Suomi NPP: Setting a New Standard for Global Climate Monitoring

On October 28, 2011, the Suomi National Polar-Orbiting Partnership (NPP) spacecraft lifted off from Vandenburg Air Force Base in California and began its scheduled five year mission as a new installment to the NASA fleet of Earth observing systems.  Now in a pole-to-pole orbit around the globe, sensors aboard the NPP platform collect information related to our planet’s land, atmosphere, ice, and oceans.  The geospatial information derived from the Suomi NPP platform has the potential to clearly demonstrate the value of continuous earth observation towards understanding the dynamics of climate change, and the impacts to our planet.

Amidst much debate about both the causes and effects of climate change, time is a key theme.  Weather events that occur over a short period of time are easily understood, even if they are unusual or historic.  However, relating a brief weather occurrence to a broader climatic trend that plays out over a longer time period can invite a difference of opinion regarding causation.  Given that our historic weather records are young relative to the hourglass by which the Earth functions, it’s not surprising that we lack a good reference point for perceiving changes to climate.  Despite a late start, over the past several decades humanity is using remotely sensed data to amass a record of Earth observations related not only to weather, but to a wide range of interconnected processes and properties of our planet.  The Suomi NPP platform represents the latest effort to use satellite technology to bolster our historical record and gain a broad understanding of how our planet changes over time.

Through the use of five imaging instruments, including the largest, and arguably most important sensor onboard, the Visible Infrared Imager Radiometer Suite (VIIRS), Suomi NPP collects measurements used to improve understanding of the complex interactions of the earth’s natural climatic and ecological systems, and provide for the ability to react to changes based on more accurate predictions.  Together, the instruments will allow scientists and the geospatially inclined to:

  • Measure the relative health of the ozone layer
  • Monitor natural disasters, such as wildfires, volcanic eruptions, snowstorms, droughts, floods, hurricanes and dust plumes
  • Use sounding instruments to collect information about cloud cover, atmospheric temperatures, humidity and other variables to improve the accuracy of weather predictions
  • Map changes to global land vegetation to understand the global carbon cycle and monitor agricultural processes that may predict food shortages and famines
  • Track changes to Earth’s sea ice, land ice and glaciers as indicators of climate change
  • Measure air pollution by tracking soot, particulate matter, nitrogen dioxide and sulfur dioxide
  • Maintain a global record of atmospheric, land surface and sea surface temperatures critical to understanding the long-term dynamics of climate change

NASA_Suomi_NPP_Atmosphere_

As the Suomi NPP system collects critical data records of vegetation, clouds, aerosols, sea and land surface temperature, and the productivity of our biosphere, we will gain an unprecedented ability to understand how the components of interconnected Earth systems affect one another and how climate change may be affecting them both individually and collectively.  Ultimately, this knowledge can inform our decisions about how we choose to interact with our natural environment.  In the meantime, here’s hoping the Suomi NPP system resoundingly legitimates the need to prioritize continued funding for satellite-based scientific endeavors in the United States.   How will you use NPP VIIRS data?

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VISualize 2013: Global Change and Environmental Monitoring – SPOILER ALERT!

It’s that time of year once again when thought leaders in remote sensing science and research will come together to collaborate and share their current work – this time with the focus placed on Environmental Monitoring and Global Change.  While I will personally not be able to attend, I was fortunate to gain advance access to some of the abstracts that will presented at this year’s conference. You will see on the registration site that the first two days include presentations from trusted and respected organizations including NASA JPL and GSFC, EPC, Wildlife Conservation Society, Ball Aerospace, Mason University, and the University of Texas. Additionally I am glad to share a few highlights from the abstracts in advance:

Identifying the Top 10 Conservation Challenges that Can Be Answered Through Remote Sensing Technologies, Robert Rose, Wildlife Conservation Society, Bronx, NY.

Who doesn’t love a top 10 list? Thanks to NASA and the Wildlife Conservation – dozens of natural resource conservation leaders came together to identify 300+ challenges that can be resolved or addressed using remote sensing! I look forward to learning which were identified in the top 10.

Ground truthing: Best Practices for Image Validation and Supervised Classification, George Greenwood, ASD Inc., Boulder, CO.

I recently attended a delightful presentation by Adam Tollefsrud from the USDA on his research of biomass volume and its association with localized topographic features. When asked if they were ground truthing their data, he chuckled while asserting that research without ground truthing can be somewhat suspicious! What tools and methods make for best practice in ground truthing – and where should one start? This presentation should give great insight into first steps and accessibility to adding spectral field data to remote sensing analyses.

Tillage mapping with multi-temporal Landsat imagery via ArcGIS, Python, and ENVI/IDL, Guy Serbin, InuTeq LLC, Washington, DC.

This should be an excellent example of how exciting and important the Landsat Data Continuity Mission (LDCM) is to all of us. Best practices in conservation tillage are determined based upon multi-temporal datasets made available via Landsat 5 TM and 7 ETM+. An immediate application for the use of Landsat 8 data will enable the agricultural industry to learn and look ahead toward fulfilling goals of environmental sustainment as climate events occur.

These are just a handful of presentation topics – and after two full conference days – we hope you consider staying on for our Landsat 8 seminar. Spend an additional half-day enjoying a more in-depth study of the new nine-band payload collected by the Operational Land Imager (OLI) and the two thermal bands collected by the Thermal Infrared Sensor (TIRS). It’s not too late to add this seminar to your registration!

You can still register to attend VISualize! And let us know which presentation you’re most excited for!

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Systems and Services

When we talked about software in the past, we talked about complete, closed systems that accomplished a task or set of tasks.  These applications were written by a single vendor and were based on a set of requirements as interpreted and implemented by that vendor. Extending these applications or getting them to interoperate with other applications typically required intimate knowledge of the inner workings, and could only be accomplished by the original developer or through a highly detailed specification.

Things are changing.  Now, when we talk about software we talk about services and capabilities.  An application today might consist of a variety of services developed by different vendors or providers, all interoperating smoothly through standardized interfaces.  Many of these services offer a single capability or a small set of related capabilities.  They are often made available as web services over the internet.  Vendors and developers can pick and choose from a variety of services to build an application that meets user needs.  Where functionality is lacking, the developer can write a new service to fill the gaps. We may still call this a system, but it looks different than the closed systems we’ve seen in the past.  Functionality can be added or swapped out easily because of the encapsulation into services and the use of standardized interfaces and protocols.

Some vendors are providing platforms where a set of related services are provided allowing other vendors, or even end users, to create a customized application built from the capabilities provided with the platform.  These platforms, and the applications they serve, can be extended by incorporating additional services provided by other developers.

Two keys to the success of this type of services-based environment are standards and discoverability.  Services need to be discoverable so that the developers building applications can find them and include them.  Services need to have standardized interfaces so that they can interoperate with each other and the clients that call them.

Because services are typically centralized and accessed through the internet, many users can access them at once, often without needing to install any hardware on their local, or desktop, system.  Multiple applications can leverage the same services, and applications can be updated by updating or adding only the services supporting new functionality.  These are benefits that make this model of services-based applications more cost effective and efficient to deploy and support.

Are you seeing these changes in the applications, or systems, you use or support?  Let me know.

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The Spherical Cow: Models and Applications in Geoscience

NASA_Cow

I had a great physics teacher in high school, Mr. Dechant. I still use what I learned there. Some vector componentized wind data from NOAA I’m currently wrestling with comes to mind. He probably should have gotten an award just for signing up to be around a bunch of unbalanced teenagers, let alone actually teaching us anything. But he did sign up, and he did a great job teaching us the basics of physics, starting with classical mechanics. Teaching classical physics requires some basic assumptions to get a useable model of reality. Frictionless surfaces, uniform densities, everything in vacuum, perfectly elastic collisions and the like.

Being a bunch of high schoolers, we took great pride in picking on and tearing apart anything and everything. We seized on those necessary assumptions as being fundamentally unrealistic and therefore worthy of ridicule. Mr. Dechant was an excellent sport about it and played along while seriously addressing our objections to the frictionless surfaces. We even gave the model a (uninspired) name: “Physics Land”.  It shares borders with “Economics Land”, where rational consumers inhabit perfectly efficient markets, and “Chemistry Land”, where all reactions run to completion and no electron goes unshared. We didn’t know it at the time, but there’s even a well-worn joke about these sorts of assumptions. The punchline is that the physicist answers the dairy farmer’s milk production question, but the solution only works for spherical cows in a vacuum.

Claiming models, scientific or otherwise, are all incorrect or invalid oversimplifications ignores that we use them all the time and that they work. Machines, economies, businesses and communities all use models one way or another. In fact, they work so well that we don’t even notice them in day to day life. Remote sensing in the geosciences has models, too, and they’re tremendously powerful. Like all powerful tools, we need to be sure we use them correctly and not just make a big mess. Knowing when not to use a model can be just as important; while you would never compare uncalibrated datasets to each other, it might be perfectly fine to compare classification results from two different uncalibrated images. Fortunately, it’s much easier to assure correct usage thanks to modern software. Atmospheric models let us get at better reflectance “fingerprint” signatures of what’s on the ground, opening up great potential for mapping geology, biology, land use and more from the air or even from space. All engineered systems have some sort of imperfections, but calibration models let us maximize their signals and the confidence we can have in their measurements. Geographic models, i.e. map projections, let us take the fantastically complex 3D Earth and put it in to maps we can use for navigation, mapping resources, monitoring human activity, getting a better understanding how our planet works, and more.

Put some models to work for you! Get some data for where/what you’re interested in, from NOAA CLASS, USGS EarthExplorer, or your own favorite depot. Then, try out some calibration models, some atmospheric models, or some analytic models and see what you find! There are some amazing discoveries to be had sojourning in the various Model Lands that make up our world. Who knows, maybe you’ll find a spherical cow.

Models_ENVI_Landsat

The images above show, on the left, a calibrated and atmospherically corrected Landsat 5 scene in Karakum Desert, Turkmenistan (R: Band 3, G: Band 2, B: Band 1); an RXD Anomaly detection result is overlain in red, centered. On the right, the brightness temperature calibrated band from the same Landsat 5 scene Band 6 data, showing the anomaly as a bright spot in excess of 300 degrees C. At least 5 models in one workflow! The image of the right demonstrates how improved sensor calibration models for Landsat 8 will allow for much more accurate and precise temperature measurements from the upgraded two-band thermal sensor.  What is it? Make your best guess in the comments. The answer’s here.

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ENVI Geoservices and ArcGIS® Online – A New Paradigm for Image Analytics

The development and release of ArcGIS® Online by Esri® ushered in a new era of GIS access and availability. ArcGIS Online allows organizations and individuals to manage and display their map data on the internet via an easy-to-use interface. This has been useful for GIS professionals who have been overloaded with small requests for geographic information by allowing their users to self-serve data and maps that have been developed and published by the GIS analyst. It also allows users in the field to display ground truth information that may be collected as a series of GPS points or geographic notes. According to Esri, “In addition, non-GIS professionals, such as knowledge workers who have a need for GIS, now have a way to quickly create maps from the unstructured information they work with in spreadsheets and text files and share these maps with others who can access them on any device. This type of on-demand and self-serve mapping frees up GIS professionals from having to respond to constant requests for maps and instead concentrate on making and publishing authoritative information products.” (Esri, June, 2012)

Along with map and display capabilities, ArcGIS Online comes equipped with the ability to conduct geo-processing tasks, or geoservices. Esri currently provides geocoding and network analysis geoservices, among others. Users with an ArcGIS for Server instance can also publish their own geoservices and models from the Esri software suite and consume them via ArcGIS Online. This means that customized workflows can be distributed via ArcGIS Online for consumption by non-technical users in the field. These services can be also be integrated into custom interfaces developed using the ArcGIS Web Mapping API’s or the ArcGIS Mobile Runtime SDK.

An ENVI Geoservice in ArcGIS Online

An ENVI Change Detection Geoservice in ArcGIS Online

Exelis Visual Information Solutions has worked very closely with Esri for years to develop interoperable solutions to leverage advanced image analytics from ENVI from within the ArcGIS ecosystem. Along with both desktop and server side interoperability, ENVI is now able to take advantage of the ArcGIS Online platform to expose ENVI geoservices in the cloud. Implemented using the ENVI Services Engine and the ArcGIS API for JavaScript, the app queries and consumes Landsat image services to run a number of different analysis tasks. Results are delivered back to the thin client as a visual representation, with links to download the processed datasets available if needed. Not only can this type of implementation run analysis and deliver results on remote data, the time-aware nature of the Landsat Image Service allows for time aware analysis to be conducted such as change detection, or in this case, NDVI analysis over time.

Displaying an NDVI Result from an Image Service in a Thin Client

Displaying an NDVI Result from an Image Service in a Thin Client

This example of ENVI image analysis being run on image service data from the ArcGIS online environment is a snapshot of the future. In the same way that the storing and viewing of map products has migrated to the internet, so too will the analysis of large data be executed on large servers in remote locations and consumed via thin clients and mobile apps. What do you think? Are thin clients such as ArcGIS Online that consuming remote data and analysis functionality the future of GIS? Do you see a need in your organization for web-deployed analytics?

ArcGIS Online Will Change How You Think about Mapping and GIS, Esri 2012.

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My thoughts on AAG 2013

A couple of weeks ago, I had the opportunity to attend the AAG Annual Meeting in Los Angeles and spent quite a bit of time speaking with people from the academic community.  These are a few of my observations from time spent on the tradeshow floor.

  • Geospatial software plays an important role in geography.  This seems like a no brainer and the constant traffic at the Esri booth was expected.  What was really exciting was to see the increased traffic at the Exelis booth and some of the other new companies launching exciting geospatial software products in the market.
  • Interest in LiDAR has increased quite a bit.  Compared to last year’s event in New York, the interest in our LiDAR software seemed to double.  Researchers, students, and professors are looking at how to add this data type to improve their understanding.  This leads to my next observation.
  • Data fusion.  My colleagues Rebecca and Patrick have written great posts about what that term means to them here and here.  What I observed, is that data fusion means different things to different people, but at the end of the day the ability to combine different data sets is becoming increasingly important.
  • Excitement over Landsat 8.  We here at Exelis VIS have written about our interest in and excitement about the latest Landsat satellite.  It was really great to hear all of the positive impact this continuity of service will have for geographers.

Were you at the AAG Annual Meeting?  What did you find most interesting regarding the use of imagery?

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How are Women Faring in the Field of Geospatial Technology?

This week I listened to an interesting, if brief, podcast by Joe Fancica and Adena Schutzberg at Directions Magazine about women working in the field of geospatial technology.  Their podcast was inspired, in turn, by questions posed by Hilary Perkin to the Women in GIS LinkedIn group, looking for input for a session at URISA’s fall GIS-Pro 2013 conference.  The questions were:

1. What is the status of women in GIS?

Joe and Adena agreed in the podcast that it anecdotally seems that the field of geospatial technology is about 70% male and 30% female.  Commenter Philip Davis later mentioned that the 2012 National GIS Academic Program Survey estimated that women make up about 34% of academic programs in the field. I couldn’t find additional information about that survey, but those estimates jive with my personal experience in the field as well. At any rate, it seems clear that there are significantly more men than women in geospatial technology careers.

There is some reason to think that this demographic may be changing; among geospatial technology professionals in their 20s, it seems (to me and the editors at Directions Magazine, at least) that the percentage of women is somewhat higher. Adena mentioned that in her experience teaching at Penn State, the classes were about 50/50. My – perhaps earlier – experience at the University of Colorado in the late 90s was less equal. I would guess the classes were more like 70/30. I took or taught more than one geospatial-technology-related class in which I was the only woman. I’m glad to hear that more women may be entering the field now.

2. What issues do women face in our industry?

Lack of role models

Much of the gender imbalance seems likely to

Senior geology major Samantha Taylor receives instruction from Dr. Christina Hupy at the University of Wisconsin Eau Claire's Geography and Anthropology Department. Image courtesy of University of Wisconsin Eau Claire.

Senior geology major Samantha Taylor receives instruction from Dr. Christina Hupy at the University of Wisconsin Eau Claire. Image courtesy of University of Wisconsin Eau Claire.

be related to the fact that the fields from which people are introduced to geospatial technology are traditionally male dominated fields: geology, geography, forestry, land-use planning, urban planning, computer science, etc.  In the podcast, Joe said that these fields, “. . . have not been brought to women as opportunity fields.” I think he means that when women (or men) don’t hear about many other women  (or men) doing a certain type of work, it can be harder for a student to visualize how they could succeed in the field, and would make them less likely to decide that it is a path that would suit them.

So, what would it mean to bring geospatial technology to women as an opportunity field? Apparently, back in the early aughts (2000 to 2002) Directions Magazine ran a series of profiles of prominent women in GIS. The series petered out, though, when they failed to see enough traffic on those articles and started to run out of women to profile. Which was probably due to the exact problem they were trying to address!

While it would be great to see more profiles of prominent women in the field, Adena mentioned in the podcast that it might be even more powerful to find local role models.  I agree. For example, universities could  bring in local professionals to talk to students, so students could hear about their career paths, network, and meet possible mentors.  This could benefit both men and women considering geospatial careers. Moreover, she made the excellent point that we can help by presenting men as willing and capable role models for women, and vice versa.  That opens the pool of potential mentors and network connections for all students.

Privilege

All of the above is even more important when you consider another obstacle that Adena framed as, “Some guys are jerks.” I don’t disagree, although I believe people of all genders can be jerks. In terms of why there aren’t more women in geospatial technology, though, I think about it this way: Some behaviors that are generally accepted by a majority population can make members of a minority population feel uncomfortable or even unwelcome in the community.  Often the people perpetrating these behaviors do not recognize that their behaviors negatively affect others. They don’t recognize it, because they don’t have to; Most of the people around them come from the same perspective they do. That is called privilege.

Talking about privilege is a sticky wicket, for sure. I think a lot of that is because it is easy to conflate privilege with blame. So, if I say, for example, that I feel a little uncomfortable in a meeting where I am the only woman, I am not blaming the men in the meeting, or men in general. But I do recognize that the men in that meeting have the privilege of feeling less noticeable, less different, and more like they belong. The same is probably true for a single man in a meeting full of women. The difference is that the latter happens less often in this field, so it doesn’t work against men choosing to enter the field. Privilege doesn’t equal blame, but it does create greater responsibility for action, because, it comes with greater power.

In recognition of these dynamics, it is becoming more common to have explicit codes of conduct for professional meetings and organizations.  For example, the upcoming Foss4G NA conference in Minneapolis has published a code of conduct prohibiting things like unwelcome sexual attention, sexualized images, and offensive language related to gender, sexual orientation, race, religion, body size, etc.  I’m happy to say that Exelis VIS has a code of conduct that prohibits harassment, which is explicitly defined as unwelcome conduct, including gestures, remarks, and displaying pictures.

What other obstacles do you see that contribute to the lack of diversity in the field of geospatial technology? What additional actions could we take to address all of the obstacles?

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