Slide 1

Transcript Slide 1

Simplification of Parcel Mapping Process and its Application: Geographical Information System based Approach

Dr. K.Ezhil Vendhan

WHO WE ARE

Launched from the First American Corporation, CoreLogic is a leading provider of consumer, financial and property information, Analytics and services to business and government We have more than 1 million users who rely on our data we have most comprehensive repository of public, contributory and proprietary data in the US like mortgage information , parcel and geospatial etc.

• • • •

Introduction

A parcel map is perhaps the most convenient resource available to the public to determine the location and Parcel Identification Number of a property

Town officials like Assessors, Planners, Engineers, and others use parcel maps on a daily basis. So it is very important that parcel maps should show the current and updated information.

History shows that most GIS implementation have some difficulties with parcel mapping process.

In this perspective CoreLogic internally developed many customized GIS tools and various methods in AutoCAD Map and ArcGIS environment for parcel mapping, these methods plays vital role in creation of new parcel map and updating large quantity of existing parcel map.

Aim

The aim of this study is to analyze various methods of parcel mapping and simplification of the process to improve productivity and data accuracy.

Processes

Basically these methods can be classified into three broad categories, I.

Pre-Processing II. Production Process III. Final – Processing

Pre-Processing Methods

1. Defined Folder Structure 2. Domain Controls in Data base 3. Pre- Defined columns 4. Clipping the county parcel based on available resources 5. Multiple file Re-projection tool 6. Add XY in Single field 7. Clipping stack and Non Stack Polygons

Pre- Processing Methods 1. Defined Folder Structure Folder Creation Tool

VB Script for Tool Creation

Create Default Fields

Create Domain Control Domain Control

Clip Stack and Non Stack Line and PIN

Clipping Stack and Non Stack Polygons Clipped Stack Parcel Clipped Lines and PINs Clipped Polygon

Multiple File Geo Referencing This tool will be useful to Geo Reference Multiple File

Create XY Field in Single Field

The XY creates in same field; it will be useful to find how may parcel have aligned

Clipping Stack and Non Stack Polygons Clipped Stack Parcel Clipped Lines and PINs Clipped Polygon

Production Process

Parcel mapping Production process are classified under five major categories. 1. CAD conversion 2. Building parcel Raster to Vector (COGO and Georeference) 3. Maintenance Raster to Vector 4. Maintenance Spatial Alignment Process 5. Maintenance Existing data editing

CAD Conversion Flow Chart

COGO Method

Geo-Referencing Method

Maintenance Parcel – Raster to vector

Maintenance Spatial Alignment

Existing Data Editing

Maintain Existing

Final Process

In Final process following methods are implemented for data accuracy.

1.Arc Google Synchronize tool 2.Multiple Stack Creation tool 3.Edge Matching 4.Multi Pin Check using Spatial Unique ID Creation 5.Spatial Join/ Forward Link 6.Non- spatial / Reverse Link 7.Summarize Check 8.Color Code

Multi Stack Polygon Creation Tool Data Base

Stack Layer

OID Linking - Multiple Points Identification

Line segment missing Multiple Points

Polygon is created using the final Line and Point features. Spatial Join (OID linking / Third party tool) is done to check multiple point feature present in a closed line. All NULL and Multiple Points are corrected.

Spatial Join is done to check whether all point features is converted to Polygon.

Multiple points & Null polygons

Database Forward DB check / Spatial Join Common fields from the Spatial point feature and the Taxroll data are joined Unjoined DB are exported and verified the errors and it is rectified Spatial Data Tax Roll data

Non Spatial \Reverse DB Check Common fields from the Taxroll data and Spatial point feature are joined Unjoined DB are exported and verified the errors for rectification This Method is useful for identified Missing parcels and Stack parcel Tax Roll Data Spatial Data

Summarize Check By summarizing APN and Map column an output of APN count is obtained for both Tax roll data and Map Data. The Map which has difference in APN count is checked again for errors.

Color code (Symbology) District, Map and BLK are color coded and checked by panning, since dbase check will not clear all the errors

Parcel Mapping Applications in CoreLogic

•

CoreLogic captured 124 million parcels for 2,200 counties and townships Nationwide.

•

CoreLogic ParcelPoint ® product enables users to access the highest level of positional accuracy for developing location-based solutions.

•

Each Parcel’s Unique Identifier allows it to be linked to other forms of information, including Valuations, Service Areas, Environmental Factors, Demographics, and Parcel Data also enables sophisticated spatial analysis such as proximity, overlay and buffer zone operations.

Parcel boundary data is applicable to Insurance Applications

•

Integrating ParcelPoint product with flood risk zone is to provide more flexible and accurate decisions to the decision makers.

•

Maintaining taxing jurisdiction data base for determining the valuation and classification for taxation of property.

•

Parcel boundary data helps the homebuyer in identifying the best fit for new commercial development or matching their desirable location.

•

Developing accurate models for locating fire response area could be the difference between life and death in emergency situation.

•

Parcel data provides an efficient platform for utility companies like Power Management, Electricity, Gas, Telecommunications etc .

Various industries relay on CoreLogic for accurate Geospatial Information

•

Wireless communications companies which are using CoreLogic data as the underlying map for mobile advertising.

•

Government agencies like United States Department of Agriculture (USDA) and FBI are using CoreLogic data for understanding Agriculture Trends and Crime Patterns.

•

Insurance company State Farm is using parcel and natural hazard data to better determine insurance rates.

•

These different industries have in common need to understand exactly where a property is on earth and the need to link the appropriate data to that location.