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Cadastral Data Modelling

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What are the Advantages and Disadvantages of non-survey accurate DCDB? ... along with restrictions, most commonly caveats, mortgages and rights of way. ... – PowerPoint PPT presentation

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Title: Cadastral Data Modelling


1
Cadastral Data Modelling
  • Mohsen Kalantari
  • Land Administration - 2008

2
Lecture Overview
  • What is data modelling?
  • Importance of data modelling
  • Data modelling for data capture
  • Isolated vs Coordinated (Integrated) Surveys
  • Data modelling for database design
  • Digital Cadastral Databases (DCDBs)
  • Data modelling for cataloging purposes
  • What is recorded in a DCDB?
  • Data modelling for exchange of DCDBs
  • Exchange language for maintenance of the DCDB
  • Victorian DCDB
  • Other DCDB examples
  • Current core cadastral data model
  • A new cadastral data model

3
What is data modelling?
  • The database is specified by a data model
    describing what sort of data will be held, and
    how it will be organized.

Land Parcel Property
Rights
Person
4
What is data modelling?
  • Data modelling is a Design activity like
    architecture. Do not expect to find a single
    correct answer.
  • The requirement of data modelling process are
    flexible enough to accommodate a variety of
    different solutions, try to be Creative, then you
    will always have Choices.
  • Data modelling is NOT data analysis, the
    difference is like prescription versus
    description.

5
Why is the data model so Important?
  • A small change to the data model may have a major
    impact on the system
  • Example Spatial and non-spatial identifiers
  • The program design heavily depends on data
    modelling
  • Example Network analysis needs topology
  • A well designed data model can make programming
    simpler and cheaper
  • Example Automatic adjustment of parcel
    boundaries facilitates calculation of a parcel
    area
  • Poor data organization is often expensive to fix
  • Automatic accuracy check
  • A very powerful tool for expressing and
    communicating business requirements. It can take
    us more directly to the heart of the business
    requirements.

6
Data Modelling Approaches
  • Function Driven
  • Focuses on function specification
  • Example e-conveyancing , digital signature,
    financial settlement
  • Data Driven
  • Emphases on developing data model before detailed
    function
  • Example digital cadastral database
  • Prototyping
  • Cut and try approach dont waste the time build
    , show, modify, show it again

7
Data Modelling
  • The most common alternative approaches to data
    modelling are the
  • entity relationship (E-R) and
  • the object oriented approach .

8
Entity-Relationship
  • The E-R data model views the real world as a set
    of basic entities and relationships among these
    objects.
  • An entity is an object that exists and is
    distinguishable from other objects and a
    relationship is an association between several
    entities.

Area
Land Parcel
Belongs
Owner
ID
9
Object Oriented
  • A core object-oriented data model consists of
    object and object identifier, object attributes
    and methods and classes.
  • In the object oriented approach any real world
    entity is uniformly modelled as an object (eg.
    land parcel), every object has a state (eg.
    rights associated) and behaviour (eg. area).
  • Objects are then organised through classes as a
    means of grouping all the objects which share the
    same set of attributes and methods (eg. building
    belongs to the property class).

10
Object Oriented
Owner Name
Property Value Use
Land Parcel Rights in Land Area
Building Type
11
Role of Cadastral Data Model
12
Data modelling and Data Capture
  • Isolated Survey Approach
  • Isolated parcel surveys, connected but not fully
    integrated to neighboring parcels
  • Graphical Accuracy only
  • Usually a mix of survey accuracy to map accuracy
    as a result of digitisation of original base maps
  • Most common form of cadastre across Australian
    States and Territories (with exception ACT)

13
Data modelling and Data Capture
  • Isolated survey data model

14
Data modelling and Data Capture
  • Coordinated Survey Approach
  • Integrated parcel surveys support a coordinated
    cadastre
  • Survey accuracy, where a parcel survey
    incorporates surrounding parcels and are fully
    tied into each other
  • a Survey Accurate DCDB is based on coordinates
    determined by ground surveys which are used to
    define, describe and re-define parcel boundaries.
    For all practical purposes, the coordinates in
    this DCDB are the true coordinates result is a
    fully coordinated survey system

15
Data modelling and Data Capture
Coordinated survey data model
16
Graphical vs. Survey Accurate Cadastre
  • Level of accuracy is usually survey accuracy
  • Isolated Survey Approach leads to a non-survey
    accurate DCDB
  • Coordinated Survey Approach leads to a survey
    accurate DCDB which in turn supports a
    coordinated cadastre
  • What are the Advantages and Disadvantages of
    non-survey accurate DCDB?
  • What are the Advantages and Disadvantages of a
    survey accurate DCDB?

17
Graphical vs. Survey Accurate Cadastre
  • Non-Survey Accurate (Graphical) DCDB
  • Common approach in Australia
  • Less required to setup/maintain DCDB
  • More time to complete surveys (less connection to
    neighbouring parcels) but need to re-establish
    parcel nearly every time and connect to geodetic
    control
  • Inappropriate use of non-accurate cadastral
    dataset
  • Survey Accurate DCDB
  • More required to setup/maintain DCDB (up to
    Billions)
  • More time to perform initial survey, however very
    little work required to re-do same parcel
  • Value-added potential of accurate cadastral
    dataset

18
Data Modelling and Cadastral Databases
  • Representation of the geometric component of a
    cadastre in electronic format is termed Digital
    Cadastral Database (DCDB)

19
Data Modelling and Cadastral Databases
The physical designer sometimes is not able to
meet performance requirements, so logical
database design is not direct equivalent of the
data model
Selected Relations between Data
Logical Database Design
Program
data
Data Model
Physical Database Design
20
Data Modelling and Cadastral Databases
  • The performance of the information system is
    primarily the responsibility of physical
    designer
  • But the alternative to improve the performance
    might be to modify the data model

21
Data Modelling and Data Catalogue
  • Consists
  • Parcel boundaries
  • Easements
  • Other Additional Contents
  • Property boundaries
  • Building footprints
  • Street addresses
  • Administrative boundaries
  • Valuation
  • Other land use features (garden, roads, railway
    lines, forest, etc.)

22
Data modelling and Data Exchange
Data model in UML
Data model in exchange format
Convert
Switzerland cadastral data model - Interlis
23
Data modelling and Data Exchange
Step 3 Validation and locking. Step 4
Making new state active after decision
Step 1 Selecting parcels
Export to XML
Step 2 Import from XML
software
Modify
24
Updating of DCDBs
  • Subdivisions are charted in LTO's (Land Registry)
    on an index map
  • Update of the DCDB refers to those processes
    that ensure that all new and existing legal
    subdivisions are recorded, ie. the cadastral map
    or DCDB is up-to-date
  • Specifically this should include
  • Recording all new legal subdivisions
  • Ensuring map completeness

25
Upgrading of DCDBs
  • Upgrade activities (an improvement, not
    maintenance)
  • increase accuracy
  • inclusion of survey measurements
  • alignment of cadastral features with topographic
    features
  • changes in data model
  • generation of topological structures
  • inclusion of historical layer
  • unique identifiers for spatial entities

26
Historical Perspective of Australian
State/Territory DCDBs
  • Digistised from best available paper maps
  • Urban, Rural and Metro
  • varying accuracy
  • /- 0.5m - 2m in Urban Metro areas
  • /- 20m or more in Rural areas
  • sourced from different bodies
  • different data emphasis

27
Observations of Australian State/Territory Data
Model
  • Australia wide cadastral coverage, varying
    accuracy
  • Data models are mostly based on graphical
    cadastre
  • Data models High GIS focus
  • Individual State and Territory solutions
  • Meta data
  • Incremental updates
  • Accuracy upgrade (graphical to survey)

28
Victorian DCDB VicMap Property
  • Combination of digitised paper maps and datasets
    held by Water authorities (MMBW)
  • Vicmap Property, previously known as the State
    Digital Cadastral Map Base
  • Isolated Survey system, non-survey accurate DCDB
  • Higher accuracy in Urban and Metro regions, lower
    accuracy in regional areas
  • Very good cadastral coverage, over 90 of
    property recorded
  • Geodetic datum AMG GDA94, not yet fully adopted

29
Current cadastral data models
  • Land parcels constitute the basic building block
    in land administration systems. Parcels were
    employed to identify the areas related to
    interests in land.
  • Besides that, land parcels have been used as
    indices for organising land information in
    various land administration subsystems or within
    other related agencies.

30
Current cadastral data models
  • Interests recorded in land administration systems
    are traditionally those associated with private
    ownership.
  • The most important Interest in land is the
    ownership of land.
  • Ownership is usually recorded along with
    restrictions, most commonly caveats, mortgages
    and rights of way.

31
Current cadastral data models
  • Land administration systems have so far focused
    on private interests rather than public
    interests.
  • Although, some government agencies are
    responsible for management of public lands, their
    systems are usually not as mature as those used
    for managing records of private land, and are
    usually separately maintained.

32
Current cadastral data models
33
The issues associated with the current model
  • How new interests and RRRs might be incorporated
    into a cadastral fabric?
  • How to facilitate interoperability ?

34
The issues associated with the current model
  • Spatial dimension of the interests does not
    necessarily fit to a land parcel
  • A biota right exists as an interest that often
    appears to be attached to land parcels , but the
    commercial exploitation of the opportunities
    arising from biota may not neatly align to
    individual land parcels.
  • A water catchments right.
  • A noise restriction.

(Bennett et al., 2005)
35
The issues associated with the current model
  • Current cadastral data models are not really
    spatially-enabled and accordingly do not support
    interoperability
  • Grantor/Grantee (Deed based)
  • Title numbers (Title based system)
  • Block-and-plot numbering system
  • Street address
  • Spatial identifiers??????????????

36
An alternative model - principle
  • Land is not a legal entity until an interest is
    attached to it
  • Land parcel is registered when an ownership is
    attached it.
  • Right of way is registered when there is a
    restriction in a specific dimension of a land
    parcel.

37
An alternative model - principle
  • The very close relationship between each interest
    and its spatial dimension in the real world
    should be also recognised in information systems.
  • They should be maintained together as a unique
    entity in a cadastral information system.
  • This unique entity must define both the interest
    and its spatial dimension.

38
An alternative model core model
Incorporating Interests
Integrating Interests and their spatial dimensions
39
An alternative model conceptual model
40
An alternative model- challenges
  • The conversion of RRRs into their respective
    spatial dimensions
  • The relationships among legal property object
    layers.

41
Topological relationship
  • The topological relationship can quickly find
    neighbouring legal property objects.
  • Object sharing makes maintenance for consistency
    and updates easier.

42
Spatial relationship
  • To determine whether one legal property object
    touches, coincides with, overlaps, is inside or
    is out side of another legal property object
  • One might want to determine which car space
    footprints fall inside a particular land parcel.

43
General relationship
  • The general relationship is not physically
    explicit for example, the relationship between
    the owner(s) with an apartment
  • For instance the same position may involve
    complex relationships among persons, each
    interested in a different way, for example as a
    car space, a water catchment, or as owner of the
    parcel.

44
Vertical relationship
  • Vertical integrity is the ability to relate legal
    property objects from one data set with legal
    property objects from another.
  • For example, automatic realignment of the gas
    line through its topological link to the property
    boundary is possible.

45
New Cadastral data model
46
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