360 likes | 432 Views
Learn about creating and managing spatially accurate cadastral geometry in GIS, enhancing land records and survey systems. Explore Cadastral Fabric fundamentals and workflow customization. Understand the importance of accurate coordinates for GIS layers.
E N D
Managing a Cadastral SDI Framework Built from Boundary Data • Michael Elfick • Tim Hodson • Curt Wilkinson
Agenda • Introduction – Current situation • Background and Design Concepts • Data Model • Workflow
The influence of GPS • GPS enabled systems will be everywhere • To make GPS truly valuable, GIS must supply underlying mapping information • This information must be accurate • Accurate data greatly extends the usefulness of GIS
Goal A simple system to create and manage spatially accurate cadastral geometry in a GIS. The system must be extendable and: Follow survey methods Be able to improve existing datasets Maintain spatial relationships between the Cadastre and associated GIS layers.
Scope of Technology • Focus on cadastral geometry • not a full cadastral system • A key part of a GIS system • Designed to be an extendable platform • For land records and cadastre • Complements a civil and survey system
Cadastral Fabric • The fabric is a continuous surface of connected parcels • It is also a dimensioned boundary network • Has an explicit topology, defined by common parcel corners and neighbors • Topology is inherent in the model, and is defined and enforced during data entry
Survey Measurements • In the past, measures of bearing and distance were much easier than fixing a location on the surface of the earth • Land surveys are parcel dimensions, with known error in the measures • Parcels are also defined by their relation to other parcels • So, measures and connections were known, but true coordinates were not
From Measures to Coordinates • We need accurate coordinates for the fabric and associated GIS layers • Accurate coordinates are close to the true coordinates • Implies there is a real object (not always) • and we know how close (statistic of error) • For Instance, Control Points have: • A physical location (monument) • Error information (level of confidence)
Central Concepts • Often, associated GIS layers are created and maintained in context with the Cadastre • An accurate Cadastre can serve as the ‘control’ for the rest of the GIS • If we capture the shifts in coordinates of the Cadastre, we can then adjust the associated layers and maintain spatial relationships • The result is more accurate coordinates all around
Edited only by Cadastral Editor Editable by standard GIS ESR Shapes Coordinates Measurements Derived from Coordinates Computed from LSA – held by Points From Survey or Records – held by the Line Central Design Concept • Differentiation of Source information from derived information
Fabric Fundamentals • Parcels are the ‘unit of work’ • Create & edit parcels • Join parcels to the fabric • Control points ‘fix’ the fabric • Connected (and historic) parcels have redundancyof measurements • Multiple measurements & control points processed in a least squares adjustment
Parcel Parcel Model • Parcels are represented by : • parcel linefeatures, • parcel pointfeatures, and • parcel polygonfeatures, • referred to in aggregate as parcel features
Parcel Model • Parcels are defined by non-spatial data, and • Parcels have spatial data – dimensions on lines
Model of a Parcel • Lines have geometry defined by dimensions and by points
Points & Control Points • A control point is an special type of parcel point, giving that point an enhanced status
Plans • Plans are used to represent a collection of information about a legal land document
Data Model Plans - Concepts • Most Parcels are associated with a planandJobs are often based on Plans • Plans and all associated parcels can be recovered from the Cadastral Fabric • Plans hold the metadata for parcels (go back to legal document of origin) • You can extend the Plan concept to fit your organization, for example: • you can add to the schema for other sorts of metadata about the document
Plans Model Status manages the life-cycle of the Plan
4 4 4 2 7 1 6 2 3 6 2000 1985 1994 History - Concepts • Parcels updated with new record information are never deleted from the Fabric, they are simply marked as Historic • 4 different types of historic information maintained: • State of the Cadastre on a particular date • State of the Fabric on a particular date • Lineage of a Parcel • History of Adjustments to the Cadastral Fabric
Workflow Customisation • This can start with adding new attributes (fields) to the Cadastral Fabric Tables • The Cadastral Editor can be used to edit these attributes via the Property Inspector • The Cadastral Editor UI is written using ArcObjects components, overlying an editing engine
Workflow System Integration • Cadastral fabric tables can have relationships to other geodatabase tables via relationship classes • So other systems, like a text based title management database, can be linked to the cadastral geometry of the fabric
Workflow Editing Workflow
Workflow Jobs – “Work-Orders” • A Job is a “work-order” for creating, modifying or adjusting one or more parcels. For instance: • Entering a parcel subdivision • Entering control points • Adjustment • Jobs can be saved, or committed • Jobs can be open for any length of time
Data Model Locked Parcels • A job may lock parcels, no other job can edit the parcel attributes or dimensions • Parcel Points are never locked • This allows LSA adjustment while jobs are open • If not locked, standard reconcile will detect conflicts
Workflow Parcel Editing • The ‘unit of work’ • Parcels are created by entering a loop traverse of the parcel boundary • Parcel closurereport is a first level Q/A check First Level QA check
Workflow Parcel Join - Concepts • Parcel Joining enforces the topologicalmodel relationships between parcels • Join is an interactive ‘point and click’ UI • Match shared points • Automatic scale and rotate • Auto-join utility • Second level QA check provided by the transformation residuals during a join
Parcel Join Second Level QA check
Join • Joining is the easiest and fastest way to build the Fabric • Join process ensures fit to the Fabric • No slivers possible • No accidental overlaps • Automatically handles translation, scale, rotation from local reference system • Each newly joined parcel adds valuable information that can be used in future least squares adjustment jobs
Least Squares Adjustment • Fabric + Control +LSA = Good Coordinates • Preparation of the data is half the work • The fabric model and the software does this • LSA does more than improve the coordinates • Shows where control is needed • Finds errors in the data (eg. incorrectly entered measurements…) • Extensive Reports on analysis of the data • Works only on the coordinates, never changes the original measurement values
Workflow Job Adjustment • Once the Control has been tested, job adjustment is easy • Set tolerances • Select constraints • Straight lines • Line points
Workflow Job Commit (close-out) • Before a change is inserted into the Cadastral Fabric the system does integrity checks : • Tests of bounding parcel coordinates • Notify if need to readjust • If parcels were not locked, then reconcile • On commit, the system: • Calculates adjustment vectors • Updates job, history… • Releases locks on the parcels
Workflow Associated Feature Classes • On commit, the transaction manager creates a set of Adjustment Vectors • Each point’s coordinate residual provides a vector that may be used on the GIS layers • Vector sets are stored as a history of coordinate shifts based on each least sq. adjustment • GIS Layers can be updated using the Adjustment Vectors • You decide when to make a GIS layer update to the Cadastral Fabric • This is possible because Cadastral Fabric maintains the adjustment “history” of each layer
Workflow GIS Layers Adjustment
Workflow GIS Layers Adjustment
SUMMARY • ArcGIS has been extended for cadastre data • Improve existing data, regardless of quality • It uses survey methods • Can follow a job workflow, and keep history • Applies cadastral adjustments to feature classes • Is an easily extended and customized system • It supports ‘remote’ editing • It supports pessimistic locking • Can be scaled to very large datasets