GIS – Great Lakes Sediment Budget – Technical Methodology – Buffline Digitization Madeleine Dewey EIT1 , Cedric Wrobel EIT1 1United States Army Corps of Engineers Great Lakes and Ohio River Division, Buffalo District Department of Coastal and Geotechnical Design Editor and Senior Reviewer: Weston Cross PG1 Published: September 2021 Abstract: This document is intended for use as a reference guide to complete bluffline digitization work for the Great Lakes Sediment Budget, a project of the Great Lakes Restoration Initiative. Digitization work consists of manually drawing polylines along the lakeshore to delineate where the bluffline, or more broadly, the line of significance, exists. This reference can be used for both historic, and contemporary blufflines. In addition, this guide outlines what datasets, ESRI ArcGIS tools, and strategies should be employed. The manual for ESRI ArcMap 10.7, the version of ArcGIS used to create this guide, can be found at: https://support.esri.com/en/products/desktop/arcgis‐desktop/arcmap/10‐7‐1

This is an instructional document developed for volunteers who follow the Fluvanna History Initiative on One Shared Story's GIS Hub.Training was held at the Fluvanna County Public Library on Sunday September 29, 2019. This effort is being coordinated through an Esri GIS Premium Hub Community with assitance from GIS Corp and funding from the UVA Equity Atlas and the BAMA Works Fund.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We converted the photointerpreted data into a format usable in a geographic information system (GIS) by employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM), Zone 16, using the North American Datum of 1983 (NAD83). Orthorectify: We orthorectified the interpreted overlays by using OrthoMapper, a softcopy photogrammetric software for GIS. One function of OrthoMapper is to create orthorectified imagery from scanned and unrectified imagery (Image Processing Software, Inc., 2002). The software features a method of visual orientation involving a point-and-click operation that uses existing orthorectified horizontal and vertical base maps. Of primary importance to us, OrthoMapper also has the capability to orthorectify the photointerpreted overlays of each photograph based on the reference information provided. Digitize: To produce a polygon vector layer for use in ArcGIS (Environmental Systems Research Institute [ESRI], Redlands, California), we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format by using ArcGIS. In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map-attribute codes (both map-class codes and physiognomic modifier codes) to the polygons and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer. Geodatabase: At this stage, the map layer has only map-attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map-class names, physiognomic definitions, links to NVCS types), we produced a feature-class table, along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature-class layers produced from this project, including vegetation sample plots, accuracy assessment (AA) sites, aerial photo locations, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.

We constructed a time-series spatial dataset of parcel boundaries for the period 1962-2005, in roughly 4-year intervals, by digitizing historical plat maps for Dane County and combining them with the 2005 GIS digital parcel dataset. The resulting datasets enable the consistent tracking of subdivision and development for all parcels over a given time frame. The process involved 1) dissolving and merging the 2005 digital Dane County parcel dataset based on contiguity and name, 2) further merging 2005 parcels based on the hard copy 2005 Plat book, and then 3) the reverse chronological merging of parcels to reconstruct previous years, at 4-year intervals, based on historical plat books. Additional land use information such as 1) whether a structure was actually constructed (using the companion digitized aerial photo dataset), 2) cover crop, and 3) permeable surface area, can be added to these datasets at a later date.

Planimetric Miscellaneous Structure features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintenance of the data includes heads-up digitizing using the orthophoto images.

The Geographic Information System (GIS) Solutions market is experiencing robust growth, driven by increasing adoption across diverse sectors. The market, estimated at $15 billion in 2025, is projected to expand significantly over the forecast period (2025-2033), fueled by a Compound Annual Growth Rate (CAGR) of approximately 8%. This growth is attributed to several key factors. Firstly, the rising need for precise spatial data analysis and visualization across industries like agriculture (precision farming), oil & gas (resource exploration and management), and construction (infrastructure planning and development) is driving demand. Secondly, advancements in GIS software and services, including cloud-based solutions and AI-powered analytics, are enhancing efficiency and accessibility. Thirdly, government initiatives promoting smart cities and infrastructure development are further boosting market expansion. The market is segmented by application (Agriculture, Oil & Gas, AEC, Transportation, Mining, Government, Healthcare, Others) and type (Software, Services), with software solutions currently holding a larger market share due to increasing digitization and data-driven decision-making. North America and Europe are currently the leading regional markets, benefiting from established infrastructure and high technology adoption rates, but Asia-Pacific is poised for significant growth driven by rapid urbanization and infrastructure development. Despite the promising growth trajectory, certain challenges remain. High initial investment costs for GIS software and implementation can be a barrier to entry for smaller businesses. Furthermore, the need for skilled professionals to effectively utilize and manage GIS data poses a considerable constraint. However, the ongoing development of user-friendly interfaces and accessible training programs is mitigating this issue. The competitive landscape is characterized by a mix of established players like ESRI, Hexagon, and Pitney Bowes, alongside emerging technology providers. These companies are actively investing in R&D and strategic partnerships to maintain their competitive edge and capitalize on the market's expansion. The long-term outlook for the GIS solutions market remains positive, with continuous innovation and expanding applications across various sectors paving the way for sustained growth throughout the forecast period.

The Long Island Sound Study developed these digital data from 1:100,000-scale National Oceanic & Atmospheric Administration (NOAA) and United States Geological Survey (USGS) maps as a general reference to the depth of water in Long Island Sound. In 1996, these data were digitized from paper maps by the Long Island Sound Study (http://www.longislandsoundstudy.net) and incorporated into a Long Island Sound GIS database. Not intended for maps printed at map scales greater or more detailed than 1:100,000 scale (1 inch = 1,578 feet.) Dataset credit: Applied Geographics, Inc. of Boston, Massachussets was contracted by the Long Island Sound Study to automate and digitize these bathymetry data for Long Island Sound. Linda Bischoff, GIS Analyst, digitized the data and created the orginal metadata.

Digitizing A georeferenced topo map of Meru 122_1, 122_2, 123_3, 124_4. Cropped and mosaiced . It contains digitized topographical features .

The entire Vermont extent of the National Flood Hazard Layer (NFHL) as acquired 12/15/15 from the FEMA Map Service Center msc.fema.gov upon publication 12/2/2015 and converted to VSP.The FEMA DFIRM NFHL database compiles all available officially-digitized Digital Flood Insurance Rate Maps. This extract from the FEMA Map Service Center includes all of such data in Vermont including counties and a few municipalities. This data includes the most recent map update for Bennington County effective 12/2/2015.DFIRM - Letter of Map Revision (LOMR) DFIRM X-Sections DFIRM Floodways Special Flood Hazard Areas (All Available)

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The mapping component of the BRCA project used a combination of methods to interpret and delineate vegetation and land use polygons. The USGS applied an electronic segmentation method (e-Cognition software) to create preliminary linework on features with high-contrast photo-signatures. Using the preliminary linework as a baseline starting point, the primary photointerpreter drew polygons directly on screen through heads-up digitizing using ArcGIS editing tools. Additionally, trained photointerpreters assisting the primary photointerpreter drew polygons on Mylar overlays covering 1m resolution, 1:12,000-scale, 9 x 9-inch true-color aerial photographs. This process enabled the photointerpreters to view the landscape in stereo in order to identify finer details. The linework drawn on Mylar overlays was then transferred into digital media by heads-up digitizing using ArcGIS software. The park and environs were interpreted and mapped to the same level of detail.

The Flood Insurance Rate Map (FIRM) depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event (A or AE) and the 0.2-percent-annual- chance flood event (X). The FIRM data can be derived from Flood Insurance Studies (FISs) and previously published Flood Insurance Rate Maps (FIRMs). The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). This database has been created by digitizing data from georefrenced paper FIRM maps and adding information from FIS where available. All FIRMs were georeferenced at a 1:4000 scale or finer. This data should be used as a reference layer, not as an authoritative source.

This dataset contains well log files collected from wells penetrating the Tuscarora Sandstone, structural geologic map of West Virginia and salinity information based on brine geochemistry in West Virginia and Pennsylvania. A combination of proprietary and free software may be required to view some of the information provided. Software used for data analysis and figure creation include ESRI ArcGIS. For GIS map files, you will have to change the directories of the files to match your computer. LAS files were digitized using IHS Petra software, but may be viewed in Microsoft Notepad, or converted to .csv files in Microsoft Excel.

The State Lands Commission has prepared the Significant Lands Inventory (report) for the California Legislature as a general identification and classification of those unconveyed State school lands and tide and submerged lands which possess significant environmental values. The publication incorporates evaluated and pertinent comments received on the initial draft report which was circulated statewide in February 1975.The absence of a particular digitized waterway in the dataset does not mean that the State does not claim ownership of that parcel or waterway, or that such specific parcel or waterway has no significant environmental values. This dataset is not intended to establish ownership, only to identify those parcels which possess significant environmental values. Staff was unable to physically inventory all of the considered lands; instead, the advice and participation of those with known enviornmental expertise was utilized as additional to staff survey.Tide and submerged lands are digitized in the WaterBody and WaterLine feature classes; WaterLines for coastal areas, WaterBody for inland areas. Tide and submerged lands under the jurisdiction of the State Lands Commission are those sovereign lands received from the Federal Government by virtue of California's admission to the Union on an equal footing with the original States. Such lands, and State interest therein, are generally the lands waterward of the ordinary high water mark of the Pacific Ocean (seaward to a three-mile limit); tidal bays, sloughs, estuaries; and, navigable lakes and streams within the State.School Lands are digitized in the SchoolLand feature class. State school lands under the jurisdiction of the Commission are largely composed of the 16th and 36th sections of each township. The Federal Government transferred these lands to the State in 1853, in order to establish a financial foundation for a public school system. In cases where the 16th and 36th sections were mineral in character, incomplete as to acreage total, or already claimed or granted by the Federal Government, the State was permitted to select other lands "in lieu" of the specific sections.The public trust of commerce, navigation and fisheries which the State retains on patented sovereign lands should also be considered included in this inventory. Wherever a waterway, or body of water, is listed or mapped, the common trust state interest in patented sovereign lands, if any, is also included.The State Lands Commission emphasized when it adopted this report at its December 1, 1975 meeting that all tide and submerged lands are significant by the nature of their public ownership. Only because of the methodology used for this report are all of these waterways not specifically listed in this inventory.It is the intent of the State Lands Commission that the Significant Lands Inventory be periodically updated. This dataset should be considered informational, to assist the Legislature, the Commission, and the public in considering the environmental aspects of a proposed project and the significant values to be protected therein.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. James W. Sewall Company developed a complete GIS coverage for the park and revised the preliminary vegetation map classes to better match the results from the cluster analysis and NMS ordination. Polygons representing vegetation stands were digitized on-screen in ArcGIS 8.3, and later in ArcMap 9.1 and 9.2, using lines drawn on the acetate overlays, base layers of 1:8,000 CIR aerial photography, orthorectified photo composite image, and plot location and data. The minimum map unit used was 0.5 ha (1.24 ac). Stereo pairs were used to double check stand signatures during the digitizing process. Photo interpretation and polygon digitization extended outside the NPS boundary, especially where vegetation units were arbitrarily truncated by the boundary. Each polygon was attributed with the name of a vegetation map class or an Anderson Level II land use category based on plot data, field observations, aerial photography signatures, and topographic maps. Data fields identifying the USNVC association inclusions within the vegetation map class were attributed to the vegetation polygons in the shapefile. The GIS coverages and shapefiles were projected to Universal Transverse Mercator (UTM) Zone 19 North American Datum 1983 (NAD83). FGDC compliant metadata (FGDC 1998a) were created with the NPS-MP ESRI extension and included with the vegetation map shapefile. A photointerpretation key to the map classes for the 2006 draft vegetation map is included as Appendix A. The composite vegetation coverage was clipped to the NPS 2002 MIMA boundary shapefile for accuracy assessment (AA). After the 2006 vegetation map was completed, the thematic accuracy of this map was assessed.

Polygons were digitized from the Land Status Atlas maintained by the Chugach National Forest Lands staff which was derived from Public Land Orders (PLO's). The digitizing was done from 1:63,360 paper USGS quads using LIDES and ARC/INFO. All withdrawals for the Chugach National Forest are located on the Kenai Peninsula. Data available from the United States Department of Agriculture Forest Service.

This dataset represents the depth to groundwater in Utah, defined by areas. Original manuscript maps were provided by the Utah Geological Survey (UGS) and digitized by AGRC. The final data products were verified and approved by the UGS. Procedures_Used: Data was digitized by AGRC with ARC/INFO software from the reproduction film positive at 1:750,000 scale. After modifications. the final data products were verified and approved by the UGS. Reviews_Applied_to_Data: Possible distortion of the original manuscription (conceivably introduced through the photo-reduction process) was detected during digitizing. The digitized linework was visually compared to the source document. Differences in the base map data as depicted on this dataset are revealed when compared to other sources (eg. the shoreline of the Great Salt Lake). This disparity does not reflect the quality of the data.

Download .zipThis coverage represents individual ditch projects and their corresponding watersheds as provided by the Clinton County Engineer's Office.

This coverage was digitized from data drafted onto USGS quadrangle maps utilizing a run length encoding technique sampling along horizontal lines which represented the midline of cells with a height of 250 feet. The measurement increment along these lines was one decafoot (10 ft.) The quadrangle files were then merged into a county file which was subsequently converted to ARC/ INFO format.

The user should bear in mind that this coverage is only an approximation of the ditch boundaries as drafted and due to the nature of the raster digitizing process employed at that time the ditches themselves are represented as somewhat discontinuous polygons.

Additional details on the digitizing process are available on request.

Original coverage data was converted from the .e00 file to a more standard ESRI shapefile(s) in November 2014.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesReal Estate & Land ManagementReal Estate and Lands Management2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

This dataset is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information.

This dataset consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

Note: This metadata record was created by MnGeo to serve as a generic record for all SSURGO data sets within Minnesota. See the individual county metadata records created by NRCS for county-specific information; these records are included in the data set download files.

The Bicycle Plan is the countywide planning document for bicycle facilities. The GIS data component of the Bicycle Plan consists of an inventory of existing and proposed bikeways with a class I through IV designation. Bikeway data was captured using road centerlines captured from the aerial photography as the apparent centerline and heads up digitizing directly from the orthophotography by GIS staff. Attributes were compiled via a conflation process from the original bikeway data to the new coverage captured from the aerial photography. Subsequently a QC process followed to correct errors in the conflation and digitizing process. Bikeways captured from the Merrick Street centerlines do not represent the actual location of the bikeway feature. Heads up digitized features do represent the apparent centerline of the bikeway feature.

Planimetric Parking features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintenance of the data includes heads-up digitizing using the orthophoto images.