pacific island countries gis/rs user conference 2010, suva, 23-26 november 2010 sensor web...

Pacific Island Countries GIS/RS User Conference 2010, Suva, 23-26 November 2010

Sensor Web Enablement for the Pacific

Vulnerability and adaptation of coastal fisheries to climate change

Scientific support for the management of Coastal and Oceanic Fisheries in the Pacific Islands region (SciCOFish)

Funded by European Union(10th EDF)


Climate change monitoring

• Climate change monitoring involves long-term datasets from numerous partners and observation data must be made available

Þ Need for a system to share sensor observations

• Climate change trends are slow compared to interannual or interdecadal climate variability.

The trends can be biased by sensors & process:• Sensor accuracy• Change in methodology/sensor/location

Þ Need for rigorous metadata about sensors, processes and observations


Open Geospatial Consortium Standards

Web Map Service (WMS)• Requests for geo-referenced map images• 1999: WMS 1.0.0• 2004: WMS 1.3.0

Web Feature Service (WFS)• Requests for geographical features (vector data in GML)• 2002: WFS 1.0.0• 2009: WFS 2.0.0

Web Coverage Service (WCS)• Requests for geographical coverages (raster data in GeoTIFF)• 2003: WCS 1.0.0• 2009: WCS 2.0.0

Some implementations of these services• ArcGIS Server, Geomedia WebMap, MapXtreme, Geoserver, MapServer,…

(see http://www.opengeospatial.org/resource/products/compliant for full list)

http://www.opengeospatial.org/resource/products/compliant


Open Geospatial Consortium Standards

OGC Sensor Web Enablement (SWE) StandardsStandards to exploit web connected sensors and sensor data. 1.0.0 version released in 2006-2007.

Information models• Observation & Measurement Schema (O&M)

Encoding of observations and measurements

• Sensor Model Language (SensorML)Describes sensor systems and processes

• Transducer Markup Language (TransducerML)Describes transducers (response model)

Web services

• Sensor Observation Service (SOS)Provides access to observations

• Sensor Planning Service (SPS)Tasks acquisition from sensors

• Sensor Alert Service (SAS)Subscribe to specific alert type

• Web Notification Service (WNS)Asynchronous communication for long requests


Observation & Measurement Schema

“An observation is an event that estimates an observed property of a feature of interest using a procedure and generating result.”

Feature of interestDomain specific feature, which is a representation of the observation target for which the observation is made.• Earth realm (ocean, river, sea surface,...)• Named region, location (Micronesia, Kimbe Bay)• Event (cyclone Erica)• System (sensor)

Observed propertyPhenomenon for which the observation result provides an estimate of its value.• Temperature• Humidity

ProcedureDescription of a process used to generate the result (sensor, model, observer)

ResultValue generated by the procedure

Additional propertiesSampling Time, Result Time, Parameter, Metadata, Result Quality


Observation & Measurement Schema

“An observation is an event that estimates an observed property of a feature of interest using a procedure and generating result.”

<om:Measurement> <om:samplingTime><gml:TimeInstant>

<gml:timePosition>2010-10-14T00:22:12+11:00</gml:timePosition> </gml:TimeInstant> </om:samplingTime> <om:featureOfInterest>

<sa:SamplingPoint> <gml:name>Weather station of Zsyxx</gml:name>

<sa:sampledFeature xlink:href="myFeatureReference"/> <sa:position> <gml:Point srsName="EPSG:4326">

<gml:pos>160.124 -22.14</gml:pos> </gml:Point> </sa:position>

</sa:SamplingPoint> </om:featureOfInterest> <om:observedProperty xlink:href="property:OGC:RelativeHumidity"/>

<om:procedure xlink:href="mySensorReference"/>

<om:result xlink:href="percent" >41</om:result>

</om:Measurement>

When

How

What

Where

Value


SensorML/TransducerML

There are many ways of measuring a single physical value !

°C

°FK


SensorML/TransducerML

SensorML is used to define physical (detectors,...) and non-physical (classification, image processing, spatial transforms,...) processes

• Description• Parameters

• Metadata • General information (identifier and classifier)• Constraints (valid time, legal constraints)• Properties (capabilities and characteristics)• References (contacts and documentation)• History

• Inputs (observed phenomena or incoming data for a non-physical process) • Outputs (data created by the process)

SensorML examples

Example: Garmin GPS 17 HVS <?<sml:SensorML  <sml:member> <sml:System gml:id="GPS_17HVS"> <gml:description>SensorML instance for a Garmin GPS</gml:description> <gml:name>Garmin GPS 17HVS</gml:name> <sml:identification> <sml:IdentifierList<><sml:identifier> <sml:Term definition="urn:x-ogc:def:identifier:OGC:shortName“>

<sml:value>Garmin 17HVS</sml:value></sml:Term></sml:identifier></sml:IdentifierList> </sml:identification> <sml:classification> <sml:ClassifierList><sml:classifier name="Sensor Type"> <sml:Term definition="urn:x-ogc:def:classifier:OGC:sensorType"> <sml:value>GPS</sml:value> </sml:Term> </sml:classifier></sml:ClassifierList> </sml:classification> <sml:characteristics> <swe:Record> <swe:field name="channels"> <swe:Count> <swe:value>12</swe:value> </swe:Count> </swe:field> </swe:Record> </sml:characteristics>

Identifier

Classification

Characteristics

Description


SensorML examples

Some outputs of the GPS sensor

<sml:outputs> <sml:OutputList> <sml:output name="Record1_output"> <swe:Record id="record_type_1"> <swe:field name="position“><swe:Position id="GPS_POSITION"> <swe:location><swe:Vector referenceFrame="urn:x-ogc:def:crs:EPSG:6.1:4329"> <swe:coordinate name="latitude“> <swe:Quantity><swe:uom code="deg"/></swe:Quantity> </swe:coordinate > <swe:coordinate name="longitude"> <swe:Quantity><swe:uom code="deg"/></swe:Quantity> </swe:coordinate > </swe:Vector> </swe:location> </swe:Position> </swe:field> <swe:field name="samples">

<swe:Count definition="urn:ogc:def:data:numOfSamples"/> </swe:field> <swe:field name="operationTime"> <swe:Quantity definition="urn:ogc:def:sensor:MMI:timeSinceStartup"> <swe:uom code="s"/></swe:Quantity> </swe:field> </swe:Record> </sml:output> </sml:OutputList></sml:outputs></sml:System></sml:member></sml:SensorML>

Position

Number of samples

Operation time


SensorML examples

System capabilities of a Conductivity, Temperature, Depth (CTD) Sensor

<sml:capabilities> <swe:Record> <swe:field name="Depth Capability"> <swe:Quantity definition="urn:x-ogc:def:classifier:SBE:depthCapability"> <swe:uom code="m"/> <swe:value>7000</swe:value> </swe:Quantity> </swe:field> <swe:field name="Storage Type"> <swe:Category definition="urn:x-ogc:def:classifier:SBE:storageType"> <swe:value>EEPROM</swe:value> </swe:Category> </swe:field> <swe:field name="Memory Capacity"> <swe:Count definition="urn:x-ogc:def:classifier:SBE:memoryCapacity"> <swe:uom code="By"/> <swe:value>2960000</swe:value> </swe:Count> </swe:field> </swe:Record> </sml:capabilities>


SensorML examples

System inputs of a Conductivity, Temperature, Depth (CTD) Sensor

<sml:inputs> <sml:InputList> <sml:input name="temperature"> <swe:Quantity definition="urn:x-ogc:def:phenomenon:OGC:temperature"> <swe:description>Sea Water Temperature</swe:description> </swe:Quantity> </sml:input> <sml:input name="conductivity"> <swe:Quantity definition="urn:x-ogc:def:phenomenon:OGC:conductivity"> <swe:description>Sea Water Conductivity</swe:description> </swe:Quantity> </sml:input> <sml:input name="pressure"> <swe:Quantity definition="urn:x-ogc:def:phenomenon:OGC:pressure"> <swe:description>Sea Water Pressure</swe:description> </swe:Quantity> </sml:input> </sml:InputList> </sml:inputs>

SensorML examples

System outputs of a Conductivity, Temperature, Depth (CTD) Sensor

<sml:output name="output data"> <swe:Record id="CDT_DATA"> <swe:field name="temperature"> <swe:Quantity definition="urn:x-ogc:def:phenomenon:OGC:temperature"> <swe:description>Sea Water Temperature</swe:description> <swe:uom code="Cel"/>  <swe:constraint><swe:AllowedValues><swe:interval>-10.0 100.0</swe:interval></swe:AllowedValues> </swe:constraint> <swe:quality><swe:Accuracy><swe:uom code="Cel"/><swe:value>0.002</swe:value></swe:Accuracy> </swe:quality> </swe:Quantity> </swe:field> <swe:field name="conductivity"> <swe:Quantity definition="urn:x-ogc:def:phenomenon:OGC:conductivity"> <swe:description>Sea Water Conductivity</swe:description> <swe:uom code="S/m"/> <swe:constraint><swe:AllowedValues><swe:interval>0 10.0</swe:interval></swe:AllowedValues> </swe:constraint> <swe:quality><swe:Accuracy><swe:uom code="S/m"/><swe:value>0.0003</swe:value></swe:Accuracy> </swe:quality> </swe:Quantity> </swe:field>


Sensor Observation Service 1.0

GetCapabilities()

Capabilities Response

DescribeSensor()

SensorML/TML

GetObservation()

O&M Data

SOS ServerSOS Client

Obtention of sensor description and observations through SOS


Sensor Observation Service 2.0

GetObservationByIDGetFeatureOfInterest

InsertSensorDeleteSensorInsertObservation

InsertResultInsertResultTemplateGetResultTemplateGetResult

SOS 2.0 (RFC at the moment) extends SOS 1.0

SOS ServerSOS Client


Sensor Web Enablement for climate change data

Climate change monitoring constraints:

• Need for a system to share sensor observations• Need for rigorous metadata about sensors, processes and observations

Þ O&M schema provides a standard for observations

Þ SensorML provides a standard for sensors and processes metadata

Þ SOS provides a mechanism to access that information

SWE


Vulnerability and adaptation of coastal fisheries to climate change

SPC is deploying temperature scientific-grade sensors in some pilot sites for long term monitoring of sea surface temperature in reef areas.

The data will be made freely available on SPC web site through Sensor Observation Service in 2011.


Some existing Sensor Observation Service servers

NOAA Integrated Ocean Observing System (IOOS) http://sdf.ndbc.noaa.gov/sos/http://opendap.co-ops.nos.noaa.gov/ioos-dif-sos/

Institute for Geoinformatics University of Münster weather datahttp://v-swe.uni-muenster.de/

Renaissance Computing Institute (RENCI) Sensor Data Bushttp://www.sensordatabus.org/default.aspx

http://sdf.ndbc.noaa.gov/sos/

http://opendap.co-ops.nos.noaa.gov/ioos-dif-sos/

http://v-swe.uni-muenster.de/

http://www.sensordatabus.org/default.aspx


Sensor Web Enablement resources

OGC Sensor Web Enablement working grouphttp://www.opengeospatial.org/projects/groups/sensorweb

OGC SWE Standardshttp://www.opengeospatial.org/standards/omhttp://www.opengeospatial.org/standards/sensormlhttp://www.opengeospatial.org/standards/sos

Implementing Sensor Observation Servicehttp://mapserver.org/ogc/sos_server.htmlhttp://www.oostethys.org/downloadshttp://52north.org/http://wiki.deegree.org/deegreeWiki/deegree3/SensorObservationServicehttp://ogc.codeplex.com/

http://www.opengeospatial.org/projects/groups/sensorweb

http://www.opengeospatial.org/standards/om

http://www.opengeospatial.org/standards/sensorml

http://www.opengeospatial.org/standards/sos

http://mapserver.org/ogc/sos_server.html

http://www.oostethys.org/downloads

http://52north.org/

http://wiki.deegree.org/deegreeWiki/deegree3/SensorObservationService

http://ogc.codeplex.com/

pacific island countries gis/rs user conference 2010, suva, 23-26 november 2010 sensor web...

Documents

result sensor

sensor data

observation result

sensor systems

sensor accuracy change

observation data

pacific vulnerability

observation target