This data is a layer file depicting all County-owned parks, greenspaces and recreational spaces in DeKalb County, GA. This layer file was developed for the DeKalb County Department of Parks, Recreation and Cultural Affairs to provide baseline data for parks, greenspace and recreational spaces within the County

This layer is a component of Dekalb County tax maps.

The data shows the legal boundaries of the municipalities in DeKalb County, GA.

Road segments representing centerlines of all roadways or carriageways in a local government. Typically, this information is compiled from orthoimagery or other aerial photography sources. This representation of the road centerlines support address geocoding and mapping. It also serves as a source for public works and other agencies that are responsible for the active management of the road network.

This is recent DeKalb County Address data. The data is being updated everyday.

DeKalb County parcel data merged with city-specific attributes. DeKalb County should be considered as the authoritative provider of parcel data. Projection is WGS84. Link to DeKalb County's Parcel Viewer

Discover the latest resources, maps and information about the coronavirus (COVID-19) outbreak in your community

This is a contour created from Lidar data in 2012.

This is Street Pavement data in DeKalb county, Georgia. These features were originally captured in 1995 and updated in 2012.The data is used as a layer in the DeKalb county basemap..

Feature layer generated from running the Join Features solution

This is water bodies data in DeKalb county, Georgia. The data is polygon features representing waterbodies. The data was acquired from aerial photography and Lidar in 1995 and updated in 2012.

DeKalb County Land Lots

This data is the trails of the PATH Foundation. Multi-use trails are created and maintained by the PATH Foundation. Data last updated 11/21/2016.CreditsPATH Foundation (www.pathfoundation.org).

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau.For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.Naming conventions:Prefixes: None Countp Percentr Ratem Mediana Mean (average)t Aggregate (total)ch Change in absolute terms (value in t2 - value in t1)pch Percent change ((value in t2 - value in t1) / value in t1)chp Change in percent (percent in t2 - percent in t1)s Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed Suffixes: _e19 Estimate from 2014-19 ACS_m19 Margin of Error from 2014-19 ACS_00_v19 Decennial 2000, re-estimated to 2019 geography_00_19 Change, 2000-19_e10_v19 2006-10 ACS, re-estimated to 2019 geography_m10_v19 Margin of Error from 2006-10 ACS, re-estimated to 2019 geography_e10_19 Change, 2010-19The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2015-2019). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2015-2019Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the manifest: https://www.arcgis.com/sharing/rest/content/items/3d489c725bb24f52a987b302147c46ee/data

This dataset represent the boundaries of Fulton County voting precincts. Voting precincts are districts created for the purpose of assigning voters to polling places based on their place of residence. The boundaries are defined by the Fulton County Department of Registration and Elections. The dataset includes all precincts in Fulton County but also includes precincts for the part of the city of Atlanta that lies in DeKalb County because the Fulton County Department of Registration and Elections conducts elections for the the city of Atlanta even though the precincts in DeKalb County are defined by DeKalb County. Precincts are identified by alphanumeric designators which typically begin with a two-letter prefix indicating the city in which they lie. For example, precinct JS09 lies in the city of Johns Creek. The only exception to this convention is assignment of designators for precincts in the city of Atlanta, which begin with a two digit number indicating the council district in which they lie followed by a letter or letter and number combination to make each designator unique. The designator is recorded in the dataset in the field VoterDist. Changes to precinct boundaries can be triggered by a number of events including the redistricting that occurs as part of the reapportionment process following the decennial census, annexation of land by municipalities, and requests from municipalities to change the number of precincts with their boundaries. Any change to a precinct boundary must go through a formal process that begins with the documentation of the proposed change, approval by the County Board of Registration and Elections and approval by the County Board of Commissioners.

Basemap for DeKalb County, Georgia

The signal inventory data is about the location of DeKalb County signal (traffic light) locations.The data was created by Thomas Lucky in 2021.------------------------------------------------------------------------------------------------Attribute infoDEKALB_ID – internal ID for each signal that corresponds to our and R&D’s signal inventory.

MAXVIEW_ID – ID for the statewide signal software

Location – 1st intersecting street of signal

Location_2 – 2nd intersecting street of signal

Location_3 – 3rd intersecting street of signal

STATE_RTE – State route number if it is on a state route

IP_ADDRESS – IP of controller in signal cabinet

GATEWAY – Gateway of controller in signal cabinet

MAINT_AGE – What agency maintains the signal

CITY – name of city of signal is in a city’s jurisdiction.

SIGNAL_SYS – Internal DeKalb number for signal system if in a coordinated signal system

MAXVIEW_SY – Number for statewide maxview software for a coordinated signal system

PDF_LINK – Link to pdf file of the signal design (wasn’t set up)

MICROSTATION – Link to microstation cadd drawing of signal (wasn’t set up)

Latitude – latitude coordinates

Longitude – longitude coordinates

SigOps_Reg – Region of the SigOps program the signal is in

Dunwoody was incorporated as a city in December, 2008. It is comprised of the northern tip of DeKalb County, Ga in the area north of I-285. Dunwoody is surrounded by cities on all sides and is 13.2 square miles.

This is Building Footprints data for DeKalb county, Georgia.

Truck routes of DeKalb County, Georgia. This dataset was derived from DeKalb County Code of Ordinances Article XXI, Sec. 17-361.