|
Contact Us: gis_rdc@earthlink.net |
(877) 221-6684 (toll-free) (215) 243-8246
- fax
|
|||
|
|
|
|
********************************************************************** Wabasha County GIS Database Development (1996 to
present)
GISRDC has been the consultant to Wabasha County since 1995. During that time, we have been involved in several projects, listed below in chronological order. Wabasha County GIS Database
Development Pilot Project Keywords:
Database, Pilot Project, database development We
developed several GIS layers for a pilot project area (Oakwood Township) to
demonstrate the capabilities of GIS to the county staff and County Board of
Commissioners. These included: DOQ’s,
DRG’s, contours (digitized from DRG’s), soils (digitized from soil maps),
parcels, right-of-way, railroads, hydrography, NWI, and rural addressing. Wabasha County 1992 DOQ Image Conversion to County Coordinates Keywords:
Images, hardware performance, “heads-up” digitizing We
converted the 1992 Digital Orthophoto Quad (DOQ’s) images to county
coordinates by rotation and projection.
At the time (1996), prevailing hardware and software was such that
each image took 30 seconds to redraw on the screen. Since the objective was to be able to use the DOQ’s with
“heads-up” digitizing , we had to develop a method to deal with this video
performance issue. The solution
included splitting them into 16 smaller tiles and converting them to 16
levels of gray. Redrawing time was
reduced from 30 seconds to 1 second. Image catalogs were created for each
township and city. Wabasha County Digital Raster Graphics (DRG) Image files Keywords:
Images, data conversion We
converted the DRG’s to county coordinates. Keywords:
data conversion, raster to vector, database, “heads-up” digitizing We digitized
the contours for the county, resolving many problem areas with discontinuous
contours, to form complete contour lines.
We processed the DRG’s with EPPL7 to convert the rasters to vectors,
and then edited the resulting file with the DRG in the background. A database
was also prepared. Keywords:
database, “heads-up” digitizing We
created a PLSS layers using available section corner information from MnDOT,
and the DOQ’s. This is a set of files
that originate from a quarter-quarter section point file. The points are used to generate
quarter-quarter lines, and the lines are used to generate quarter-quarter
polygons. The databases for each define the township, range, section, quarter
and quarter-quarter section relevant to each. From this set, other files have
been generated by dissolving the polygons or selecting from the line and
point files: quarter-sections, sections, half-sections, and PLS townships.
The quarter-quarter section polygon file forms the base framework for parcel
mapping. Keywords:
scanning and georeferencing, database, “heads-up” digitizing, quality
control. We
digitized parcels on a township basis by scanning and georeferencing source
maps provided by the County, and then digitizing the parcels by splitting and
combining polygons in a copy of the PLSS quarter-quarter file (above). Digitizing was done “heads-up” using the
DOQ’s, the PLSS files, and the scanned source maps. PIN numbers were added, parcels were joined to the Tax List to develop
the database, and quality control measures were used to check the map. Exceptions were corrected to the degree
possible, and the remainder was reported to the County for additional
research and resolution. We also have
prepared parcel maps for the three largest cities: Lake City, Kellogg and
Wabasha. This project is still in
process: 8 townships are completed, one is in process, and 8 more
remain. Keywords:
scanning, raster to vector conversion, database development, topological
analysis We
digitized the soil maps by scanning black and white soil maps by section, and
converted the rasters to vectors using the EPPL7 software and topological
analysis techniques. The vectors were
converted to DXF files, and then edited, transformed to county coordinates
and edgematched. Soil codes and
attributes were also added, including the CER value for assessing cropland. Keywords:
Images, “heads-up” digitizing We
corrected the TIGER hydrography file to the DOQ Images. Keywords:
Images, “heads-up” digitizing We
corrected the TIGER roads file to the DOQ Images. We have also used the centerlines, created by another consultant
using GPS technology, for the Rural Addressing Project (described below). Keywords:
Images, “heads-up” digitizing We
digitized structures and driveways based on the features visible on the DOQ
Images. Wabasha County Rural Addressing Keywords:
Pilot Project, modeling, database
development, scanning and georectification, images, “heads-up” digitizing,
ArcView Avenue Scripts, User Application, OCR, data parsing We are
currently conducting the Rural Addressing project for the County. The base files for the project are a
centerline file and driveway point file created with GPS. We have successfully completed a Pilot
Project, named all of the roads. We
developed and implemented a model to create a Master Address Point database
file based on an address grid that has been adapted to a county with many
non-rectilinear road features, due to the county’s topography. All possible address points have been
created using ArcView Avenue scripts adapted from a downloaded ESRI script to
add points along a line at specified intervals. There are over 700,000 points, each with an address, none of
which are duplicates. We are
currently in the process of developing an User Application for assigning new
addresses. This set of points will
make it very easy to assign new addresses, because the user will simply have
to find the nearest point with the correct parity. Unfortunately, the GPS contractor did not capture the fire numbers
with the driveway points. The Sheriff’s
Department cannot download a copy of its E911 Database, for data privacy
reasons. Therefore, we had to create the database by scanning hard copy
output from the system (over 500 pages), and then using OCR software to
convert the image to text. Using data
parsing and standardization techniques, we have been able to separate the
text into usable data fields, to create an E911 database. At
present, we are in the process of matching the old fire number maps that have
been scanned and georeferenced , to the E911 database, and the GPS point file. The next step will
be to match the records to the telephone companies’ databases to complete the
new rural addressing database and converting from the old fire number system
to the new addressing system. When that
has been accomplished, we can link the old addresses to the new addresses,
and complete the project. Wabasha County GIS Data Organization Keywords:
Data Organization, training We are
currently reorganizing all of Wabasha’s GIS data into a formal, non-redundant,
and permanent data structure. When
complete, we will deliver it to the County, and train the newly-hired GIS
coordinator. Wabasha County 2002 FSA Photo Conversion to County Coordinates In 2003, we processed the 2002
Color FSA Photography to achieve the following objectives: Þ Create
township Images by Mosaic-ing and clipping. Þ Convert
to County Coordainates Þ Tile
into six 50 MB sections for compression with MrSID Þ Also,
compressed township images with the ECW File Compressor. Each uncompressed township image
is about 300 MB, and each ECW compressed image is about 5MB. Wabasha County Metadata Grant, Preparation and Search Tool In 2003, we assisted Wabasha
County in developing a successful grant application to the federal government’s
“Don’t Duck Metadata” grant program.
As of September, 2003. we are in the process of preparing the Metadata
and a user-friendly metadata search tool. ********************************************************************** Lake City GIS Needs Analysis and Plan (2001) Keywords:
Needs Analysis, User Group Meetings, training We
conducted a GIS Needs analysis for the City of Lake City, which included and
training session on “What is GIS?”, departmental meetings, a data inventory,
a needs and applications matrix, setting objective measures to establish
priorities, and a final implementation plan. ********************************************************************** McLeod County GIS Database Development (1997 to
present)
Dr.
Tomaselli has been the GIS consultant to McLeod County since 1997, first
while at OSM and Associates, and then since 1999 as the owner of GISRDC. The McLeod County work has encompassed
several projects over the years, which are listed below in chronological
order. McLeod County Ditch Map Inventory and Database Keywords:
database development, scanning and georeferencing, images, “heads-up”
digitizing, data conversion. While at
OSM, Dr. Tomaselli designed and implemented a Ditch Map Inventory and Database
project that used GIS as the organizing tool. It involved scanning and georeferencing nearly 100 ditch maps
and digitizing a ditch map and an ditch watershed map. Databases for both
were also developed. for the ditches were corrected to the ditch features
visible on the DOQ’s. The County
Board and staff members were able to see the value of GIS technology. The
project was originally produced in the UTM coordinate system, but was
subsequently converted to the County Coordinate system by GISRDC in 2000. McLeod County Rural Addressing Keywords: database development, scanning and
georeferencing, images, “heads-up” digitizing, data conversion, quality
control, standardization. While at
OSM, Dr. Tomaselli designed a project to digitize the hand-drawn rural
address maps showing address points. The old maps were scanned and
georeferenced. The address points
were corrected to the visible structures on the DOQ images, using “heads-
up” digitizing.. A TIGER centerline file was corrected to
the DOQ’s as well, and the database was expanded to include address ranges,
EMS, and other attributes. The project was implemented by others,
however. Under a subsequent GISRDC
project, a quality control check of the database file was done, database
errors were flagged, and street names were standardized. McLeod County 1992 DOQ Image
Conversion to County Coordinates Keywords:
Images, data conversion This was
done in conjunction with the Sheriff’s project, so that the Sheriff’s project
would be in County Coordinates. See the description under Wabasha County. McLeod County Parcel
Mapping Pilot Project Keywords:
pilot project While at
OSM, Dr. Tomaselli designed and conducted a parcel mapping pilot
project. McLeod County decided to
implement parcel mapping county-wide. McLeod County Public Land Survey
System (PLSS) Keywords:
database, “heads-up” digitizing A set of
PLS files and databases was developed, similar to Wabasha County’s, except
that some GPS points were available for some section corners. (See Wabasha
County description). A GPS point
database was also developed. McLeod County Interim
Parcel Mapping– Keywords:
scanning and georeferencing, images, “heads-up” digitizing, database development,
quality control, COGO, Avenue Programming. In 1999, McLeod County contracted with
GISRDC to conduct the “interim” parcel mapping project to provide a
moderately accurate parcel layer for GIS to be used until more accurate maps
could be prepared with COGO. This
project was very similar to the Wabasha County project, and involved
preparing a PLSS layer, scanning, georeferencing and digitizing
reference maps with the DOQ’s in the background, joining the map with the Tax
List to create a parcel database, and reporting exceptions and mis-matches
back to the County. One township was
prepared with COGO, but the approach was abandoned because the cost was too
great and because GISRDC felt that this would be better done by an
Engineering Technician, supervised by the County Surveyor. This project is still in process with 10 of 14
townships completed. In
conjunction with the parcel mapping project, we developed and Parcel Query Lookup System. McLeod County Half Section Parcel Mapping The Interim Parcel Mapping project also
included preparing half-section maps in a PDF format, the process for which
has been automated with Avenue Programming.
Preparing the maps meant that we had to show right-of-way and
government lots. A right-of-way was
created by buffering centerlines or digitizing roadway plats. Scanning,
georeferencing and digitizing photocopies of the original government lot map
drawings produced a government lot layer. This project is still in process
with 10 of 14 townships completed. McLeod County 1996 DOQ Update from NAPP Photography Keywords:
scanning and georectification, images, quality control, clipping, mosaic,
EPPL programming. After successfully
producing 1996-98 DOQ’s for Wright County (see below), a similar project was
undertaken for McLeod. McLeod County Image File
Compression Keywords:
images, data compression, hardware performance In 2000,
all of the image files were compressed with the free ECW file compression
program, which greatly improved the performance of ArcView. McLeod County GIS Data
Organization Keywords:
data organization Until
2001, there was no one at the County assigned with the responsibility for
applying GIS. The GIS files were
simply delivered to the County.
However, with the hiring of a GIS Coordinator, the data needed to be
organized and installed on the County’s file server. Rowekamp and Associates recommended a file
structure, but GISRDC implemented the structure because we had the most
direct knowledge of the file content. McLeod County Snow Plow Routing Model, Phase I Keywords:
Modeling, routing, analysis, scanning and georeferencing In 2001, GISRDC conducted Phase 1 of a Snow
Plow Route Modeling project. We
developed a routing base file as an extract of the centerline file, including
attributes necessary for replicating the time delays for snow plowing,
including the length, number of lanes, type of pavement, number of
intersections, number of mailboxes and deadheading. The county has 14 plowing
vehicles: 10 trucks and 4 motor graders.
Each vehicle has a paved route and a gravel route, with the paved
route portion plowed first. The
operator returns to the shop after the paved route, takes a break and then
plows the gravel portion. In effect,
there are 28 routes. Each plow operator prepared 2 hand-drawn maps
showing the path that they take from the start to the finish of the paved and
gravel portions. Route maps were
scanned and georeferenced, and individual route maps were created for each
route, in route sequence order, using PC ArcInfo 3.5.2 Network’s Route
command. The total plow times and speeds were
calibrated using the reported speeds and route times reported by the
operators, and also taking into account the type of vehicle and drifting
conditions in some parts of the County.
The final report showed the length and average speed of each route,
along with color coded maps showing the elapsed time for the vehicle to plow
each segment in both directions. McLeod County Snow Plow Routing
II, ArcView Application Development Keywords:
Modeling, routing, analysis, User Application, Avenue Programming, training,
documentation In 2002, at the request of County staff,
GISRDC adapted the snowplow project so that it could be modified and updated
by local staff using ArcView. The
Network Analyst extension was tested, but found to not be particularly
helpful. The ArcView Snow Plow
Routing Application included customized tools to modify existing routes or
even create new routes from scratch. The snow plow base file was
modified to include both directions of travel. This permits possible one-way plowing or deadheading as well.
The tools contain safeguards to prevent any of the following: a road segment
being plowed by more than one vehicle, being plowed twice by the same
vehicle, gaps in the path (not being plowed at all), a paved segment from
being plowed within a gravel route (and vice-versa), a city street or
state/US highway from being plowed by a county plow (although the plow could
use them for deadheading). When a
segment is swapped between two adjacent routes, the vehicle type is updated,
since it makes a big difference in plow time whether a truck or a motor
grader is plowing it. When a route
is changed, the user must also modify the route path to include the
changes. The
final result is a color coded map for each route showing the elapsed time, as
well as a summary table of the entire route system. This application was very complex because of the complexities
of snow plow routing, but it has been tested extensively and could be used in
other counties with a properly prepared set of base files. User training and documentation was also
prepared. McLeod County GIS Database Maintenance Plan Keywords:
Data User Meetings, data quality control, user applications and
specifications, images, COGO, Needs Analysis In 2001, the County Board decided that
before new GIS layers were to be developed, a plan must be developed for
maintaining the GIS System. Data user
meetings were held, and the following issues were addressed: how the data is
used, how update information is received and processed, data quality, data
needs, and potential applications. In
November, 2002, the plan was completed, and included a comprehensive analysis
and recommendations as to what was needed to improve, update and maintain the
major GIS projects: ditch mapping, address and centerline mapping, and the
Interim Parcel Maps. Data quality was
assessed and specific improvement needs were identified. Update applications and specifications
were identified. It also contained
recommendations for how to proceed with developing a high accuracy parcel
mapping project, using COGO. The plan
also recommends creating a new “DOQ” Image layer from 2002 FSA digital
photos, which was successfully demonstrated by a pilot project conducted in
conjunction with the plan. McLeod County Metadata and
Metadata Search Tool Keywords:
metadata, HTML In 2003, a complete set of metadata was
completed for 113 data sets or data set categories. The metadata was prepared using the State of Minnesota’s
DataLogR software from the Land Management Information Center (LMIC). In addition, a Metadata Search Tool was
developed to help users to quickly view abbreviated versions of the Metadata
by using the geographic entity and theme keywords. This was done by creating
an HTML document with hyperlinks. ********************************************************************** Wright County
1996-98 Digital Photo Image Update
Keywords: Images, scanning
and georectification, clipping mosaic, hardware performance, EPPL7
programming, ArcView Extensions, Metadata In
2000, GISRDC contracted with Wright County to try something new: create new
“DOQ”-like photos from NAPP photography.
The new photos were created in the Wright county coordinate system. The
photos from USGS ranged in date from 1996 to 1998. Film positives were purchased from USGS, scanned with a
high-resolution scanner, and then georectified to the 1992 DOQ’s and to the
County’s high accuracy parcel and centerline maps (created with COGO). The photos were georectified using EPPL7
and the ArcView extension created by Tim Loesch of MnDNR. Eight control points per photo were used
to “rubbersheet” it to match ground control points from the centerline and/or
parcel file. Approximately
120 photos were involved. Using
quality control measures, the photos are equal to or better than the 1992
DOQ’s in terms of spatial accuracy.
The measure was that the photos had to match the centerline and/or
parcel file, and that at the edges roads would match with not more than a 15
foot offset. The best portion of each
photo covering a township was clipped and the resulting photos were mosaicked
into a township-wide photo. Wright
County was also concerned with the video performance issues. We created mini-doq’s, and reduced the
levels of gray to 16, as we did with Wabasha and McLeod. Each township photo was split into a 10 by
10 matrix, resulting in 100 “mini-doq’s” per township. Image catalogs were created for each
township to facilitate and simplify user access to the data. Metadata was also prepared. ********************************************************************** Fond
Du Lac, WI – Police Department E-911 Address Database Development, 1995-1996 Keywords: database
development, standardization. The purpose of this project was to allow the
city of Fond du Lac’s Police Department to map police call incidents using
address points rather than points that were interpolated from address
ranges. In this project, we created
an address point database from the parcel file. The parcel addresses were matched to the addresses in the 911
file. This included standardization
of street names. ********************************************************************** Green Lake County, WI - Sheriff's Address Map Image Lookup
System, 1995 Keywords: Images, database
development, “hotlink”, geocoding The purpose of this project was to allow the Sheriff’s
Department to enter an incident address and zoom to the appropriate section
of the county address map on which the address point is located, using
ArcView’s geocoding and “hotlinking” capabilities. This was accomplished by scanning the address map that was
tiled into page-sized images. A
database of road names, address ranges and map sheet numbers, and path names
to the image files was developed to facilitate address look-up and opening the hotlinked images. ********************************************************************** River Falls Township - Parcel
and Soils Mapping, and Database
Development, 1994-1995 Keywords:
database development, data conversion See soil and parcel mapping projects for Wabasha and
McLeod Counties. ********************************************************************** Clifton Township - Parcel and
Soils Mapping, and Database Development, 1992-1993 Keywords: database
development, data conversion See soil and parcel mapping
projects for Wabasha and McLeod Counties. ********************************************************************** National Science Foundation -
Using GIS for Fiscal Impact Analysis, 1987-1990 Keywords: modeling,
analysis, database development, data conversion This was a grant to support the
development of a model for simulating the fiscal impact of land development
using GIS. The state of the art in the area
of Fiscal Imapct Analysis modeling at that time was non-spatial and based on
regression analysis that left much to be desired. These methods did little to foster the understanding of the
actual flows of revenues and expenditures. The basic premise of the GIS
model is that a city’s revenue is directly attributable to the types, values
and intensities of land use development, which is spatially distributed and
can be mapped. For example, property
taxes are based on value and use of land; grant or aid programs are
distributed based on population, miles of road, etc. Expenditures, or city
services, are also directly attributable to land use, and are spatially
distributed, whether they be police call incident locations; police
patrolling routes, snow plowing, road maintenance needs, which are related to
roads; or parks and recreation, which are related to population distribution. The model was successfully
demonstrated with a project for the City of Anoka. It involves developing an GIS Database of the factors that are
indices of the distribution of revenues and expenditures: land parcels, land
use, roads, police call incidents, and population. Using these indices, revenues and expenditures were spatially
distributed down to the parcel level.
Then, expenditures were subtracted from revenues to determine the
fiscal impact of each parcel. The fiscal impact of land uses were determined
by summarizing the revenues and expenditures by land use. NSF and URISA endorsed this
approach as an innovative and sound method to evaluate fiscal impact. However, GIS was still in its infancy at
the time, and cities would need to develop GIS in order to apply this
approach. Now that GIS has become much
more widespread, this is an approach to fiscal impact analysis that is now more
applicable. ********************************************************************** University
of Wisconsin, River Falls, Rural Development Institute,
workshops were conducted quarterly from 1994
to 1999, and were attended by more than 100 students from Minnesota and
Wisconsin counties, cities and state and federal agencies. Keywords:
training Þ PC
ArcInfo, Introduction, Intermediate and Advanced Training (1994-1998) Þ ArcView
Training (1996-1998) Þ “What
is GIS? For Managers and Decision
Makers” Training (1994-1999) |
