i scope noisemodel
TRANSCRIPT
i-SCOPE - interoperable Smart City services through an Open Platform for urban Ecosystems
Noise Domain Model: Measurements, Modelling and Mapping
Debbie Wilson – Snowflake Software (on behalf Ordnance Survey)
interoperable Smart City services through an Open Platform for urban Ecosystems
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Overview
• Following slides provide a detailed summary description of the Noise Domain Model
• Measurements• Modelling• Mapping
• Plus proposed generic CityGML ADE for:• Adding time-varying properties to City Objects • New City Objects: ‘Heat Map’ for visualising thematic
properties that vary over space and time
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Noise Domain Model
• Develop a model that meets the requirements for:– Open Data Exchange– 2D and 3D Visualisation
• Applications:– Citizen participation in measuring noise exposure (NoiseTube)– Monitoring /Assessment of noise exposure
• Noise simulation modelling (END Directive)
– Noise Exposure Mapping for citizen engagement and decision-making
• Strategic Noise Maps (END Directive)• 2D/3D visualisation of noise exposure (NoiseTube)
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Noise Domain Model
Measurement Modelling Mapping
Ancillary data: needed as input to
noise simulation modelling
3 Viewpoints:
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Noise Measurements
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UC: NoiseTube – Citizen ParticipationNoise Measurements
http://www.noisetube.net
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UC: NoiseTube – Citizen Participation
http://www.noisetube.net
i-SCOPE - interoperable Smart City services through an Open Platform for urban Ecosystems
UC: NoiseTube – Citizen Participation
http://www.noisetube.net
i-SCOPE - interoperable Smart City services through an Open Platform for urban Ecosystems
Individual Measurement Sessions Post-Processed Aggregated Model Noise Exposure
UC: NoiseTube – Visualising Noise Exposure
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Result
Location
Time
Ancillary Info
Feature of Interest
Post-processing
Error removal
Noise values
Parameter
Summary Stats/ Aggregation
Model
What was measured?
User SensorInformation
RequirementsHow was it measured?
Noise ExposureMeasurement
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Noise Measurements Model
Objective: Extend existing models where possible
Candidate Application Schema:Observations and Measurements
ISO 19156: Observations and Measurements
INSPIRE Observations – Specialised Observations:Point, Trajectory and Gridded Observations
Procedures OGC SensorML 2.0
INSPIRE Observations - Process
Results OGC Coverages 2.0
OGC WaterML 2.0 - TimeSeries
OGC SWE Common
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12
OM_Observation: an EVENT whose RESULT is an estimate of a value of some PROPERTY of some THING obtained using a specified
PROCEDURE …
ISO19156 Observations and Measurements
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Result
Location
Time
Ancillary Info
Feature of Interest
Post-processing
Error removal
Noise values
Parameter
Summary Stats/ Aggregation
Model
What was measured?
User SensorInformation
RequirementsHow was it measured?
Noise ExposureMeasurement
result
featureOfInterest
observedProperty
procedureprocedure
result
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Profiling ISO19156 Observations and Measurements
14
ISO 19156 ‘Observations and measurements’ provides a generic framework for describing both the observing event and the results of the observation. It is applicable
to a wide range of scientific and technical domains.
The generic nature of this standard means that it requires further specialisation to constrain aspects of the model …
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INSPIRE Specialised ObservationsProfiling ISO19156 Observations and Measurements
Defines 3 types of Specialised Observation based on the Result Type. These extend the example ISO 19156 specialised observations:
• Gridded Observation
• Trajectory or Profile Observations
• Point Observations
INSPIRE Specialised Observations constrain
the result, featureOfInterest and
phenomenonTime
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• Result is an Any type – so...it can be anything!
Encoding the Observation Result
Not easy to implement or ensure
consistency
....Need to define what type to use in your Application Schema
INSPIRE Specialised Observation
Result Type Implementation Schema
PointObservation DiscretePointCoverage OGC Coverages 2.0
PointTimeSeriesObservation TimeSeries OGC WaterML 2.0
MultiPointObservation MultiPointCoverage OGC Coverages 2.0
ProfileObservation RectifiedGridCoverage or ReferencableGridCoverage
OGC Coverages 2.0
TrajectoryObservation TimeSeries OGC WaterML 2.0
GridObservation RectifiedGridCoverage or ReferencableGridCoverage
OGC Coverages 2.0
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• Result is an Any type – so...it can be anything!
Encoding the Observation Result
Not easy to implement or ensure
consistency
....Need to define what type to use in your Application Schema
INSPIRE Specialised Observation
Result Type Implementation Schema
PointObservation DiscretePointCoverage OGC Coverages 2.0
PointTimeSeriesObservation TimeSeries OGC WaterML 2.0
MultiPointObservation MultiPointCoverage OGC Coverages 2.0
ProfileObservation RectifiedGridCoverage or ReferencableGridCoverage
OGC Coverages 2.0
TrajectoryObservation TimeSeries OGC WaterML 2.0
GridObservation RectifiedGridCoverage or ReferencableGridCoverage
OGC Coverages 2.0
Question: Should Noise Measurements re-use/extend INSPIRE Specialised Observations?
Recommendation - YES
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Procedures: OGC SensorML and INSPIRE Process
SensorML is a comprehensive, generic model for describing the processes used to estimate the value
of a phenomenon using a sensor
• A measurement process can be described within an external resource and referenced to in the Observation
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Procedures: OGC SensorML and INSPIRE Process
INSPIRE Observation – Process is intended to provide an alternative lightweight model for describing the procedure compared to SensorML
class Process
«featureType»Process
«voidable»+ documentation :DocumentCitation [0..*]+ inspireld :Identifier+ name :CharacterString [0..1]+ processParameter :ProcessParameter [0..*]+ responsibleParty :RelatedParty [1..*]+ type :CharacterString
«FeatureType»observation::OM_Process
observ ation::OM_Observ ation
+ phenomenonTime :TM_Object+ resultTime :TM_Instant+ validTime :TM_Period [0..1]+ resultQuality :DQ_Element [0..*]+ parameter :NamedValue [0..*]
Base Types 2::DocumentCitation
+ name :CharacterString
+ shortName :CharacterString [0..1]+ date :CI_Date+ link :URL [1..*]+ specificReference :CharacterString [0..*]
«dataType»ProcessParameter
+ description :CharacterString [0..1]+ name :ProcessParameterNameValue
ProcessParameterNameValue
tagsasDictionary = trueextensibility = anyvocabulary = xsdEncodingRule = iso19136_2007_INSPIRE_Extensions
0..*
+relatedObservation 0..*
+generatedObservation
0..*
ProcessUsed +procedure
1
class Process
Process
+ documentation :DocumentCitation [0..*]+ inspireld :Identifier+ name :CharacterString [0..1]+ processParameter :ProcessParameter [0..*]+ responsibleParty :RelatedParty [1..*]+ type :CharacterString
observation::OM_Process
observ ation::OM_Observ ation
+ phenomenonTime :TM_Object+ resultTime :TM_Instant+ validTime :TM_Period [0..1]+ resultQuality :DQ_Element [0..*]+ parameter :NamedValue [0..*]
Base Types 2::DocumentCitation
+ name :CharacterString
«voidable»+ shortName :CharacterString [0..1]+ date :CI_Date+ link :URL [1..*]+ specificReference :CharacterString [0..*]
ProcessParameter
+ description :CharacterString [0..1]+ name :ProcessParameterNameValue
«codeList»ProcessParameterNameValue
tagsasDictionary = trueextensibility = anyvocabulary = xsdEncodingRule = iso19136_2007_INSPIRE_Extensions
0..*
+relatedObservation 0..*
+generatedObservation
0..*
ProcessUsed +procedure
1
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Procedures: SensorML and INSPIRE Process
INSPIRE Observation – Process is intended to provide an alternative lightweight model for describing the procedure compared to SensorML
class Process
«featureType»Process
«voidable»+ documentation :DocumentCitation [0..*]+ inspireld :Identifier+ name :CharacterString [0..1]+ processParameter :ProcessParameter [0..*]+ responsibleParty :RelatedParty [1..*]+ type :CharacterString
«FeatureType»observation::OM_Process
observ ation::OM_Observ ation
+ phenomenonTime :TM_Object+ resultTime :TM_Instant+ validTime :TM_Period [0..1]+ resultQuality :DQ_Element [0..*]+ parameter :NamedValue [0..*]
Base Types 2::DocumentCitation
+ name :CharacterString
+ shortName :CharacterString [0..1]+ date :CI_Date+ link :URL [1..*]+ specificReference :CharacterString [0..*]
«dataType»ProcessParameter
+ description :CharacterString [0..1]+ name :ProcessParameterNameValue
ProcessParameterNameValue
tagsasDictionary = trueextensibility = anyvocabulary = xsdEncodingRule = iso19136_2007_INSPIRE_Extensions
0..*
+relatedObservation 0..*
+generatedObservation
0..*
ProcessUsed +procedure
1
class Process
Process
+ documentation :DocumentCitation [0..*]+ inspireld :Identifier+ name :CharacterString [0..1]+ processParameter :ProcessParameter [0..*]+ responsibleParty :RelatedParty [1..*]+ type :CharacterString
observation::OM_Process
observ ation::OM_Observ ation
+ phenomenonTime :TM_Object+ resultTime :TM_Instant+ validTime :TM_Period [0..1]+ resultQuality :DQ_Element [0..*]+ parameter :NamedValue [0..*]
Base Types 2::DocumentCitation
+ name :CharacterString
«voidable»+ shortName :CharacterString [0..1]+ date :CI_Date+ link :URL [1..*]+ specificReference :CharacterString [0..*]
ProcessParameter
+ description :CharacterString [0..1]+ name :ProcessParameterNameValue
«codeList»ProcessParameterNameValue
tagsasDictionary = trueextensibility = anyvocabulary = xsdEncodingRule = iso19136_2007_INSPIRE_Extensions
0..*
+relatedObservation 0..*
+generatedObservation
0..*
ProcessUsed +procedure
1
Recommendation 1 – Use SensorML for describing Sensor Systems:
• It is more mature and comprehensive• Provides flexibility in the depth of info you can provide
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Proposed Noise Measurements Model
• Two data exchange requirements: – Source noise exposure measurements– Aggregated/modelled noise exposure measurements
1. Source noise exposure measurements:– Time series collected at mobile locations (NoiseTube)
– Need to extend to include summary statistics
Recommendation 1 – Use INSPIRE Specialised Observation – Trajectory Observation
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NoiseTrajectoryObservation class Context Diagram: NoiseTrajectoryObserv ation
TimeSeries Result for TrajectoryObservation
TimeSeries Result for TrajectoryObservation
SamplingCoverageObservation
«featureType»Trajectory and Profile Observ ations::
TrajectoryObserv ation
«featureType»NoiseTrajectoryObserv ation
«DataType»NoiseTubeStatistics
+ count :Integer+ lengthOfTrack :Length+ maxLAeq :Measure+ meanLAeq :Measure+ minLAeq :Measure
constraints{UoM of maxLAeq shall be given in dBA}{UoM of minLAeq shall be given in dBA}{UoM of meanLAeq shall be given in dBA}
«dataType»Trajectory and Profile
Observ ations::TimeLocationValueTriple
+ location :GM_Position
«DataType»SummaryStatistics
CVT_TimeInstantValuePair
«DataType»Timeseries::
AnnotatedTimeValuePair
+ geometry :TM_Position+ value :Record
CVT_DiscreteTimeInstantCoverage
«Type»Timeseries::Timeseries
+ temporalExtent :TM_Period
Constraints for INSPIRE Specialised Observ ation - Trajectory Observ ation
1. result must be a TimeSeries2. each point in the result must be a
TimeLocationValueTriple3. phenomenonTime must be a TM_Period4. featureOfInterest must be a
SF_SamplingCurve
NOTE: A Specialised NoiseTrajectoryObservation has been developed to support the requirements of the NoiseTube application to include the summary statistics that are automatically calculated from the measurement set.
+summaryStatistics 0..1
+collection 0..*
+point 0..*
NOTE: a SF_SamplingCurve feature must also be generated representing the trajectory
For an aggregated/modelled trajectory observation the INSPIRE TrajectoryObservation should be
used
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2. Aggregated/modelled noise exposure measurements• Post-processing modelling may generate generalised noise exposure
measurements for an area of interest:– Regular gridded data – overlay over terrain model or city model
– Around Road, Rail, Airport, Industry (see Noise Mapping Model)
Proposed Noise Measurements Model
Recommendation 1 – Use INSPIRE Specialised Observation – Grid Observation
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class Context Diagram: Gridded Noise Observ ation
Grid Observation Result - INSPIRE RectifiedGridCoverage
«featureType»Gridded Observ ations::
GridObserv ation
«FeatureType»Sampling Cov erage Observ ation::
SamplingCov erageObserv ation
«FeatureType»cov erageObserv ation::
OM_DiscreteCov erageObserv ation
«FeatureType»observ ation::OM_Observ ation
Constraints for INSPIRE Grid Observation:
1. The Result shall be a RectifiedGridCoverage2. phenomenonTime must be a TM_Instant3. featureOfInterest must be a SF_SamplingSolid or
SF_SamplingSurface
«featureType»Cov erages (Domain and Range)::
RectifiedGridCov erage
constraints{domainIsRectifiedGrid}{grid points shall coincide with grid cell centres}
«featureType»Coverages (Domain and Range)::
CoverageByDomainAndRange
+ coverageFunction :CoverageFunction [0..1]+ domainSet :Any+ rangeSet :Any [0..*] {ordered}
«union»Cov erages (Domain and Range)::
Cov erageFunction
+ ruleDefinition :CharacterString+ ruleReference :URI+ gridFunction :GridFunction
«featureType»Coverages (Base)::Coverage
+ metadata :Any [0..*]+ rangeType :RecordType
«dataType»Cov erages (Domain and Range)::GridFunction
+ sequenceRule :CV_SequenceRule [0..1]+ startPoint :Integer [0..*] {ordered}
NOTE: The GridObservation shall be directly imported from the INSPIRE Coverage Model without any addition extensions for Noise.
GridObservation
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Noise Modelling
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Strategic Noise Mapping (END Directive)
Noise Modelling
Inputs Modelling Process Output
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• Inputs for modelling road noise exposure
– Digital Terrain Model (10m grid)– Population
Noise Modelling
Traffic Roads Buildings/Furniture Noise Exposure
Traffic flow surface Material Reflectivity facades Lden
% Heavy Vehicles gradient height Lday
Speed limits width Noise barriers Levening
Lnight
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CityGML 2.0 Noise ADECandidate Application Schema• Noise ADE developed as an example ADE in CityGML 2.0
specification pkg Package Diagram: CityGML Noise ADE
«leaf»NoiseBuilding
+ Building
(from Noise_ADE)
«leaf»NoiseCityFurniture
+ CityFurniture
+ NoiseCityFurnitureSegment
+ NoiseCityFurnitureSegmentType
(from Noise_ADE)
«leaf»NoiseRoad
+ NoiseRailwaySegment
+ NoiseRoadSegment
+ Railway
+ Road
+ Train
(from Noise_ADE)
«applicationSchema»Noise_ADE
+ NoiseBuilding
+ NoiseCityFurniture
+ NoiseRoad
(from CityGML_ADE)
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BuildingsCityGML 2.0 Noise ADE
class Context Diagram - Noise Simulation Inputs - Buildings
«ADEElement»NoiseBuilding::Building
+ buildingReflection :CharacterString [0..1]+ buildingReflectionCorrection :Measure [0..1]+ buildingLDenMax :Measure [0..1]+ buildingLDenMin :Measure [0..1]+ buildingLNightMax :Measure [0..1]+ buildingLNightMin :Measure [0..1]+ buildingLDenEq :Measure [0..1]+ buildingLNightEq :Measure [0..1]+ buildingHabitants :NonNegativeInteger [0..1]+ buildingAppartments :NonNegativeInteger [0..1]+ buildingImmissionPoints :IntegerList [0..1]+ remark :CharacterString [0..1]
AbstractSite
«featureType»Building::AbstractBuilding
+ class :BuildingClass [0..1]+ function :BuildingFunction [0..*]+ usage :BuildingUsage [0..*]+ yearOfConstruction :Year [0..1]+ yearOfDemolition :Year [0..1]+ roofType :RoofType [0..1]+ measuredHeight :Length [0..1]+ storeysAboveGround :int [0..1]+ storeysBelowGround :int [0..1]+ storeyHeightsAboveGround :MeasureList [0..1]+ storeyHeightsBelowGround :MeasureList [0..1]+ lod0FootPrint :GM_MultiSurface [0..1]+ lod0RoofEdge :GM_MultiSurface [0..1]+ lod1Solid :GM_Solid [0..1]+ lod1MultiSurface :GM_MultiSurface [0..1]+ lod1TerrainIntersection :GM_MultiCurve [0..1]+ lod2Solid :GM_Solid [0..1]+ lod2MultiSurface :GM_MultiSurface [0..1]+ lod2MultiCurve :GM_MultiCurve [0..1]+ lod2TerrainIntersection :GM_MultiCurve [0..1]+ lod3Solid :GM_Solid [0..1]+ lod3MultiSurface :GM_MultiSurface [0..1]+ lod3MultiCurve :GM_MultiCurve [0..1]+ lod3TerrainIntersection :GM_MultiCurve [0..1]+ lod4Solid :GM_Solid [0..1]+ lod4MultiSurface :GM_Surface [0..1]+ lod4MultiCurve :GM_MultiCurve [0..1]+ lod4TerrainIntersection :GM_MultiCurve [0..1]
Issues identified with the existing Noise ADE:
1. The Building ADEElement class should generalise the CityGML Building object not AbstractBuilding
2. The attribute names could be made more succinct by removing the 'building' prefixes
3. buildingAppartments contains a spelling mistake4. Attributes such as buildingReflection should use a codelist rather than
CharacterString to ensure consistency.
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TransportCityGML 2.0 Noise ADE
class Context Diagram: Noise Simulation Input - Road and Railway
«ADEElement»NoiseRoad::Railway
«ADEElement»NoiseRoad::Road
AbstractTransportationObject
«featureType»NoiseRoad::NoiseRoadSegment
+ mDay :Measure [0..1]+ mEvening :Measure [0..1]+ mNight :Measure [0..1]+ mDay16 :Measure [0..1]+ pDay :Measure [0..1]+ pEvening :Measure [0..1]+ pNight :Measure [0..1]+ pDay16 :Measure [0..1]+ dtv :Measure [0..1]+ speedDayPkw :Speed [0..1]+ speedEveningPkw :Speed [0..1]+ speedNightPkw :Speed [0..1]+ speedDayLkw :Speed [0..1]+ speedEveningLkw :Speed [0..1]+ speedNightLkw :Speed [0..1]+ roadSurfaceMaterial :CharacterString [0..1]+ roadSurfaceCorrection :Measure [0..1]+ distanceCarriageway :Length [0..1]+ distanceD :Length [0..1]+ bridge :boolean [0..1]+ tunnel :boolean [0..1]+ roadGradientPercent :Measure [0..1]+ lod0BaseLine :GM_Curve [0..1]+ l ineage :CharacterString [0..1]
AbstractTransportationObject
«featureType»NoiseRoad::NoiseRailwaySegment
+ railwaySurfaceMaterial :CharacterString [0..1]+ railwafSurfaceCorrection :Measure [0..1]+ bridge :boolean [0..1]+ crossing :boolean [0..1]+ curveRadius :Length [0..1]+ additionalCorrectionSegment :Measure [0..1]+ lod0BaseLine :GM_Curve [0..1]
«featureType»NoiseRoad::Train
+ trainType :CharacterString [0..1]+ trainTypeCorrection :Measure [0..1]+ brakePortionDay :Measure [0..1]+ brakePortionEvening :Measure [0..1]+ brakePortionNight :Measure [0..1]+ lengthDay :Length [0..1]+ lengthEvening :Length [0..1]+ lengthNight :Length [0..1]+ speedDay :Speed [0..1]+ speedEvening :Speed [0..1]+ speedNight :Speed [0..1]+ additionalCorrectionTrain :Measure [0..1]
«featureType»Transportation::Road
«featureType»Transportation::Railway
AbstractTransportationObject
«featureType»Transportation::TransportationComplex
+ class :TransportationComplexClass [0..1]+ function :TransportationComplexFunction [0..*]+ usage :TransportationComplexUsage [0..*]+ lod0Network :GM_Complex [0..*]+ lod1MultiSurface :GM_Surface [0..1]+ lod2MultiSurface :GM_Surface [0..1]+ lod3MultiSurface :GM_Surface [0..1]+ lod4MultiSurface :GM_Surface [0..1]
Issues identified with the existing Noise ADE:
1. Change the type boolean to Boolean2. Codelists should be used where possible rather than
CharacterString (e.g. surfaceMaterial, train types)3. Is there are requirement for Segments or could the model
be simplified by using Road and Rail features only?
+noiseRailwaySegmentProperty 0..*
+noiseRoadSegmentProperty
0..*
+usedBy
0..*
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City FurnitureCityGML 2.0 Noise ADE class Context Diagram: Noise Simulation Inputs - City Furniture
«ADEElement»NoiseCityFurniture::
CityFurniture
AbstractCityObject
«featureType»NoiseCityFurniture::NoiseCityFurnitureSegment
+ type :NoiseCityFurnitureSegmentType [0..1]+ reflection :CharacterString [0..1]+ reflectionCorrection :Measure [0..1]+ height :Length [0..1]+ distance :Length [0..1]+ lod0BaseLise :GM_Curve [0..1]
«codeList»NoiseCityFurniture::
NoiseCityFurnitureSegmentType
AbstractCityObject
«featureType»CityFurniture::CityFurniture
+ class :CityFurnitureClass [0..1]+ function :CityFurnitureFunction [0..*]+ usage :CityFurnitureUsage [0..*]+ lod1Geometry :GM_Object [0..1]+ lod2Geometry :GM_Object [0..1]+ lod3Geometry :GM_Object [0..1]+ lod4Geometry :GM_Object [0..1]+ lod1TerrainIntersection :GM_MultiCurve [0..1]+ lod2TerrainIntersection :GM_MultiCurve [0..1]+ lod3TerrainIntersection :GM_MultiCurve [0..1]+ lod4TerrainIntersection :GM_MultiCurve [0..1]+ lod1ImplicitRepresentation :core:ImplicitGeometry [0..1]+ lod2ImplicitRepresentation :core:ImplicitGeometry [0..1]+ lod3ImplicitRepresentation :core:ImplicitGeometry [0..1]+ lod4ImplicitRepresentation :core:ImplicitGeometry [0..1]
Issues identified with Noise ADE:
1. Is there a requirement to model CityFurniture using segments or can multiple CityFurniture objects represent a single real-world object (e.g. noise barrier)? This would simplify the model as only has one geometry.
+noiseCityFurnitureSegmentProperty 0..*
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Noise Mapping
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Noise Mapping
END Strategic Noise Mapping:• Enable assessment of exposure of populations to noise• Inform development of action plans to reduce noise exposure and
protect existing quiet areas• inform and engage the public in the development of noise action plans
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END Strategic Noise Maps
• Environmental noise exposure has to be strategically mapped in the following areas: – Agglomerations - large, densely populated urban areas –
(UK: > 250,000 people with a population density of < 500 /km2 )
– Around roads with more than six million vehicle passages a year
– Around railways with more than 60,000 train passages a year
– Around airports with more than 50,000 movements a year
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Noise Exposure Maps
• These are typically thematic maps “Heat Maps”, contours, grids or city objects whose values may be:– Noise Exposure: Laeq (dBA), Lden, Lnight– Statistics: Total or % population exposed
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Candidate Application Schema• Basic overlaying of noise exposure information
– ISO 19156 – Observations and Measurements– OGC Coverages – e.g. RectifiedGridCoverage,
MultiPointCoverage
• Developed Noise Mapping Model:– Contours (Generic)– Generic Models for Time-Varying Properties
• TimeVaryingProperty Model• Heat Map ADE
– City Object – Noise Exposure
Noise Mapping
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• Very simple, generic model consisting of a contour line, contour value and contour property type
Noise Contours
Question: Are any other properties required?
class Noise Contours
«FeatureType»ContourLine
+ geometry :GM_Curve+ contourValue :Measure+ contourPropertyType :ContourPropertyType
«CodeList»ContourPropertyType
tagscodeList = http://www.iscopeproject.net/codeList/ContourPropertyTypeextensibility = anyxsdEncodingRule = citygml-ade
Example values for ContourPropertyType:
Noise Exposure: minLAeq, maxLAeq, meanLAeq, Lden, Lnight etc.....
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• Real-world phenomenon like noise expose vary both over time and space
• Starting point develop a generic model for time-varying properties
Modelling Time-Varying Property
Design Principles:• Needs to be simple• Can be used within for multiple purposes:
• Thematic Noise Mapping “Heat Maps”• City Object Noise Exposure Maps• Other thematic areas: Energy -Solar Potential
• Based on existing O&M Modelling pattern as has similar requirements
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class CityGML ADE: Time Varying Properties
«FeatureType»TimeDependentVariable
+ referenceTime :TM_Object
«metaclass»General Feature Model::
GF_PropertyType{root}
«type»Records and Class
Metadata::Any{root}
Metadata entity set information::MD_Metadata
«FeatureTyp...observation::OM_Process
+phenomenon 1
Metadata
+metadata0..1
Process
+procedure 0..1
+result 1
TimeDependentVariable : has a RESULT which is an estimate of a value of some PROPERTY belonging to a feature obtained using a specified PROCEDURE
…
Modelling Time-Varying Property
NOTE: there is no featureOfInterest as the TimeDependentVariable
is intended to be a complex property of a
feature
NOTE: The multiplicity of procedure and metadata
has been relaxed
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Thematic Heat Map• The Time-Varying Property can be used within a
Thematic Heat Map feature• A HeatMap feature has been developed as a new
CityGML City Object LOD0• 2 Specialised types:
– SurfaceHeatMap– GriddedHeatMap
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Thematic Heat Map class Context Diagram: Heat Maps
«FeatureType»SurfaceHeatMap
+ loD0_Surface :GM_MultiSurface
«type»Records and Class Metadata::
Any{root}
«FeatureType»CityGML ADE: Time Varying
Properties::TimeDependentVariable
+ referenceTime :TM_Object
«metaclass»General Feature Model::
GF_PropertyType{root}
«FeatureType»GriddedHeatMap
constraints{/* result must be a RectifiedGridCoverage */inv: self.result.oclIsKindOf(RectifiedGridCoverage)}
CoverageByDomainAndRange
«featureType»Cov erages (Domain and Range)::
RectifiedGridCov erage
+result 1+phenomenon
1
+result 1
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• Time-varying properties such as Noise Exposure/Solar Potential can be added as thematic attributes to City Objects
Adding Time-Varying Properties to City Objects
• Model should be flexible enough to allow objects to have multiple time-varying properties
• Time-varying properties such as Noise Exposure/Solar Potential can be added as thematic attributes to City Objects
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class Buildings
«ADEEleme...Building
«FeatureType»CityGML ADE: Time Varying
Properties::TimeDependentVariable
+ referenceTime :TM_Object
«metaclass»General Feature Model::
GF_PropertyType{root}
«type»Records and Class Metadata::
Any{root}
AbstractBuilding
«featureType»Building::Building
+noiseExposure 0..*
+phenomenon 1 +result 1
City Object – Noise ExposureExample: Building Noise Exposure
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class Buildings
«ADEEleme...Building
«FeatureType»CityGML ADE: Time Varying
Properties::TimeDependentVariable
+ referenceTime :TM_Object
«metaclass»General Feature Model::
GF_PropertyType{root}
«type»Records and Class Metadata::
Any{root}
AbstractBuilding
«featureType»Building::Building
+noiseExposure 0..*
+phenomenon 1 +result 1
City Object – Noise ExposureExample: Building Noise Exposure
Profiling the Result: • A business rule should be defined for
each time-varying property to constrain the result type
• Result type can be existing record/coverage type:
• SWE Common – Data Array• Coverage
i-SCOPE - interoperable Smart City services through an Open Platform for urban Ecosystems
class Buildings
«ADEEleme...Building
«FeatureType»CityGML ADE: Time Varying
Properties::TimeDependentVariable
+ referenceTime :TM_Object
«metaclass»General Feature Model::
GF_PropertyType{root}
«type»Records and Class Metadata::
Any{root}
AbstractBuilding
«featureType»Building::Building
«Type»NoiseExposureDataRecord
+ minLAeq :Measure+ maxLAeq :Measure+ meanLAeq :Measure
result must be a NoiseExposureDataRecord/* result must be a NoiseExposureDataRecord*/inv: self.result.oclIsKindOf(NoiseExposureDataRecord)
+noiseExposure 0..*
+phenomenon 1 +result 1
City Object – Noise ExposureExample: Building Noise Exposure
Profiling the Result: • A business rule should be defined for
each time-varying property to constrain the result type
• Result type can be existing record/coverage type:
• SWE Common – Data Array• Coverage
• Or, can explicitly define a <<type>> class within the domain model
i-SCOPE - interoperable Smart City services through an Open Platform for urban Ecosystems
Conclusions
• Action 1: Need to share with modelling team to agree proposed generic CityGML ADE for time-varying properties and Heat Map
• Action 2: Noise Domain Expert Review to identify what noise exposure parameters would be published in a heat map or on a City Object– Needed to develop controlled vocabulary of phenomenon– Agree whether SWE Common Data Array would be suitable for
encoding result or define concrete result class
• Action 3: Identify which City Objects would form a Noise Exposure – City Objects ADE