspot identification, and multi-regional comparison across the globe. With those information, we hope that the Analyzer could raise the awareness about flood risks and climate change impacts, and help international organizations and governments identify challenges and opportunities and prioritize risk mitigation and climate adaptation projects.

Tianyi Luo is an Associate with World Resources Institute’s Water Program. He received his MS degree in Environmental and Water Resources Engineering from Tufts University and his bachelor’s from Hefei University of Technology, and currently manages the data analytics and GIS analysis for the Aqueduct Project. Tianyi is specialized in water risks, GIS and remote sensing, and data visualization.

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David Alvarez

“THE FURTHER BACKWARDS YOU LOOK, THE FURTHER FORWARD YOU CAN SEE"

Winston Churchill