The My Neighborhood - Property application allows users to find property information for Baltimore County. This includes parcels and zoning information. Users have the ability to create a customized, printable map as well as a property information report. Users can search for a property and generate a report by entering in an address or 10-digit tax account id

The layer will be removed from the iMap Data Catalog in the near future. To access the most recent Baltimore City neighborhood data please visit https://data.baltimorecity.gov/datasets/baltimore::neighborhood-1.

This data shows the extends of the community associations in Baltimore County. It gives the name of the association and if the association is currently active in Baltimore County. This data can be linked to the Planning Dept. "contacts" database which contains the association contact information, president, terms, bylaws, etc.

Boundaries for all the adopted community plans in Baltimore County. Community Plans are created to develop community-specific detail, relevant policies, and implementation strategies necessary to fulfill planning objectives of the communities.

Neighborhoods within Baltimore City limits. This dataset was sourced from Baltimore Neighborhood Indicators Alliance (BNIA). No additional metadata was provided with the dataset. This is part of a collection of 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.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Baltimore County, MD (S1701ACS024005) from 2012 to 2023 about Baltimore County, MD; Baltimore; MD; poverty; percent; 5-year; population; and USA.

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

The COUNTY_FACILITIES feature class is a point feature class derived from data in the Facilities Geodatabase. This feature class stores a variety of facilities that are owned by Baltimore County or are important to citizens of Baltimore County. The feature class contains attributes including the facility name, address, ADC grid, facility use classifications, and some additional contact information for certain facilities. This feature class is still being developed. Eventually this feature class will contain every facility theme that is currently in the MyNeighborhood:Facilities application, as well as several other facility themes. A facility theme is a high level classification of a group of facilities in this feature class. Facility Themes include Public Schools, Colleges, Courthouses, Libraries, County Offices, etc. New facility themes will be added to this feature class once the theme has been certified as accurate and complete for the entire county. Currently the following facility themes have been added to the COUNTY_FACILITIES feature class: Public Schools; Colleges and Universities; Park and Ride Lots; Courthouses; Correctional Facilities; Police Facilities; Libraries; County Council Offices; County Offices; Senior Centers; Social Services Centers; County Health Sites; Hospitals; Fire Stations; Landfills; Revenue Authority Parking Garages; Revenue Authority Golf Courses; Commuter Rail Stations; 800 MHZ Towers; DPW Highway Shops; County WIC Centers Within a facility theme there may also exist several facility types. For example, the public schools facility theme has four different facility types: Elementary, Middle, High, and Special Education. Some facility themes will only have one facility type. This feature class also has a field named MAP_LABEL, which is an abbreviated facility name for mapping purposes. The COUNTY_FACILITIES feature class stores links to the facilities geodatabase. Most of the data in this feature class is pulled from the facilities geodatabase, however some fields are stored only in this feature class. The fields for phone number, fax, website, hours, centrex, and acres are all stored in this feature class. Not all of these fields will be populated for each facility theme. Organization Abbreviations BCOPD - Baltimore County Police Department BCOFD - Baltimore County Fire Department BCVFA - Baltimore County Volunteer Firemen's Association BCRA - Baltimore County Revenue Authority MTA - Maryland Transit Administration SHA - State Highway Administration MSP - Maryland State Police MEMA - Maryland Emergency Management Agency DPW - Department of Public Works CCBC - Community College of Baltimore County UMBC - University of Maryland Baltimore County BCPL - Baltimore County Public Library USMAI - University System of Maryland and Affiliated Institutions (Consortium of Libraries) Other Abbreviations CSAFE - Collaborative Supervision And Focused Enforcement (Police Program) PAL - Police Athletic League WIC - Women, Infants, and Children (County Program) MARC - Maryland Area Regional Commuter (MTA Train Service) ES - Elementary School MS - Middle School HS - High School SES - Special Education School P & R - Park and Ride GC - Golf Course

This EnviroAtlas dataset shows the Baltimore, MD EnviroAtlas community boundary. It represents the outside edge of all the block groups included in the EnviroAtlas Community. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This is a MD iMAP hosted service. Find more information on http://imap.maryland.gov. ' above published service description.A representation of the boundaries of Baltimore City neighborhoods. The data can be obtained from the Baltimore City Open Data Portal at https://data.baltimorecity.gov/Neighborhoods/Neighborhoods-Shape/ysi8-7icr. Map Service Link: http://geodata.md.gov/appdata/rest/services/ TrainingProgram/MD_BaltimoreCityNeighborhoods/FeatureServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

Because the Master Plan is providing higher level countywide strategies, the recommendations may not be tangible enough for a community to implement at a local level. Systematic development of small area community plans allow the Department of Planning to identify more specific place-based strategies to support the future land use and development trajectory of Baltimore County’s communities.

Small area community plans can help to fine-tune and align land use planning with economic development strategies, providing a valuable roadmap for securing additional state, federal, and private funding to implement those specific strategies. They are also useful for targeting areas of focus for the County, such as such as vacant commercial areas, corridors, and other priorities of the County’s strategic plan.

This study examined the effects of police arrest policies and incarceration policies on communities in 30 neighborhoods in Baltimore. Specifically, the study addressed the question of whether aggressive arrest and incarceration policies negatively impacted social organization and thereby reduced the willingness of area residents to engage in informal social control, or collective efficacy. CRIME CHANGES IN BALTIMORE, 1970-1994 (ICPSR 2352) provided aggregate community-level data on demographics, socioeconomic attributes, and crime rates as well as data from interviews with residents about community attachment, cohesiveness, participation, satisfaction, and experiences with crime and self-protection. Incident-level offense and arrest data for 1987 and 1992 were obtained from the Baltimore Police Department. The Maryland Department of Public Safety and Corrections provided data on all of the admissions to and releases from prisons in neighborhoods in Baltimore City and Baltimore County for 1987, 1992, and 1994.

RecCenters_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Recreational, Rec Summary BES analysis. Description Recreational Centers in Baltimore City. This dataset was obtained from BNIA; no metadata was provided. A limited assessment comparing this dataset to IKONOS imagery acquired in 2001 indicates that the point locations have most likely been geocoded and thus are in the vicinity of, but generally not at the precise location of the facility. Credits BNIA Use limitations BES research only. Extent West -76.695292 East -76.535325 North 39.367133 South 39.223398 Scale Range There is no scale range for this item.

Geocoded for Baltimore County. 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(r) classification, census block group, and latitude-longitude. PRIZM(r) classifications categorize the American population using Census data, market research surveys, public opinion polls, and point-of-purchase receipts. The PRIZM(r) 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 describing US Census geographies, including those provided by the US Census. This database includes data only for environmental behaviors: How likely would you be to take part in the following efforts to improve and maintain the quality of the watersheds near where you live, very unlikely, somewhat unlikely, somewhat likely, very likely? a) pay increased

The Baltimore Regional Neighborhood Initiative (BRNI) program aims to demonstrate how strategic investment in local housing and businesses can lead to healthy, sustainable communities with a growing tax base and enhanced quality of life. The program attempts to focus on areas where modest investment and a coordinated strategy will have an appreciable neighborhood revitalization impact. Community Development Organizations with an approved strategic neighborhood revitalization plan may apply for Baltimore Regional Neighborhood Initiative funding for projects located in Sustainable Community Areas in Baltimore City and inner beltway of Baltimore and Anne Arundel counties.If a Community Development Organization is interested in applying to the program and does not have an approved strategic neighborhood revitalization plan, then it must submit a plan at the time of application along with its projects for which it is requesting funds. Prior to any funding awards, the strategic neighborhood revitalization plan must be approved by the Department.Community Development Organizations are strongly recommended to apply with partner organizations, including Community Development Financial Institutions. Cross-jurisdictional partnerships are eligible and encouraged.

Comprehensive demographic dataset for Baltimore County County, MD, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Baltimore County's 17 officially designated Commercial Revitalization Districts are the "front doors" to our desired established communities. Each district is staffed by a planner who works closely with the business and property owners, business associations and the local communities to provide a range of services aimed at maintaining the health and vitality of our neighborhood commercial areas.

Median household income is the middle value of the incomes earned in the prior year by households in an area. Income and earnings are inflation-adjusted for the last year of the 5-year period. The median value is used as opposed to the average so that both extremely high and extremely low prices do not distort the total amount of income earned by households in an area. Source: American Community SurveyYears Available: 2006-2010, 2007-2011, 2008-2012, 2009-2013, 2010-2014, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, 2016-2020, 2017-2021, 2018-2022, 2019-2023Please note: We do not recommend comparing overlapping years of data due to the nature of this dataset. For more information, please visit: https://www.census.gov/programs-surveys/acs/guidance/comparing-acs-data.html

These retrofit areas were producing by overlaying certain weighted data layers based on the following categories:• Transportation Access• Land Use/Ownership • Funding Resources• Demographic Status• Neighborhood Deficiency• Neighborhood Assets• Employment OppotunitiesThe data layers and their weights were unioned together into one layer and broken out into 5 categories based on the total weight for each area. Lowest (0-10); Low (11-16); Moderate (17-21); High (22-24); Highest (25-43). This data layer places a centralized point with a point ID, name and defined place type over areas in Baltimore County that were identified as prime for redevelopment at a more dense capacity.

This dataset includes census block group level component scores of various indices from the National Centers for Coastal Ocean Science (NCCOS) Community Risk Assessment of Flooding and Heat Hazards in Baltimore, MD. Indices included in this archived dataset include SoVI(R), ecosystem services valuation, structural exposure, urban heat hazard, and flood hazard. Each component score is aggregated...