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Noise Domain Model:
Measurements, Modelling and Mapping
Debbie Wilson – Snowflake Software
(on behalf Ordnance Survey)
Overview
• Following slides provide a detailed summary
description of the Noise Domain Model
• Measurements
• Modelling
• ...
Noise Domain Model
• Develop a model that meets the requirements for:
– Open Data Exchange
– 2D and 3D Visualisation
• App...
Noise Domain Model
Measurement Modelling Mapping
Ancillary data:
needed as input to
noise simulation
modelling
3 Viewpoint...
Noise Measurements
UC: NoiseTube – Citizen Participation
Noise Measurements
http://www.noisetube.net
UC: NoiseTube – Citizen Participation
http://www.noisetube.net
UC: NoiseTube – Citizen Participation
http://www.noisetube.net
Individual Measurement Sessions Post-Processed Aggregated Model
Noise Exposure
UC: NoiseTube – Visualising Noise Exposure
Result
Location
Time
Ancillary
Info
Feature of
Interest
Post-
processing
Error
removal
Noise
values
Parameter
Summary Stat...
Noise Measurements Model
Objective: Extend existing models where possible
Candidate Application Schema:
Observations and
M...
12
OM_Observation: an EVENT whose RESULT is an estimate of a value
of some PROPERTY of some THING obtained using a specifi...
Result
Location
Time
Ancillary
Info
Feature of
Interest
Post-
processing
Error
removal
Noise
values
Parameter
Summary Stat...
Profiling ISO19156 Observations and Measurements
14
ISO 19156 ‘Observations and measurements’ provides a generic framework...
INSPIRE Specialised Observations
Profiling ISO19156 Observations and Measurements
Defines 3 types of Specialised Observati...
• Result is an Any type – so...it can be anything!
Encoding the Observation Result
Not easy to
implement or ensure
consist...
• Result is an Any type – so...it can be anything!
Encoding the Observation Result
Not easy to
implement or ensure
consist...
Procedures: OGC SensorML and INSPIRE Process
SensorML is a comprehensive, generic model for
describing the processes used ...
Procedures: OGC SensorML and INSPIRE Process
INSPIRE Observation – Process is intended to provide an alternative
lightweig...
Procedures: SensorML and INSPIRE Process
INSPIRE Observation – Process is intended to provide an alternative
lightweight m...
Proposed Noise Measurements Model
• Two data exchange requirements:
– Source noise exposure measurements
– Aggregated/mode...
NoiseTrajectoryObservation
class Context Diagram: NoiseTrajectoryObservation
TimeSeries Result for Trajectory
Observation
...
2. Aggregated/modelled noise exposure measurements
• Post-processing modelling may generate generalised noise exposure
mea...
class Context Diagram: Gridded Noise Observation
Grid Observation Result - INSPIRE RectifiedGridCoverage
«featureType»
Gri...
Noise Modelling
Strategic Noise Mapping (END Directive)
Noise Modelling
Inputs Modelling Process Output
• Inputs for modelling road noise exposure
– Digital Terrain Model (10m grid)
– Population
Noise Modelling
Traffic Roads B...
CityGML 2.0 Noise ADE
Candidate Application Schema
• Noise ADE developed as an example ADE in CityGML 2.0
specification
Buildings
CityGML 2.0 Noise ADE
class Context Diagram - Noise Simulation Inputs - Buildings
«ADEElement»
NoiseBuilding::Bu...
Transport
CityGML 2.0 Noise ADE
class Context Diagram: Noise Simulation Input - Road and Railway
«ADEElement»
NoiseRoad::R...
City Furniture
CityGML 2.0 Noise ADEclass Context Diagram: Noise Simulation Inputs - City Furniture
«ADEElement»
NoiseCity...
Noise Mapping
Noise Mapping
END Strategic Noise Mapping:
• Enable assessment of exposure of populations to noise
• Inform development of...
END Strategic Noise Maps
• Environmental noise exposure has to be strategically
mapped in the following areas:
– Agglomera...
Noise Exposure Maps
• These are typically thematic maps “Heat Maps”,
contours, grids or city objects whose values may be:
...
Candidate Application Schema
• Basic overlaying of noise exposure information
– ISO 19156 – Observations and Measurements
...
• Very simple, generic model consisting of a contour
line, contour value and contour property type
Noise Contours
Question...
• Real-world phenomenon like noise expose vary both
over time and space
• Starting point develop a generic model for time-...
class CityGML ADE: Time Varying Properties
«FeatureType»
TimeDependentVariable
+ referenceTime :TM_Object
«metaclass»
Gene...
Thematic Heat Map
• The Time-Varying Property can be used within a
Thematic Heat Map feature
• A HeatMap feature has been ...
Thematic Heat Mapclass Context Diagram: Heat Maps
«FeatureType»
SurfaceHeatMap
+ loD0_Surface :GM_MultiSurface
«type»
Reco...
• Time-varying properties such as Noise
Exposure/Solar Potential can be added as thematic
attributes to City Objects
Addin...
class Buildings
«ADEEleme...
Building
«FeatureType»
CityGML ADE: Time Varying
Properties::
TimeDependentVariable
+ referen...
class Buildings
«ADEEleme...
Building
«FeatureType»
CityGML ADE: Time Varying
Properties::
TimeDependentVariable
+ referen...
class Buildings
«ADEEleme...
Building
«FeatureType»
CityGML ADE: Time Varying
Properties::
TimeDependentVariable
+ referen...
Conclusions
• Action 1: Need to share with modelling team to agree
proposed generic CityGML ADE for time-varying propertie...
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I scope noisemodel

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  • The Noise Domain Model needs to take into account three different viewpoints:Source Measurements of Noise Pollution plus ancillary data inputs (e.g. Road surface material/condition, speed limits, average amount and type of transport). These are required as inputs into.....Models – these can be simple algorithms such aggregation/generalisation to produce summary statistics to complex noise simulation modellingEstimated Noise Exposure: the result of noise measurement and modelling are estimates of noise exposure which can then be visualised in 2D and 3D for decision making
  • Transcript of "I scope noisemodel"

    1. 1. Noise Domain Model: Measurements, Modelling and Mapping Debbie Wilson – Snowflake Software (on behalf Ordnance Survey)
    2. 2. 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
    3. 3. 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)
    4. 4. Noise Domain Model Measurement Modelling Mapping Ancillary data: needed as input to noise simulation modelling 3 Viewpoints:
    5. 5. Noise Measurements
    6. 6. UC: NoiseTube – Citizen Participation Noise Measurements http://www.noisetube.net
    7. 7. UC: NoiseTube – Citizen Participation http://www.noisetube.net
    8. 8. UC: NoiseTube – Citizen Participation http://www.noisetube.net
    9. 9. Individual Measurement Sessions Post-Processed Aggregated Model Noise Exposure UC: NoiseTube – Visualising Noise Exposure
    10. 10. Result Location Time Ancillary Info Feature of Interest Post- processing Error removal Noise values Parameter Summary Stats/ Aggregation Model What was measured? User SensorInformation Requirements How was it measured? Noise Exposure Measurement
    11. 11. 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
    12. 12. 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
    13. 13. Result Location Time Ancillary Info Feature of Interest Post- processing Error removal Noise values Parameter Summary Stats/ Aggregation Model What was measured? User SensorInformation Requirements How was it measured? Noise Exposure Measurement result featureOfInterest observedProperty procedureprocedure result
    14. 14. 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 …
    15. 15. INSPIRE Specialised Observations Profiling 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
    16. 16. • 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
    17. 17. • 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
    18. 18. 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
    19. 19. Procedures: OGC SensorML and INSPIRE Process INSPIRE Observation – Process is intended to provide an alternative lightweight model for describing the procedure compared to SensorML «featureType» Process «voidable» + documentation :DocumentCitation [0..*] + inspireld :Identifier + name :CharacterString [0..1] + processParameter :ProcessParameter [0..*] + responsibleParty :RelatedParty [1..*] + type :CharacterString «FeatureType» observation::OM_Process «dataType» ProcessParameter + description :CharacterString [0..1] + name :ProcessParameterNameValue s +generatedObservation 0..* ProcessUsed +procedure 1 class Process «voidable + docum + inspire + name + proce + respon + type «FeatureType» observation::OM_Observation + 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..*] + d + n «codeList» ProcessParameterNameValue tags asDictionary = true extensibility = any vocabulary = xsdEncodingRule = iso19136_2007_INSPIRE_Extensions 0..* +relatedObservation 0..* +generatedObservation 0..* ProcessUsed +proced
    20. 20. Procedures: SensorML and INSPIRE Process INSPIRE Observation – Process is intended to provide an alternative lightweight model for describing the procedure compared to SensorML «featureType» Process «voidable» + documentation :DocumentCitation [0..*] + inspireld :Identifier + name :CharacterString [0..1] + processParameter :ProcessParameter [0..*] + responsibleParty :RelatedParty [1..*] + type :CharacterString «FeatureType» observation::OM_Process «dataType» ProcessParameter + description :CharacterString [0..1] + name :ProcessParameterNameValue s +generatedObservation 0..* ProcessUsed +procedure 1 class Process «voidable + docum + inspire + name + proce + respon + type «FeatureType» observation::OM_Observation + 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..*] + d + n «codeList» ProcessParameterNameValue tags asDictionary = true extensibility = any vocabulary = xsdEncodingRule = iso19136_2007_INSPIRE_Extensions 0..* +relatedObservation 0..* +generatedObservation 0..* ProcessUsed +proced Recommendation 1 – Use SensorML for describing Sensor Systems: • It is more mature and comprehensive • Provides flexibility in the depth of info you can provide
    21. 21. 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
    22. 22. NoiseTrajectoryObservation class Context Diagram: NoiseTrajectoryObservation TimeSeries Result for Trajectory Observation TimeSeries Result for Trajectory Observation SamplingCoverageObservation «featureType» Trajectory and Profile Observations:: TrajectoryObservation «featureType» NoiseTrajectoryObservation «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 Observations:: 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 Observation - Trajectory Observation 1. result must be a TimeSeries 2. each point in the result must be a TimeLocationValueTriple 3. phenomenonTime must be a TM_Period 4. featureOfInterest must be a SF_SamplingCurve NOTE: A Specialised NoiseTrajectoryObservation has been developed to support the requirements of the NoiseTube +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
    23. 23. 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
    24. 24. class Context Diagram: Gridded Noise Observation Grid Observation Result - INSPIRE RectifiedGridCoverage «featureType» Gridded Observations:: GridObservation «FeatureType» Sampling Coverage Observation:: SamplingCoverageObservation «FeatureType» coverageObservation:: OM_DiscreteCoverageObservation «FeatureType» observation::OM_Observation Constraints for INSPIRE Grid Observation: 1. The Result shall be a RectifiedGridCoverage 2. phenomenonTime must be a TM_Instant 3. featureOfInterest must be a SF_SamplingSolid or SF_SamplingSurface «featureType» Coverages (Domain and Range):: RectifiedGridCoverage 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» Coverages (Domain and Range):: CoverageFunction + ruleDefinition :CharacterString + ruleReference :URI + gridFunction :GridFunction «featureType» Coverages (Base)::Coverage + metadata :Any [0..*] + rangeType :RecordType «dataType» Coverages (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
    25. 25. Noise Modelling
    26. 26. Strategic Noise Mapping (END Directive) Noise Modelling Inputs Modelling Process Output
    27. 27. • 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
    28. 28. CityGML 2.0 Noise ADE Candidate Application Schema • Noise ADE developed as an example ADE in CityGML 2.0 specification
    29. 29. Buildings CityGML 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 mistake 4. Attributes such as buildingReflection should use a codelist rather than CharacterString to ensure consistency.
    30. 30. Transport CityGML 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] + lineage :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 Boolean 2. 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..*
    31. 31. City Furniture CityGML 2.0 Noise ADEclass 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..*
    32. 32. Noise Mapping
    33. 33. 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
    34. 34. 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
    35. 35. 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
    36. 36. 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
    37. 37. • 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 tags codeList = http://www.iscopeproject.net/codeList/ContourPropertyType extensibility = any xsdEncodingRule = citygml-ade Example values for ContourPropertyType: Noise Exposure: minLAeq, maxLAeq, meanLAeq, Lden, Lnight etc.....
    38. 38. • 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
    39. 39. 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 +metadata 0..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
    40. 40. 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
    41. 41. Thematic Heat Mapclass 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» Coverages (Domain and Range):: RectifiedGridCoverage +result 1 +phenomenon 1 +result 1
    42. 42. • 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
    43. 43. 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 Exposure Example: Building Noise Exposure
    44. 44. 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 Exposure Example: 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
    45. 45. 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 Exposure Example: 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
    46. 46. 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
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