USUS--Egypt Workshop on Space Egypt Workshop on Space Technology and GeoTechnology and Geo--information information for Sustainable Development, for Sustainable Development, June June 1414--17, 2010 17, 2010 -- Cairo, EgyptCairo, Egypt

Shoreh Elhami, GISP, GIS DirectorShoreh Elhami, GISP, GIS Director Email: Email: selhami@co.delaware.oh.usselhami@co.delaware.oh.uswww.dalisproject.orgwww.dalisproject.org

Effective use of GIS in a USEffective use of GIS in a US--based based local governmentlocal government

SummarySummary

•• Introduction/HistoryIntroduction/History

•• ApplicationsApplications

•• Data Dissemination StrategiesData Dissemination Strategies–– Web Based SolutionsWeb Based Solutions

•• Other ProductsOther Products

Delaware County, Ohio, USADelaware County, Ohio, USA

State of OhioState of Ohio

County of DelawareCounty of Delaware

United StatesUnited States

Delaware CountyDelaware County

Fastest growing county in the state of Ohio Fastest growing county in the state of Ohio since 1980since 1980

2020thth fastest growing county in the nationfastest growing county in the nation

Ranks 8Ranks 8thth (nationally)(nationally) for attracting the young & for attracting the young & wealthy wealthy (24(24--35 Yrs old with >$100,000)35 Yrs old with >$100,000)

64% population growth between 1990 & 200064% population growth between 1990 & 2000

50% increase in population from 2000 to 200950% increase in population from 2000 to 2009

Population GrowthPopulation Growth

* Figures for 1960 to 2000 are based on Census, 2010 and 2020 projections are generated by Morpc

18.84%

25.48%

24.31%

64.34%

54.77%

22.77%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00%

1960-1970

1970-1980

1980-1990

1990-2000

2000-2010

2010-2020

Percent Increase in Population (1960-2020)

Recorded Subdivisions & Development in Pipeline from 1808 to 200Recorded Subdivisions & Development in Pipeline from 1808 to 20099

GIS History/Datasets:GIS History/Datasets:

••The Project was initiated in 1991The Project was initiated in 1991

••Since 1991, six Orthophotos and over 100 data Since 1991, six Orthophotos and over 100 data layers have been createdlayers have been created

••Every subdivision, condo, lot split, combination, Every subdivision, condo, lot split, combination, & annexation is processed and entered into GIS & annexation is processed and entered into GIS by the GIS teamby the GIS team

••Several county and city departments actively Several county and city departments actively use GIS, there are many casual usersuse GIS, there are many casual users

••Recipient of many state, and nationwide awardsRecipient of many state, and nationwide awards

• Parcels (property boundaries)• Road Right of Ways• Road Centerline• Subdivision Boundaries• Municipal Boundaries• Township Boundaries• School Districts• Tax Districts• Rail roads• Various Landmarks • Hydrology• Master Address Points• Orthophotography• GPS Points• Topography and many more…

Existing Datasets (1991 Existing Datasets (1991 –– 2010)2010) Over 100 datasetsOver 100 datasets

Existing Datasets

Other Coverages:Other Coverages: School Districts, Townships, Municipalities, Tax DistrictsSchool Districts, Townships, Municipalities, Tax Districts

Attributes of Road CenterlineAttributes of Road Centerline

••Road_layerRoad_layer (10 Digit Item )(10 Digit Item )XXXXXXXXXXXXXXXXXXXX1 2 3 4 5 6 7 8 9 101 2 3 4 5 6 7 8 9 10L1&2 = Jurisdiction CodeL1&2 = Jurisdiction CodeL3&4 = Road TypeL3&4 = Road TypeL5&6&7&8 = Segment IDL5&6&7&8 = Segment IDL9&10 = SubL9&10 = Sub--Segment IDSegment IDOther Attributes:Other Attributes:••Road Type Road Type ••Road Name Road Name ••PrePre--type (i.e. State Route)type (i.e. State Route)••PrePre--direction direction ••SuffixSuffix--directiondirection••Address Ranges on the right and left side of each segmentAddress Ranges on the right and left side of each segmentfromfrom the beginning the beginning toto the end of each segment. (F_Right, the end of each segment. (F_Right,

T_Right, F_Left, and T_Left)T_Right, F_Left, and T_Left)••Zip codes, ODOTZip codes, ODOT’’s Unique ID, Theoretical Range, Alias Namess Unique ID, Theoretical Range, Alias Names

Master Address PointsMaster Address Points

•Created a GPS’ed Point Coverage including all Structures’ addresses including multi-family residential and commercial units

• Parcel Identification Number• Image ID• X, Y, & Z Coordinates of the Structure• Street Name• Structure Number• Unit Number (for Multi-Family Units)• Pre Direction• Suffix Direction• Pre-Type (i.e. State Route)• Road Type• Land Use• GPS Van’s X, Y

& Z Coordinates

Multi unitaddresses

Other Image Data Sources: Oblique Other Image Data Sources: Oblique Imagery Imagery –– Pictometry (2004, 2007, 2009)Pictometry (2004, 2007, 2009)

GIS System is used by many local or GIS System is used by many local or remote users... remote users... ••AuditorAuditor’’s Offices Office

••Appraisal (various analysis including sales ratio, Appraisal (various analysis including sales ratio, neighborhood delineation, etc)neighborhood delineation, etc)••Support for Triennial and SexennialSupport for Triennial and Sexennial••CAUV (inspections and calculations)CAUV (inspections and calculations)••Mobile homes (mapping, monitoring)Mobile homes (mapping, monitoring)••TIF, BOR, Abatements, etc... (mapping, geoTIF, BOR, Abatements, etc... (mapping, geo--locating)locating)

••Planning Departments (City/County)Planning Departments (City/County)••Building Departments Building Departments (City/County)(City/County)••Economic Development (City/County)Economic Development (City/County)••Emergency Responders (EEmergency Responders (E--911, Sheriff, Police, etc.)911, Sheriff, Police, etc.)••Infrastructure/Utility Mapping (City/County)Infrastructure/Utility Mapping (City/County)••Many more....Many more....

Orange Township Zoning, Land Use, & Enterprise ZoneOrange Township Zoning, Land Use, & Enterprise Zone

New Subdivision & Rezoning ReviewsNew Subdivision & Rezoning Reviews

Flood of 2005 – Identification & Notification of Affected Residents within the Inundation Zone

Blue line = Inundation Zone

Red Dots = Occupied Structures

••CountyCounty’’s first IMS was developed in 1997 and was s first IMS was developed in 1997 and was based on Map Objects (based on Map Objects (only 12 layers were served, simple only 12 layers were served, simple interface, quick response)interface, quick response)

••The ArcIMS based application The ArcIMS based application –– DALIS Web DALIS Web –– launched in July 2005, over 1/2 Million hits per launched in July 2005, over 1/2 Million hits per month; over 80 data layers are served on this sitemonth; over 80 data layers are served on this site

••Various versions of IMS runs on Intranet and Various versions of IMS runs on Intranet and Internet Internet (each contain different data sets)(each contain different data sets)

••More IMS applications in 2006More IMS applications in 2006--2008 (Sex Offender, 2008 (Sex Offender, elections, annexation applications) elections, annexation applications)

Interactive Map Server (IMS) Applications:Interactive Map Server (IMS) Applications:

General Tab: Various Search Options

Owner, Address, Intersection, Condo, Custom Search

Subdivision Search

Land Marks, Rental, Commercial, and Industrial Unit Search

Environment Tab: Shaded Relief, Flood Plains, Soils, Topo, Sewer lines

Zoning/Active Subs Tab

Find Comparable Properties

Other Products & ServicesOther Products & Services

Flex Based ArcGIS ServerFlex Based ArcGIS ServerApplication for Delaware County Application for Delaware County

Public Safety Public Safety

The Role of Remotely Sensed Data The Role of Remotely Sensed Data on Securing Return On Investment on Securing Return On Investment

(ROI)(ROI)

Two ExamplesTwo Examples

Thematic Mapper Thematic Mapper (TM) Model(TM) Model

October Stacked imageOctober Stacked image

July Stacked imageJuly Stacked image

Current Agriculture Use Valuation (CAUV) Current Agriculture Use Valuation (CAUV) Compliance ProgramCompliance Program

July NDVI (Normalized Difference Vegetation Index), lighter areaJuly NDVI (Normalized Difference Vegetation Index), lighter areas, s, higher NDVI, more vegetation (prehigher NDVI, more vegetation (pre--harvest)harvest)

October NDVI (darker areas, lower NDVI, less vegetation, postOctober NDVI (darker areas, lower NDVI, less vegetation, post--harvest)harvest)

TM ModelTM Model

TM Model TM Model -- Change Detection from JulyChange Detection from July--OctoberOctober

TM Model TM Model -- Possible Violators, TM Model(119 of 382,31%)Possible Violators, TM Model(119 of 382,31%)

CAUV Compliance ProjectCAUV Compliance Project(Use of Remote Sensing (Use of Remote Sensing –– Harvest Model)Harvest Model)

Return On InvestmentReturn On Investment

The project resulted in return of The project resulted in return of $1,587,503$1,587,503 million dollars of taxes to million dollars of taxes to

the county in its first year. The the county in its first year. The money was then distributed among money was then distributed among

the school districts within the County.the school districts within the County.

Woodland Layer from Color Infrared Woodland Layer from Color Infrared Imagery (CIR) and LiDAR Dataset Imagery (CIR) and LiDAR Dataset

• Methodology (out sourced)• 90 cm pixel resolution CIR – supervised classification• Filtered out the low brush (lesser than 60 cm in height)

by cross referencing the LiDAR data (2-meter post spacing) with the results

• Manual cleansing• Used in the CAUV project (woodland has lesser value

than cropland)

Woodland Layer from CIR/LiDARWoodland Layer from CIR/LiDAR

Change Detection Between Change Detection Between Two Building Outline layersTwo Building Outline layers

Two building outline layers from 2006 and 2008 Two building outline layers from 2006 and 2008 Ortho imageries were created by using a mix of Ortho imageries were created by using a mix of image processing techniques and manual editingimage processing techniques and manual editing

A change detection procedure was conducted on A change detection procedure was conducted on 20062006--2008 structures to detect missing 2008 structures to detect missing improvements (in hopes of securing lost value and improvements (in hopes of securing lost value and taxes)taxes)

New/Changed StructuresNew/Changed Structures

Over 3,600 polygons identified as Over 3,600 polygons identified as ““NewNew””Over 3,441 polygons identified as Over 3,441 polygons identified as ““Changed, Possibly Changed Changed, Possibly Changed & Unknown& Unknown””Over 860 polygons identified as Over 860 polygons identified as ““DemolishedDemolished””After dropping small polygons (lesser than 500 After dropping small polygons (lesser than 500 sqftsqft) & those with ) & those with a permit, a permit, Found:Found:

4 4 New New houses &165 houses &165 NewNew outbuildingsoutbuildings138 138 ChangedChanged structuresstructures

52 52 Demolished Demolished structuresstructures

Change Detection Preliminary ResultsChange Detection Preliminary Results

Total Estimated Appraised ValueTotal Estimated Appraised Value

10,497,795 + 2,242,321= 12,740,11610,497,795 + 2,242,321= 12,740,116

Estimated taxes based on an average tax rate Estimated taxes based on an average tax rate (commercial and residential)(commercial and residential)

+/+/--$230,000$230,000ROI after Deducting the Costs:ROI after Deducting the Costs:

+/+/--$205,000$205,000

Change Detection Preliminary ResultsChange Detection Preliminary Results

Conclusion Conclusion

• Proper use of GIS and Remote sensing benefits many governmental departments & it assists in:• Streamlining Workflows• Engaging Citizens• Empowering Decision Makers • Fostering Collaboration Among Various Stakeholders• Demonstrating Accountability

Q&AQ&AEmail: Email: selhami@co.delaware.oh.usselhami@co.delaware.oh.us

www.dalisproject.orgwww.dalisproject.org