IMAGINiT Civil Solutions Blog

Mapping Coral Reefs

Coral reef systems are important for a number of reasons.  Since they are sensitive ecosystems, they can be used as barometers for the conditions of the oceans and as indicators of climate change.  Coral reefs provide protection for shorelines.  They are habitats for nearly one quarter of ocean fish species and provide a source of food for millions of people.  As well as natural and climate change related pressures on the reef systems, man is having an increasingly devastating effect.  In the Spratly Islands in the South China Sea, entire reefs are being destroyed by poachers harvesting giant clams.  The BBC recently reported on this activity.  You can find one of the BBC stories here.

You would think that with this importance there would be abundant data on reef systems and that they would have been the subject of numerous studies.  Oddly, there has not been a lot of scientific study of reef ecosystems over the global reef areas.  While there have been lots of smaller studies using conventional marine technologies and underwater data gathering, the results of these studies really can’t be scaled to determine what is happening to reef systems at a larger scale.

NASA is undertaking a three-year project to survey the reefs in greater detail on a global basis.  This survey, called the COral Reef Airborne Laboratory (CORAL), will use an airborne Portable Remote Imaging Spectrometer or PRISM, developed and managed at NASA’s Jet Propulsion Laboratory in Pasadena, California.  Additional, concurrent in-water measurements will be used to validate the airborne measurements of reef condition.

One of the expected outcomes of this expedition will be the creation of a unique database of uniform scale and quality for the large reef areas.

Shown below is an illustration produced with Autodesk AutoCAD Map 3D.  It is based on data taken during a study of part of the reef system around the island of Maui.  The data was derived from the original SHP files and I migrated it to a SQL Server database.  An FDO connection to that database populated the map.  The illustration shows a portion of the reef themed to highlight the health and density of the coral.  The 3D view shows this theming as a graph where the height of each polygon represents the overall health in that area.  You can see the red area where some major silting was detected and the colony has suffered.  The confession here, however, is that while the reef areas are correct, I have fabricated the health and density data so I could show one of the ways this type of data may be represented.

 

 

I’m really interested to see if the NASA data will be available upon completion of the survey.  I’m sure it will make for some interesting and enlightening presentations.

Studying Extreme Events

I was sitting up, reading in bed late in the night of December 29th, when the bed was jolted by a hard thump.  This wasn’t a gentle vibration, but a solid knock that resembled having the bed hit by a low speed car.  This wasn’t the first time I’d felt something like this, so I suspected I had just felt an earthquake.  Sure enough, it was the shock of a 4.7 magnitude quake centered northeast of Victoria, on Vancouver Island.  You can see the details here.  By the time it had travelled the distance to my location, it was effectively a 2.7 magnitude event.

It seems a lot of areas in North America are experiencing extreme natural events this winter, including tornados in Texas and severe flooding in the US Midwest.  All of these natural disasters cost lives and millions in property damage.  A study being undertaken by engineering researchers at the University of Arkansas, who are studying how soil reacts to stress caused by earthquakes or floods, currently are participating in a research project to document the effects of the recent, severe flooding in the US Midwest.

This is a co-operative study among the University of Arkansas, the U.S. Army Corps of Engineers, local levee districts and researchers at other universities.  This group comprises the Geotechnical Extreme Events Reconnaissance Association team.  The team is travelling to parts of Arkansas and Missouri to photograph and assess flood damage and the performance of levee systems.

Data needs to be collected as soon as possible after one of these events, as much of this data exists only within a small time window before being being altered by the natural processes and human responses.  The goal is to better understand how infrastructure and complex transportation systems respond in the face of extreme natural events including earthquakes, tsunamis, hurricanes, landslides and floods. The researchers map and survey both damaged and undamaged areas to provide data that will be used to improve engineering and design of these systems.

In the case of flood events and the response of levees to these floods, data initially available may be washed away or destroyed during repairs.  It is critical that the conditions be evaluated and documented during the flood, if possible, and shortly thereafter. Gathering this data from the field is essential to understanding of how levees perform in a given event and under what mechanisms failures occur.  The scientists and engineers will work with the U.S. Army Corps of Engineers and state and local organizations to document the geotechnical, hydraulic and climatic impact of the flooding and how it affects public policy as part of a systems-based approach to understanding the overall performance of the central-Midwest flood-protection system.

Michelle Bernhardt, assistant professor of civil engineering at the University of Arkansas and one of the engineering researchers, uses computer modeling to digitally simulate small particles, representative of those comprising various soils.  Her models show how these particles react to displacements and stress caused by an earthquake or flood.  Studying these particle-to-particle interactions improves our understanding of large-scale interactions and how materials react to different loading mechanisms, thereby furthering our knowledge of fundamental soil behavior.

Toward an Open Standard Discrete Global Grid System

OK, so here I am again, talking about standards.  In this case, it’s another initiative by the Open Geospatial Consortium (OGC).

Over the past few years, there has been an almost exponential growth in the amount of geospatial data available, the platforms and applications used to collect it and the tools to process, analyze and display it.  With this growth comes a requirement for understanding how various data types can be connected and how location specific data may be represented accurately when that data may be provided within any number of coordinate reference systems. Interoperability is key to fully utilizing these diverse data sets.

Unfortunately, we are in a situation where we still often rely on time consuming and counter productive methods of managing this data.  Geographic transformations are common, some of which may be quite difficult.  The environment we all work in currently falls short in providing a framework where all the participants in a project may be able to take direct advantage of the data available, making the data less valuable as a whole and even impacting any decisions base on the analysis.

The OGC is taking a look at this situation initially through the process of first requesting public comment on a proposed Discrete Global Grid System (DGGS) Core Standard candidate.  What does this DGGS Core Standard entail?  Well, one of the fundamental contributions of a DGGS is geospatial data fusion on demand.  When you have an environment consisting of a number of data providers, the only way you can attain a fusion is through the use of an open standard upon which to base the information architecture.  The OGC DGGS Core Standard candidate would enable interoperability within and between different discrete global grid systems.  This gives you a a wider choice on how you want to collect your data and initially represent its spatial location without worrying if other participants can make use of it.  This also broadens the ability to reuse and exchange the data for varied purposes.

The OGC DGGS candidate works by defining rules for structuring spatial data architectures in an efficient manner for storage and analytics.  The hope (and goal) of this candidate is to overcome the limitations of individual coordinate systems.  Once you have removed the difficulties of working with these legacy coordinate systems, you should be able to make use of and integrate various sets of data much more quickly, with fewer errors and intermediate processing.

A DGGS represents the Earth not as a lattice of points like a conventional coordinate system, but as sequences of cell tessellations, each tessellation having global coverage and with progressively finer spatial resolution. Traditional coordinate systems are defined as the basis for navigation (each time you follow the same path you end up in the same place), whereas a DGGS is meant to ensure that the representation of measurements is repeatable.  Each cell will represent, within its area and explicit spatial resolution, a homogenous value with some form of identifier or indexing to allow for ordering, hierarchies and nearest neighbour algebras.  By assigning a cell corresponding to the position and the size of an individual event being observed, the spatial cataloging of the event becomes more efficient.  Included within the DGGS are (or should be) a standard set of functional algorithms that yield a rapid analysis of the data over very large numbers of cells.

The images below illustrate how some different tessellations may appear.

 

The idea of a DGGS itself is not unique to this OGC candidate.  Indeed, there are several working DGGS prototypes. The PYXIS WorldView client application uses the Icosahedral Snyder Equal Area Aperture 3 Hexagonal DGGS (Snyder Grid).  This DGGS has been used successfully to demonstrate multi-source on-demand data integration and analysis within several OGC Open Web Services, cross-community interoperability test-beds, and International Group on Earth Observations GEOSS architectural pilot projects.

The New Zealand government research institute Landcare Research is developing an open-source DGGS geographical analysis system for worldwide scientific collaboration called SCENZ-Grid.  This uses a rectangular DGGS of 3x3 tessellations of the six faces of a hierarchical equal area iso-latitude pixelated ellipsoidal cube (HEALPix). HEALPix originated in NASA's JPL for astrophysical analyses of massive full-sky data-sets.

If you want to take a look at the documents for the candidate OGC Discrete Global Grid Systems (DGGS) Core Standard, they are available for review and comment at (www.opengeospatial.org/standards/requests/143). Any comments are due by February 4th, 2016.

You also can visit the OGC website at www.opengeospatial.org/.

The Arctic Spatial Data Infrastructure Project

In earlier posts, you’ve seen me mention the Open Geospatial Consortium (OGC®), but you may not be aware of what it is or what it does.  Let me explain.  The OGC is an international consortium composed of more than 515 companies, government agencies, research organizations, and universities participating in a consensus process to develop publicly available geospatial standards. This is a really significant effort because the standards developed by the OGC make it possible to support interoperable solutions that “geo-enable” the Web, wireless and location-based services, and mainstream IT.  Technology developers can use these standards to make geospatial information and services accessible and useful with any application that needs to be geospatially enabled. I urge you to visit the OGC website at www.opengeospatial.org.

Recently, the OGC has announced a new OGC Interoperability Program project called the “Arctic Spatial Data Infrastructure Standards and Communication Pilot” (Arctic SDI Pilot).

The Arctic SDI Pilot is sponsored by the United States Geological Survey (USGS) and Natural Resources Canada.  Given that the Arctic is an ecologically sensitive area as well as a focus for resource exploration and political sabre rattling, the goal of this pilot is to demonstrate to Arctic stakeholders the diversity, richness and value of a Spatial Data Infrastructure (SDI) based on Web services and standardized exchange formats.  The hope is that this will help address many of the critical issues impacting the Arctic.  The stakeholders in this region include organizations and decision makers engaged in scientific research, resource and environmental management as well as those involved in economic and political policy making.  All the participants in this Arctic SDI Pilot will publish their findings and document any best practices that would allow for the support of a rich network of Web-accessible data and service resources for the Arctic.

This pilot has two phases. Phase 1, which is an OGC Interoperability Program Concept Development study, began in December 2015. In this phase, an inventory of available data and services will be built, and the SDI architecture will be defined.  Phase 1 also will provide direct input into OGC’s major Testbed 12 Interoperability Program initiative. These testbeds provide organizations with abilities to develop and test components based the concepts identified in a pilot in a real world context.  You can see the RFQ for Testbed 12 here.

http://www.opengeospatial.org/standards/requests/139

Phase 1 findings will serve as input for Phase 2, which will be an OGC Interoperability Program Pilot Project. Here’s where it gets interesting for most of us.  The OGC pilot projects apply and test OGC Standards in operational applications using Standards Based Commercial Off-The-Shelf (SCOTS) products that implement OGC Standards. At this point, developers and end users can interact, collaborate and learn how to better address their requirements using standards-based architectures. The more these communities participate, the greater the benefit to the project, and the knowledge base.  By adopting and developing applications that rely on these open standards, the more connected our information becomes.  In our global society, this represents an essential platform to our understanding of the processes we are observing, monitoring and managing.