Towards Smart Cadastre That Supports 3D Parcels. Victor KHOO Singapore

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1 Towards Smart Cadastre That Supports 3D Parcels Victor KHOO Singapore

2 Outline Background What is Cadastre Vision 2020? Cadastre System Development Why? Driving Force What do we want? How? - Cadastral Innovation

3 Singapore - Cadastral Perspective Land Area : 714 sq km Population : 5 million Survey Districts : 64 Land Surface Parcels : 137,000 Air Space / Subterranean Parcels : 200 Strata Parcels : 1.2 million

4 Singapore Economic Growth

5 Cadastre System in Singapore Comprehensive register of real properties Property ownership framework Adopt Torrens system The register: Registration of Titles The map: Cadastral Survey

6 Cadastre System in Singapore

7 Establish ISN Modern Cadastral Survey System the SVY21 system Land lot survey Data preparation and plan drawing Electronic Submission Cadastral information distribution Data uploading to GIS and cadastre database Job inspection and plan approval by Chief Surveyor

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9 Cadastral Survey Development past 20 years GPS Technology / Infrastructure Co-ordinated Cadastre Information / GIS Technology Regulations Primary Triangulation with GPS technology (1992) Secondary control network known as Integrated Survey Network (ISN) (1995) Establishment of SIMRSN for DGPS applications (1999) Implementation of SiReNT CORS network (2006) New local co-ordinate system, SVY21 (1995) Coordinated Cadastre pilot study (1996) Review of the survey directive based on Coordinated Cadastre concept (1998) Cadastre data conversion (1999) Official implementation of Coordinated Cadastre (2004) Electronic Submission via CORENET (2004) Job Data Storage System (JDS) (2004) Consolidated GIS System (CGS) (2004) Lot Information Management System (LIMS) (2011) 1998 Boundaries and Survey Maps Act (BSMS) - Coordinated Cadastre Use of GPS technology Electronic submission of cadastral survey 2000 LSA amended to include all types of land survey work

10 Cadastre Vision Development of Cadastre Systems Modern Cadastre (based on coordinated cadastre) Smart Cadastre Ubiquitous Cadastre

11 Driving Force Cadastre Users Financial Institution Planning Agencies Development Agencies General Public Cadastre Information Land Agencies Utilities Companies Property Owners Statistics Department Property Agents

12 Sustainable Cadastre Business as usual is not sustainable Current cadastre not fit for future purpose Technology converging GNSS / GIS / Remote Sensing / Laser Scanning, RFID, Wireless etc. Application converging Augmented Reality, Mobile devices for information Complex development - 2D vs 3D Development going underground and above ground

13 From Data Information - Knowledge Wisdom Knowledge Adhoc Query/ Analysis Data Mining / Advance Analysis Information Predefined Reporting Data Modern Smart Ubiquitous cadastre cadastre cadastre

14 Cadastral Information Management Issues Integrity Authoritative Timeliness Bad customer experience Data leaking Cadastral Survey Data copy Copy and manage by vendor copy GeoSpace Other agencies / i.e. LTA Copy and manage by vendor INLIS Cannot track users Other Department in SLA

15 Where do we go from here?

16 What do we want going forward? Reduce risk of errors and improve integrity of cadastre information Improve process efficiency and productivity Improve users/customers satisfaction Spatial enablement in SLA and the Government Wide usage of Cadastre Information System Retrieval of ALL cadastre related information at finger tip Analysis of ALL cadastre information in relation to other information

17 Vision - Smart Cadastre

18 Introduce Data Management Regime One authoritative source Ensure timeliness Ensure high integrity Know who are the users, track usage

19 Adopt Open Source & International Standard Cadastre system will not be tied to one type of technology Facilitate fast data submission and data sharing Facilitate automation Facilitate smart data capturing Open format for perpetual safekeeping of Digital Cadastre Record

20 Establish Smart Data Model LANDLOT_POINT S Feature Class (Point) SPID SUB_TYPE XCOORD YCOORD PT_FLG PT_TYP FDOC_ID STATION_NO CM_NO LAST_UPD_BY LAST_UPD_DA TE RL AIRSPACELOT_PO INTS Feature Class (Point) SPID SUB_TYPE XCOORD YCOORD PT_FLG PT_TYP FDOC_ID STATION_NO CM_NO LAST_UPD_BY LAST_UPD_DAT E RL AIRSPACELOT_LINEPOIN TS FROM_AIRSPACELOTPTI D TO_AIRSPACELOTPTID AIRSPACELOT_FACEID AIRSPACELOT_FACES Feature Class (Polygon) _LENGTH _AREA LEFT_AIRSPACELOT_BO DYID RIGHT_AIRSPACELOT_B ODYID legend Standard Point Identifier (SPID) linkage SketchID linkage CP_Number linkage Accuracy linkage MKTS_Key linkage SI_PolygonID linkage Address linkage Job - Adjustment linkage LANDLOT_LINEPOINTS FROM_LANDLOTPTID TO_LANDLOTPTID LEFT_LANDLOTPOLYGO NID RIGHT_LANDLOTPOLYG ONID SI_POLYGONS Feature Class (Polygon) SI_POLYGONI D SI_NAME EXIST _LENG TH _AREA MKTS_POLYGON S Feature Class (Polygon) MKTS_KEY _LENG TH _AREA AIRSPACELOT_BODIES Feature Class (Multipatch) LOT_KEY _LENGTH _AREA SUB_TYPE PO_AREA COMPUTED_AREA AREA_TYPE PLAN_NUMBER SVYQTY LAST_UPD_BY LAST_UPD_DATE REMARKS LOT_STATUS OWNERSHIP_TYPE REGN_SYSTEM DERIVATION_TYPE AREA_DESCRIPTION LOT_INVESTIGATION _FL STANDARD_SURVEY LANDUSE_STATUS UPLOAD_BY UPLOAD_DATE OLD_LOT_FORMAT LEVEL SLID SI_POLYGONID SLA Core Cadastral Data Model Job Management Data Model LANDLOT_POLYGONS PROJECTS JOBS Table Table Feature Class (Polygon) STATE_RESERVE LOT_ADJUSTMENTS PROJECT_ID Feature Class (Polygon) PROJECT_ID Feature Class (Polygon) LANDXML_ID LOT_KEY JOBID RS_CODE _LENGTH _AREA DESCRIPTION... _LENGTH SUB_TYPE LOT_KEY _AREA PO_AREA LAST_UPD_BY RECORD_IDENTIFIE LINKAGES ADJUSTMENT_DA COMPUTED_AREA LAST_UPD_DATE Table TE AREA_TYPE REMARKS RS VECTORCOUNTS PLAN_NUMBER LANDLOT_POLYGO Table PROJECT_ID JOBID SVYQTY NID SOURCE_PLAN_NUMB JOB_ID SEQUENCEID LAST_UPD_BY _LENGTH ER ISSUED_RECORD Stores sequence Ids and their LAST_UPD_DATE _AREA TARGET_PLAN_NUMB corresponding adjustment dates _NO REMARKS ER... LOT_STATUS... OWNERSHIP_TYPE REGN_SYSTEM For details of the model, see the page on Job FIELD_DOCS Table DERIVATION_TYPE Management Data Model FDOC_ID AREA_DESCRIPTION SURVEYORID LOT_INVESTIGATION TRAVERSE_POIN TRAVERSE_LINE PLAN_NUMBE _FL TS ACCURACY SURVEYORID R STANDARD_SURVEY Table S Feature Class (Point) NUMBER_PAG Feature Class (Point) LANDUSE_STATUS ES UPLOAD_BY FDOC_TYPE UPLOAD_DATE CATEGORY FROM_SPID LANDXML_ID OLD_LOT_FORMAT SPID DESCRIPTION TO_SPID SLID SUB_TYPE BRG_SD DISTANCE SI_POLYGONID XCOORD DIST_SD _LENG MKTS_KEY YCOORD PPM TH TOTAL_PNTS PT_FLG ACCURACYID BEARING_AN PT_TYP G PLANS Table FDOC_ID ACCURACYID STATION_NO CM_NO PLAN NUMBER RL Traverse DESCRIPTION MKTS_NUMBERS SURVEYORID SCALE CADASTRALMAP_NUMBERS STREET_NAMES HOUSE_NUMBERS LOT_HISTORY APPROVEDPLANS_NUMBERS History INNER_POLYGO Table CS_FILEREF_NUMBERS SKETCH_NUMBERS N SKETCH_PAGES Table CHILD_SLID DRAFTSMAN_NAME PARENT_SLID OUTER_SLI EXAMINER_NAME SYSTEM_STARTDA D ACCURACYID TE INNER_SLID PLAN_APPROVALDATE SYSTEM_ENDDATE PLAN_TYPE LEGAL_STARTDAT LANDXML_ID E LEGAL_ENDDATE SUBTERRANEANLOT_PO INTS Feature Class (Point) SUBTERRANEANLOT_FACES Feature Class (Polygon) SPID SUB_TYPE XCOORD _LENGTH YCOORD _AREA PT_FLG LEFT_SUBTERRANEANLOT_BO PT_TYP DYID FDOC_ID RIGHT_SUBTERRANEANLOT_B STATION_NO ODYID CM_NO LAST_UPD_BY SUBTERRANEANLOT_BODIES LAST_UPD_DATE Feature Class (Polygon) RL SUBTERRANEANLOT_LINEPO ADDRESS INTS Feature LOT_KEY Class SUBADDRESS _LENGTH Feature Class _AREA XCOORDINAT SUB_TYPE E SUITENUMBE FROM_SUBTERRANEANLOTP PO_AREA YCOORDINAT R TID COMPUTED_AREA E SUITEALPHA TO_SUBTERRANEANLOTPTID AREA_TYPE STREETCODE ADDRESSID SUBTERRANEANLOT_FACEID PLAN_NUMBER ADDRESSID SUBADDRESS SVYQTY HOUSENUMB ID LAST_UPD_BY ER HOUSENUMB LAST_UPD_DATE HOUSEALPHA ER SLI REMARKS POSTCODE HOUSEALPHA Feature Class LOT_STATUS NAMEID Feature Adjustment Model ADJUSTMENT_VECT ORS Table FROMX FROMY TOX TOY SPID SEQUENCEID Stores displacement vectors between the old and new coordinates of adjusted point. Vector are grouped logically by an sequence id which corresponds to an adjustment date. H_CONTROLPOINTS Feature Class (Point) HCONTROLPT_N O EL_HT LAST_UPD_DATE LAST_UPD_BY STATUS RL SNAPSHOT CONST SURVEY_DATE SURVEYORID LOCATION DESCRIPTION REMARKS DEAD_DATE LIVE_DATE SPID ASSIST_SURVEY ORID Surveyors Model REG_SURVEYORS Table RS_CODE RS_NAME SAP_CUSTOMERI D ID SURVEYORID COMPANY_NAME ACTIVE_IND ADDRESS PHONE HANDPHONE REMARKS ASST_SURVEYORS Table ASSISTANT_NAME ID PHONE SURVEYORID ASSIST_SURVEYO RID PHOTO EXPIRY DATE Control Points Model VCONTROLPT_NO V_CONTROLPOINTS COORD_NORTH Feature Class (Point) COORD_EAST LATITUDE LONGITUDE MARK_TYPE EL_HT LAST_UPD_DATE LAST_UPD_BY STATUS RL SURVEY_DATE SURVEYORID LOCATION LAST_UPD_BY REMARKS LAST_ADJUSTMENT_DATE WITNESS_MARK1_MARKTYPE WITNESS_MARK2_MARKTYPE WITNESS_MARK3_MARKTYPE WITNESS_MARK4_MARKTYPE WITNESS_MARK1_HEIGHT_DI FF WITNESS_MARK2_HEIGHT_DI FF WITNESS_MARK3_HEIGHT_DI FF WITNESS_MARK4_HEIGHT_DI FF WITNESS_MARK1_REDUCED_ LEVEL WITNESS_MARK2_REDUCED_ LEVEL WITNESS_MARK3_REDUCED_ LEVEL WITNESS_MARK4_REDUCED_ LEVEL

21 Introduce Automation Semi-automation in plan checking Electronic processing of survey job Self-service map interface Online information and policy for pre-submission check Automation of data extraction - collection of administrative data and plan data Plan data to be submitted in intelligent form

22 From 2D to 5D

23 Authoritative Address Currently, addresses are linked to lot number in LIMS database Authoritative addresses Build a process of capturing address spatially by the Registered Surveyor. Address info directly capture in GIS New address data type will be created to be linked to the building

24 Benefits for SLA Reduce risks ensure high integrity and minimise errors in job approving ensure processing consistency reduce dependency on highly specialised para-professionals long-term security and protection of cadastre information Improve efficiency and productivity reduce query of the jobs improve work-flow and reduce job processing time Improve decision support collection of intelligent cadastre information in database format intelligent query improve tracking of users and usage Improve customer satisfaction

25 Benefits for Industry Improve efficiency and productivity ability of pre-populate of data improve turn-around time improve access to cadastral survey information Reduce risks reduce anomalies and errors Cost Saving improve work-flow online automation and basis functions

26 Smart Cadastre There will be 3 main trusts in the realisation of Smart Cadastre establishment of comprehensive data model to capture all cadastral survey related data that support 3D parcels, capture historical data (4D) with various accuracy (5D). establish the 3D GIS and 3D plan requirements for 3D parcel submission introduce automation in cadastral job processing and adopt LandXML that support 3D in data exchange

27 What s Next?

28 Vision - Ubiquitous Cadastre

29 Ubiquitous Cadastre Vision Source: earthmine

30 Thank You