1 / 24

Sensor Web Strategies

Sensor Web Strategies. Karen Moe Sensor Web Task Team NASA Earth Science Technology Office February 25, 2008 CEOS WGISS-25 Sanya, China. Earth Observation Sensor Web. Sensor Web Task Team (SWTT) strategies and expected outcomes Sensor web operational concepts

jayme
Download Presentation

Sensor Web Strategies

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Sensor WebStrategies Karen MoeSensor Web Task TeamNASA Earth Science Technology Office February 25, 2008 CEOS WGISS-25 Sanya, China 1

  2. 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… 2

  3. 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. 3

  4. 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 4

  5. 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 5

  6. 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 6

  7. 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 7

  8. 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 8

  9. CALIPSO - CloudSat Terra (MODIS) Aqua (MODIS) EO-1 Fire Sensor Web Evolution Sensor Web Support to ACC • 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 MODIS Active Fire Map EO-1 (ALI & Hyperion) Smoke Trajectory Forecast Model 9

  10. 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 10

  11. 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 11

  12. 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 12

  13. 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” 13

  14. 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) 14

  15. Back-up Charts • Overview of use case progression since WGISS-24 • WGISS-24 sensor web technology challenges 15

  16. 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 16

  17. 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 17

  18. 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 18

  19. 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 19

  20. 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 event • Derived from the NASA ESTO Sensor Web Meeting Feb 2007 20

  21. 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 21

  22. 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 22

  23. 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 23

  24. 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 24

More Related