Download .zipThe A Law Coal Permit Maps county coverage sets were developed using the original mine maps for coal mining and reclamation permits issued under Ohio law from approximately 1966 through 1973. Approximately 1111 A-Permits were issued during this time period, however, only 350 records could be located and captured at this time. The Division of Mineral Resources Management will continue to search for missing A permit archival records as resources allow; additional A permit data may be added to this existing coverage in the future.

Ohio started issuing coal mining licenses in the 1940s. The earliest license and permit requirements were minimal and sometimes did not include submittal of a map or other delineation of the mined area. Significant changes to legal requirements are reflected by the alphabetical designation of each subsequent law revision, i.e., earlier A-law permits (circa 1966) through contemporary D-law permits. The ODNR-Division of Mineral Resources Management (DMRM) has attempted to create as complete a database as possible from available archive records, however, research has identified missing permit files. Thus, this GIS data is known to be incomplete due to the loss of archival records.

The A law permit maps were scanned at a density of 200 dots per inch (dpi). The scanned image was then heads-up digitized using Microstation computer aided design software (CAD) to create design files grouped by county location. Data captured within the design file includes permit boundary and affected boundary and associated attributes. When available, test hole locations and associated attributes were also captured. The design file was then "placed-to-ground" using ODNR Division of Geological Survey's "ODNR Land Subdivision Background Design Files" NAD83 State Plane coverages and DOQQ aerial images obtained through the Ohio Geographically Referenced Information Program (OGRIP)/Ohio Department of Administrative Services. The design file was then converted to ARC/INFO coverage and projected to State Plane Ohio Coordinates, NAD83:

Projected coordinate system name: NAD_1983_StatePlane_Ohio_South_FIPS_3402_Feet or NAD_1983_StatePlane_Ohio_North_FIPS_3401_Feet

Geographic coordinate system name: GCS_North_American_1983

A complete county coverage set consists of three data files for the permit area, affected area, and test hole locations. For example, the coverage for Harrison County includes:

harrison_a_permitted (Harrison County, A-permit area polygons) harrison_a _affected (Harrison County, A-permit affected area polygons) harrison_testholes_a (Harrison County, Test Hole points)

In addition to the ArcView shape files in the county data sets, the scanned TIF images for source documents are available at DMRM. The scanned mine map depicts information about the operations conducted, environmental resources, and extracted coal resources. If more detailed information is desired, the available archival record for each captured permit can be accessed at either the State Archives at the Ohio Historical Society or the ODNR-DMRM central office.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesDivision of Mineral Resources ManagementAbandoned Mine Land Program2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov

AT_2004_CARR File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Carroll County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the A&T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A&T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 848 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -77.306843 East -76.779275 North 39.727017 South 39.342858 Scale Range There is no scale range for this item.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, stairways, and winter trails.

CAMA_2004_CARR

   File Geodatabase Feature Class


   Thumbnail Not Available

   Tags

   Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, CAMA, Database, Structure, Appraisal




   Summary


   Detailed structural information for parcels.


   Description


   The CAMA (Computer Assisted Mass Appraisal) Database is created on a yearly basis using data obtained from the State Department of Assessments and Taxation (SDAT). Each yearly download contains additional residential housing characteristics as available for parcels included in the CAMA Database and the CAMA supplementary databases for each jurisdiction.. Documentation for CAMA, including thorough definitions for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab.


   It should be noted that the CAMA Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the CAMA Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields).


   A cursory review of the 2004 version of the CAMA Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the CAMA Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 399 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords."


   Credits


   Maryland Department of Planning


   Use limitations


   BES use only.


   Extent



   West -77.306843  East -76.779379 

   North 39.727017  South 39.346946 




   Scale Range

   There is no scale range for this item.

Carroll Transit System, operated by Ride With Us, offers six routes called TrailBlazers, that are open to the public. This layer locates the routes by color in Carroll County.

Boundary for Carroll County Maryland

This data was developed in response to citizens’ road maintenance requests from across the state as to whom to contact as the official maintenance authority - be it MDOT State Highway Administration, MDOT Transportation Authority, a county, or a municipality.MDOT SHA Website

Carroll County Developments In Process

Assessments and Taxation (A and T) Database from MD Property View 2004 for Carroll County. The A and T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A and T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A and T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A and T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the A and T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A and T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 848 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

Observation Wells

MD/PA Sandy Supplemental Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G14PD00397 Woolpert Order No. 74333 CONTRACTOR: Woolpert, Inc. This task is for a high resolution data set of lidar covering approximately 1,845 square miles. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format, and 8-bit intensity images. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format, and LAS swath data. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. Coastal tiles 18SVH065720 and 8SVH095690 contain no lidar points as they exist completely in water. A DEM IMG was generated for these two tiles as the digitized hydro breakline assumed the data extent in the area. As such only 2568 LAS and Intensity files will be delivered along with 2570 DEM IMG's.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Image Service Link: https://mdgeodata.md.gov/lidar/rest/services/Carroll/MD_carroll_shadedRelief_RGB/ImageServer

FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme, orthographic imagery, is packaged in a separate NFIP Metadata Profile): cadastral, geodetic control, governmental unit, transportation, general structures, hydrography (water areas & lines). These data include an encoding of the geographic extent of the features and a minimal number of attributes needed to identify and describe the features. (Source: Circular A16, p. 13)

Tags survey, environmental behaviors, lifestyle, status, PRIZM, Baltimore Ecosystem Study, LTER, BES Summary BES Research, Applications, and Education Description XY Positions for BES telephone survey. The BES Household Survey 2003 is a telephone survey of metropolitan Baltimore residents consisting of 29 questions. The survey research firm, Hollander, Cohen, and McBride conducted the survey, asking respondents questions about their outdoor recreation activities, watershed knowledge, environmental behavior, neighborhood characteristics and quality of life, lawn maintenance, satisfaction with life, neighborhood, and the environment, and demographic information. The data from each respondent is also associated with a PRIZM� classification, census block group, and latitude-longitude. PRIZM� classifications categorize the American population using Census data, market research surveys, public opinion polls, and point-of-purchase receipts. The PRIZM� classification is spatially explicit allowing the survey data to be viewed and analyzed spatially and allowing specific neighborhood types to be identified and compared based on the survey data. The census block group and latitude-longitude data also allow us additional methods of presenting and analyzing the data spatially. The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. The BES 2003 telephone survey was conducted by Hollander, Cohen, and McBride from September 1-30, 2003. The sample was obtained from the professional sampling firm Claritas, in order that their "PRIZM" encoding would be appended to each piece of sample (telephone number) supplied. Mailing addresses were also obtained so that a postcard could be sent in advance of interviewers calling. The postcard briefly informed potential respondents about the survey, who was conducting it, and that they might receive a phone call in the next few weeks. A stratified sampling method was used to obtain between 50 - 150 respondents in each of the 15 main PRIZM classifications. This allows direct comparison of PRIZM classifications. Analysis of the data for the general metropolitan Baltimore area must be weighted to match the population proportions normally found in the region. They obtained a total of 9000 telephone numbers in the sample. All 9,000 numbers were dialed but contact was only made on 4,880. 1508 completed an interview, 2524 refused immediately, 147 broke off/incomplete, 84 respondents had moved and were no longer in the correct location, and a qualified respondent was not available on 617 calls. This resulted in a response rate of 36.1% compared with a response rate of 28.2% in 2000. The CATI software (Computer Assisted Terminal Interviewing) randomized the random sample supplied, and was programmed for at least 3 attempted callbacks per number, with emphasis on pulling available callback sample prior to accessing uncalled numbers. Calling was conducted only during evening and weekend hours, when most head of households are home. The use of CATI facilitated stratified sampling on PRIZM classifications, centralized data collection, standardized interviewer training, and reduced the overall cost of primary data collection. Additionally, to reduce respondent burden, the questionnaire was revised to be concise, easy to understand, minimize the use of open-ended responses, and require an average of 15 minutes to complete. The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data, including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. Additional documentation of this database is attached to this metadata and includes 4 documents, 1) the telephone survey, 2) documentation of the telephone survey, 3) metadata for the telephone survey, and 4) a description of the attribute data in the BES survey 2003 survey. This database was created by joining the GDT geographic database of US Census Block Group geographies for the Baltimore Metropolitan Statisticsal Area (MSA), with the Claritas PRIZM database, 2003, of unique classifications of each Census Block Group, and the unique PRIZM code for each respondent from the BES Household Telephone Survey, 2003. The GDT database is preferred and used because of its higher spatial accuracy than other databases describin... Visit https://dataone.org/datasets/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-bes%2F337%2F610 for complete metadata about this dataset.

MD/PA Sandy Supplemental Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G14PD00397 Woolpert Order No. 74333 CONTRACTOR: Woolpert, Inc. This task is for a high resolution data set of lidar covering approximately 1,845 square miles. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format, and 8-bit intensity images. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format, and LAS swath data. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. Coastal tiles 18SVH065720 and 8SVH095690 contain no lidar points as they exist completely in water. A DEM IMG was generated for these two tiles as the digitized hydro breakline assumed the data extent in the area. As such only 2568 LAS and Intensity files will be delivered along with 2570 DEM IMG's.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Image Service Link: https://mdgeodata.md.gov/lidar/rest/services/Carroll/MD_carroll_aspect_m/ImageServer

Park Sites and Trails in Carroll County, Maryland

Rural Legacy Areas for Carroll County Maryland

This GIS database is a generalized land cover database designed for Regional Planning with a land use component used for forecasts and modeling at ARC. LandPro should not be taken out of its Regional context, though county-level or municipal-level analysis may be useful for transportation, environmental and land use planning.

Description This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission and is a generalized land cover database designed for regional planning with a land use component used for forecasts and modeling at ARC. LandPro2012 should not be taken out of its regional context, though county-level or municipal-level analysis may be useful for transportation, environmental and land use planning. LandPro2012 is ARC's land use/land cover GIS database for the 21-county Atlanta Region (Cherokee, Clayton, Cobb, DeKalb, Douglas, Fayette, Fulton, Gwinnett, Henry, Rockdale, the EPA non-attainment (8hr standard) counties of Carroll, Coweta, Barrow, Bartow, Forsyth, Hall, Newton, Paulding, Spalding and Walton and Dawson which will become a part of the 2010 Urbanized Area). LandPro2012 was created by on-screen photo-interpretation and digitizing of ortho-rectified aerial photography. The primary source for this GIS database were the local parcels and the 2009 true color imagery with 1.64-foot pixel resolution, provided by Aerials Express, Inc. 2010 is the first year we have used parcel data to help more accurately delineate the LandPro categories.For ArcGIS 10 users: See full metadata by enabling FGDC metadata in ArcCatalog Customize > ArcCatalog Options > Metadata (tab)Though the terms are often used interchangeably, land use and land cover are not synonymous. Land cover generally refers to the natural or cultivated vegetation, rock, or water covering the land, as well as the developed surface which can be identified on aerial photography. Land use generally refers to the way that humans use or will use the land, regardless of its apparent land cover. Collateral data for the land cover mapping effort included the Aero Surveys of Georgia street atlas, the Georgia Department of Community Affairs (DCA) Community Facilities database and the USGS Digital Raster Graphics (DRGs) of 1:24,000 scale topographic maps. The land use component of this database was added after the land cover interpretation was completed, and is based primarily on ownership information provided by the 21 counties and the City of Atlanta for larger tracts of undeveloped land that meet the land use definition of "Extensive Institutional" or "Park Lands" (refer to the Code Descriptions and Discussion section below). Although some of the boundaries of these tracts may align with visible features from the aerial photography, these areas are generally "non-photo-identifiable," thus require other sources for accurate identification. The land use/cover classification system is adapted from the USGS (Anderson) classification system, incorporating a mix of level I, II and III classes. There are a total of 25 categories in ARC's land use/cover system (described below), 2 of which are used only for land use designations: Park Lands (Code 175) and Extensive Institutional (Code 125). The other 23 categories can describe land use and/or land cover, and in most cases will be the same. The LU code will differ from the LC code only where the Park Lands (Code 175) and Extensive Institutional (Code 125) land holdings have been identified from collateral sources of land ownership.Although similar to previous eras of ARC land use/cover databases developed before 1999 (1995, 1990 etc.), "LandPro" differs in many significant ways. Originally, ARC's land use and land cover database was built from 1975 data compiled by USGS at scales of 1:100,000 and selectively, 1:24,000. The coverage was updated in 1990 using SPOT satellite imagery and low-altitude aerial photography and again in 1995 using 1:24,000 scale panchromatic aerial photography. Unlike these previous 5-year updates, the 1999, 2001, 2003, 2005 2007, 2008 and 2009 LandPro databases were compiled at a larger scale (1:14,000) and do not directly reflect pre-1999 delineations. In addition, all components of LandPro were produced using digital orthophotos for on-screen photo-interpretation and digitizing, thus eliminating the use of unrectified photography and the need for data transfer and board digitizing. As a result, the positional accuracy of LandPro is much higher than in previous eras. There have also been some changes to the classification system prior to 1999. Previously, three categories of Forest (41-deciduous, 42-coniferous, and 43-mixed forest) were used; this version does not distinguish between coniferous and deciduous forest, thus Code 40 is used to simply designate Forest. Likewise, two categories of Wetlands (61-forested wetland, and 62-non-forested wetland) were used before; this version does not distinguish between forested and non-forested wetlands, thus Code 60 is used to simply designate Wetlands. With regard to Wetlands, the boundaries themselves are now based on the National Wetlands Inventory (NWI) delineations along with the CIR imagery. Furthermore, Code 51 has been renamed "Rivers" from "Streams and Canals" and represents the Chattahoochee and Etowah Rivers which have been identified in the land use/cover database. In addition to these changes, Code 52 has been dropped from the system as there are no known instances of naturally occurring lakes in the Region. Finally, the land use code for Park Lands has been changed from 173 to 175 so as to minimize confusion with the Parks land cover code, 173. There has been a change in the agriculture classification for LandPro2005 and any LandPro datasets hereafter. Previously, four categories of agriculture (21- agriculture-cropland and pasture, 22 - agriculture - orchards, 23 - agriculture - confined feeding operations and 24 - agriculture - other) were used; this version does not distinguish between the different agricultural lands. Code 20 is now used to designate agriculture. Due to new technology and the enhancements to this database, direct comparison between LandPro99, LandPro2001, LandPro2003 and landPro2005 and all successive updates are now possible, with the 1999 database serving as ARC's new baseline. Please note that as a result of the 2003 mapping effort, LandPro2001 has been adjusted for better comparison to LandPro2003 and is named "LandPro01_adj." Likewise, LandPro99 was previously adjusted when LandPro2001 was completed, but was not further adjusted following the 2003 update. Although some adjustments were originally made to the 1995 land use/cover database for modeling applications, direct comparisons to previous versions of ARC land use/cover before 1999 should be avoided in most cases.The 2010 update has moved away from using the (1:14,000) scale, as will any future updates. Due to the use of local parcels, we have begun to snap LandPro boundaries to the parcel data, making a more accurate dataset. The major change in this update was to make residential areas reflect modern zoning codes more closely. Due to these changes you will no longer be able to compare this dataset to previous years. High density (113) has changed from lots below .25 to lots .25 and smaller. Medium density (112) has changed from .25 to 2 acre lots, to .26 to 1 acre lots. Low density has changed from 2 to 5 acre lots to 1.1 to 2 acre lots. It must be noted that in the 2010 update, you still have old acreage standards reflected in the low density. This will be corrected in the 2011 and 2012 updates. The main focus of the 2010 update was to make sure the LandPro' residential areas reflected the local parcels and change LandPro based on the parcel acreage. DeKalb is the only county not corrected at this time because no parcels were available. The future updates will consist of but are not limited to, reclassifying areas in 111 that do not meet the new acreage standards, delineating and reclassifying Cell Towers, substations and transmission lines/power cuts from TCU (14) to a subset of this (142), reclassifying airports as 141 form TCU, and reclassifying landfills form urban other (17) to 174. Other changes are delineating more roads other than just Limited Access Highways, making sure parks match the already existing Land use parks layer, and beginning to differentiate office from commercial and commercial/industrial.Classification System:111: Low Density Single Family Residential - Houses on 1.1 - 2 acre lots. Though 2010 still reflects the old standard of lots up to 5 acres.112: Medium Density Single Family Residential - These areas usually occur in urban or suburban zones and are generally characterized by houses on .26 to 1 acre lots. This category accounts for the majority of residential land use in the Region and includes a wide variety of neighborhood types.113: High Density Residential - Areas that have predominantly been developed for concentrated single family residential use. These areas occur almost exclusively in urban neighborhoods with streets on a grid network, and are characterized by houses on lots .25 acre or smaller but may also include mixed residential areas with duplexes and small apartment buildings.117: Multifamily Residential - Residential areas comprised predominantly of apartment, condominium and townhouse complexes where net density generally exceeds eight units per acre. Typical apartment buildings are relatively easy to identify, but some high rise structures may be interpreted as, or combined with, office buildings, though many of these dwellings were identified and delineated in downtown and midtown for the first time with the 2003 update. Likewise, some smaller apartments and townhouses may be interpreted as, or combined with, medium- or high-density single family residential. Housing on military bases, campuses, resorts, agricultural properties and construction work sites is

Parcels subject to residenital development plans currently under review in Carroll County, Maryland

Carroll County zoning layer

Download .zipA potentiometric surface map is a contour map that represents the top of the ground water surface in an aquifer. The contour lines illustrate the potentiometric surface much like the contour lines of a topographic map represent a visual model of the ground surface. A potentiometric surface map is very similar to a water table map in that both show the horizontal direction and gradient of ground water flow.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesDivision of Geological Survey2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6693Email: gis.support@dnr.ohio.gov