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Sensor WebStrategies

Karen MoeSensor Web Task Team

NASA Earth Science Technology Office

February 25, 2008 CEOS WGISS-25

Sanya, China

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Earth Observation Sensor Web

• Sensor Web Task Team (SWTT) strategies and expected outcomes

• Sensor web operational concepts

• Concept development since WGISS-24– Technology push – Technology pull – What we’ve learned so far…

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Sensor Web: A Service-Oriented Architecture Approach

Sensor webs will be dynamically organized to • collect data, • extract information from it, • accept input from other sensor / forecast /

tasking systems, • interact with the environment based on

– what they detect or – are tasked to perform, and

• communicate observations and results in real time.

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SWTT Sensor Web Strategy

• Address GEOSS goals (science -> SBA)• Apply emerging sensor web technologies • Leverage international resources

– EO data, models, in situ sensors, & satellites

• Explore technology push & pull• Expected outcomes

– Use Cases (featuring operational concepts)– Proof-of-concept prototypes– Lessons learned / implications for GEOSS

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Sensor Web Operational Concepts

• Dynamically acquire & fuse data from models, satellite and in situ sensors

• Validate data observations in near RT

• Provide intelligent sensor control feedback to enable RT sensor tasking

• Enable discovery and access to sensor web components and services

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SWTT Exploration Phase

• Technology push – What sensor resources team members can

bring and create plausible applications– How can sensor webs support virtual

constellations

• Technology pull – What do scientists need to better

understand and forecast phenomena– What information do policy makers or

disaster response teams need

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Sensor Web Use Cases Explored

• Sensor web assisted Cal/Val for GRACE- CHAMP constellation– Put on hold due to lack of member resources to

pursue

• Flash flood monitoring use case builds on WGISS Grid technology demo– SWTT proposed phase 1 project presentation in

WGISS-25– Later phases will extend demo to show model

feedback to EO-1 sensor tasking and provide resulting data and forecasts to SERVIR disaster management system, and Int’l Fed of the Red Cross (IFRC) global flood monitoring system

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Sensor Web Support to ACC

• CEOS Atmospheric Composition Constellation (ACC) team discussed possible collaboration with SWTT

• Smoke Trajectory Forecast: ACC wants to leverage relevant satellite and in situ sensors and evolve modeling approaches to overcome limitations of existing sensor assets to produce improved forecasts

• Sensor Web for ACC builds on aerosol trajectory model and incorporates EO-1 sensor tasking

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Sensor Web Support to ACC

EO-1(ALI & Hyperion)

Smoke Trajectory Forecast Model

MODIS Active Fire Map

EO-1 Fire Sensor Web EvolutionCALIPSO - CloudSat

Terra (MODIS)

Aqua (MODIS)

• CALIPSO (near RT aerosol data) and MODIS (vertical component data) augment model forecast

• Produce a 3D smoke trajectory forecast product to international AirNow system

• Compare predicted with actual smoke conditions using EO-1 imagery

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Underlying Sensor Web flow

• Example sensor web themes in use cases, an emerging pattern– Routine event monitoring (in situ rain gauges,

sentinel systems for fire, volcanos, etc)– Model predicts potential event (flood, smoke

trajectory)– Event detection or model prediction triggers

request for near RT sensor observation task– New observation data augments model for more

accurate forecast– New observation and improved forecast feeds

disaster management portal

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Reflections on SWTT Activities since WGISS-24

• Lessons learned on how we work as a team in support of CEOS

• Discuss need for documenting SSWT– “Program” perspective – “Project” perspective – Use Case – Activity Flow Chart– Findings and Recommendations

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Reflections on SWTT (cont’d.)

• “Program” perspective – A strategic view of the team activities – One over-arching “profile” of team,

expected outcomes, relating activities to GEOSS

• “Project” perspective – A short project plan describing the

objectives of a selected application prototype

– One each per application: flood, wildfire/smoke

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Reflections on SWTT (cont’d.)

• Use Case– A detailed discussion of a specific

application summarizing actions, actors, resources

• Activity Flow Chart – A very detailed diagram of the source and

sink of each step of the prototype demo

• Methodology presented by M. Burnett – “An Approach for Repeatable Sensor Web

Construction”

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Reflections on SWTT (cont’d.)

• Findings and Recommendations– Summarize our findings on what worked,

what didn’t work, other approaches to try– Describe experience (pros, cons) with

• Standards• Processes • Tools

– Make recommendations • CEOS• GEOSS• Standards bodies (ISO, OGC, others)

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Back-up Charts

• Overview of use case progression since WGISS-24

• WGISS-24 sensor web technology challenges

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Sensor Web Use Cases Explored

• Sensor web assisted Cal/Val for GRACE- CHAMP constellation, involving taskable weather balloons, associate with GPS water vapor profiles– CHAMP-GRACE constellation used to

profile water vapor – Task in situ weather balloons – Implement web services to discover and

task applicable weather balloons– Fuse data products and identify

mismatches where calibration is needed

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Building on Grid Technology Demo

• Flash flood monitoring: Rain gauge input to forecast model detects potential flood condition. Improve flood model forecasts by discovering and supplying recently acquired applicable satellite data– Rain gauge sensors on Zambezi River

(Mozambique seasonal flood) – NASA data identified via ECHO services – NASU model forecasts flood conditions

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Model Feedback to Sensor Tasking

• Flash flood monitoring: Model flood forecast triggers EO-1 tasking event. Resulting image delivered directly to first responders– NASU model forecasts flood triggers EO-1– EO-1 acquires current image – Model forecast accuracy is improved– Satellite image also delivered directly to SERVIR, a disaster

response system initially developed for Central and South America, now being applied to African events

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Sensor Web Extension to IFRC

• Flash flood monitoring: Int’l Fed of Red Cross & Red Crescent (IFRC) approached NASA about incorporating satellite data to improve existing and planned global flood monitoring of 200 sites world wide

• Team from Geneva is providing operational user insight to use case

• IFRC has disaster response planning system and staff interested in improved information available from use of NASU model and RT sensor tasking in EO-1

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Sensor Web Features and Benefits

• Some Features:– Targeted observations through dynamic tasking– Incorporate feedback to adapt autonomous

operations (e.g., weather forecasts) – Ready access to data and information

• Some Benefits:– Improved resource use and reuse through

reconfiguration of assets– Improved cost effectiveness through autonomous

operations– Rapid response to evolving, transient phenomena– Improved data quality and science value by

comparing sensor data from the same eventDerived from the NASA ESTO Sensor Web Meeting Feb 2007

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1. Technical Challenges

• In the collection and analysis of information from heterogeneous nodes– There is a lack of uniform operations and

standard representation for sensor data– There exists inadequate means for

resource reallocation and resource sharing– Deployment and usage of resources is

usually tightly coupled with the specific location, application, and devices employed

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2. Technical Challenges

• Publishing and discovering sensor resources– Create a publicly accessible infrastructure for

publishing heterogeneous sensor resources and complex applications

– Discover and use sensor resources

• Sensor data fusion– Sensor data has different data models and formats

and different spatial and temporal resolutions,– Fusion -> higher spatial coverage and temporal

resolution

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3. Technical Challenges

• Context-based information extraction– End users have insufficient technical expertise and

time to extract information from sensor data– Users require different views of the data according

to needs and context– Data can be filtered, summarized, transformed– Features can be extracted -> higher level features

-> information -> application/decision making– Same data can be reused for different applications

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WGISS Sensor Web Discussion

• Identify Collaboration Opportunity – Standards-based proof-of-concept sensor web demo– Applied to significant GEO objective (e.g., Virtual

Constellation?); identify GEO “champion” user(s)– Mature standards, capture lessons learned – Develop processes, toolkits to improve usability– Leverage NASA Earth Science Sensor Web technology

investments and prototypes

• Provide feedback to standards bodies, e.g.– OGC SensorML, Mike Botts/UAH– OGC SWE, Liping Di/GMU, Stefan Falke/NG, others– Other standards?

• Formally recommend proven standards to GEOSS