ZIP Code boundaries in Chicago. The data can be viewed on the Chicago Data Portal with a web browser. However, to view or use the files outside of a web browser, you will need to use compression software and special GIS software, such as ESRI ArcGIS (shapefile) or Google Earth (KML or KMZ).

The geometry of this shapefile was derived from the parcel specific ZIP Code Boundaries used by Los Angeles County's geocoding services, also available on the Los Angeles County GIS Data Portal. The 19 regional offices of the Department of Children and Family Services (DCFS) use these boundaries to provide services and resources to the children and families of the different geographic areas within Los Angeles County.DCFSOFFICE: DCFS Regional Office assigned to this ZIP CodeD_SPA: Dominant Service Planning Area (SPA)OFFC_CODE: Internal DCFS useD_ADDR1: Address Line 1D_ADDR2: Address Line 2D_PHONE: PhoneGMAP_URL: Google Maps URL for directionsOFFC_X: CCS83 Zone 5 XOFFC_Y: CCS83 Zone 5 YDCFSLBL: Regional Office LabelZIPTXT: ZIP Code text valueZIP: ZIP Code numeric valueCOMMUNITY: Postal CityC_TYPE: Community TypeZIPTYP: ZIP Code TypeCOLOR_EGIS: Assigned color used in mappingCOLOR_HEX: Same assigned colors, expressed as hex valuesFor more information, visit the home site at https://dcfs.lacounty.gov/contact/regional-offices/Child Abuse Hotline, accessible 24 hours per day, 7 days a week: (800) 540-4000 or visit https://dcfs.lacounty.gov/contact/report-child-abuse/

Context

The United States Census is a decennial census mandated by Article I, Section 2 of the United States Constitution, which states: "Representatives and direct Taxes shall be apportioned among the several States ... according to their respective Numbers."
Source: https://en.wikipedia.org/wiki/United_States_Census

Content

The United States census count (also known as the Decennial Census of Population and Housing) is a count of every resident of the US. The census occurs every 10 years and is conducted by the United States Census Bureau. Census data is publicly available through the census website, but much of the data is available in summarized data and graphs. The raw data is often difficult to obtain, is typically divided by region, and it must be processed and combined to provide information about the nation as a whole.

The United States census dataset includes nationwide population counts from the 2000 and 2010 censuses. Data is broken out by gender, age and location using zip code tabular areas (ZCTAs) and GEOIDs. ZCTAs are generalized representations of zip codes, and often, though not always, are the same as the zip code for an area. GEOIDs are numeric codes that uniquely identify all administrative, legal, and statistical geographic areas for which the Census Bureau tabulates data. GEOIDs are useful for correlating census data with other censuses and surveys.

Fork this kernel to get started.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:census_bureau_usa

https://cloud.google.com/bigquery/public-data/us-census

Dataset Source: United States Census Bureau

Use: This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by Steve Richey from Unsplash.

Inspiration

What are the ten most populous zip codes in the US in the 2010 census?

What are the top 10 zip codes that experienced the greatest change in population between the 2000 and 2010 censuses?

https://cloud.google.com/bigquery/images/census-population-map.png" alt="https://cloud.google.com/bigquery/images/census-population-map.png"> https://cloud.google.com/bigquery/images/census-population-map.png

Vector polygon map data of city limits from Houston, Texas containing 731 features.

City limits GIS (Geographic Information System) data provides valuable information about the boundaries of a city, which is crucial for various planning and decision-making processes. Urban planners and government officials use this data to understand the extent of their jurisdiction and to make informed decisions regarding zoning, land use, and infrastructure development within the city limits.

By overlaying city limits GIS data with other layers such as population density, land parcels, and environmental features, planners can analyze spatial patterns and identify areas for growth, conservation, or redevelopment. This data also aids in emergency management by defining the areas of responsibility for different emergency services, helping to streamline response efforts during crises..

This city limits data is available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

Context

In order to complete our group project, which is abour developing a website to find vaccine station in Los Angeles County, in EE599 USC. We scraped two website to get our dataset.

Content

At first, we scraped the Los Angeles Almanac to get the whole zip codes of Los Angeles County. The zip codes are store in zipcode.json. It will include some zip codes, which are not used nowadays.

Los Angeles County: http://www.laalmanac.com/communications/cm02_communities.php

Secondly, we scraped Google Map to get the position of each zip code. The position is presented by the form of latitude and longitude. The postion info is stored in zip2pst.json.

At last, we scraped the VaccineFinder to get the information about the providers info and vaccine information, which are stored in porviders.json and providers_info.json. VaccineFinder: https://www.vaccines.gov/

West Allis Parcel Web Viewer is a GIS Web application that helps citizens identify their parcel and obtain information about it as well as information about their surrounding Neighborhood. This application is typically used by citizens to see their parcel assessed valuation, and compare it to other parcels in their neighborhood, but it can be used for many other uses as well. You can also see the Schools in West Allis, both public and private, as well as the West Allis West Milwaukee Public School District boundaries. Additionally, you can view zip code areas, Neighborhood District boundaries, Assessment boundaries for Residential and Commercial neighborhoods, Census 2010 Tracts, Block Groups, and Blocks, Zoning Districts, TIF and BID Districts, Existing Land Use, Land Use 2010, and Comp Plan 2030 Land Use. There is also an Intersection Bing Google feature that when turned on and clicked, will link you directly to either a Bing Map or Google Map of the area providing additional aerial photos. The Viewer will extend out to the limits of Milwaukee County, and show you Municipal Divisions in Waukesha County as well. Ortho Photo coverage for all of Milwaukee County is using the latest 2015 and 2018 imagery. West Allis Parcel Viewer Map can be used by anyone who needs to check out a parcel of land within West Allis, WI. This application provides 24/7 access to the parcel information and typically supplements customer service phone calls to City Staff with questions concerning a particular parcel

Firmographic Data for Company Intelligence, B2B Segmentation & KYB Firmographic data is the backbone of modern B2B decision-making, powering everything from lead scoring and segmentation to compliance, financial benchmarking, and market expansion planning. Canaria’s enriched Firmographic Data product delivers deep visibility into U.S. companies by combining standardized insights on revenue ranges, employee count, and business category with optional location verification through Google Maps metadata.

This clean and analysis-ready firmographic dataset is built for precision. Every record is structured, normalized, and deduplicated to support automated workflows across CRMs, BI dashboards, compliance tools, financial models, and sales platforms. Updated weekly, our firmographic data ensures that teams stay ahead of organizational shifts, while providing the matchability and granularity required to fuel market intelligence at scale.

If you're working with fragmented company information, incomplete lead lists, or outdated third-party data, Canaria’s Firmographic Data bridges the gap between surface-level signals and operational insight.

Use Cases: What This Firmographic Data Solves Canaria’s firmographic data offering is used by sales, risk, finance, compliance, and strategy teams to strengthen daily operations, strategic planning, and automation initiatives.

Company Analysis • Leverage firmographic data to assess a company’s size, structure, and potential impact within its industry • Identify organizational tiers using clean employee size brackets, location counts, and business hierarchy insights • Analyze firmographic profiles at the branch level, matched with Google Maps data to verify presence, operating hours, and reviews • Map the operational footprint of enterprises across ZIP codes, cities, and regions for trend tracking or competitive benchmarking

Know Your Business (KYB) & Regulatory Compliance • Use firmographic signals such as company type, headquarters address, incorporation location, and estimated size for KYB verification • Identify shell entities or mismatched records using cross-source validation with Google Maps-matched firmographic data • Flag risk-prone entities based on abnormal size-revenue-industry patterns or gaps in metadata • Enhance onboarding pipelines and due diligence platforms by auto-enriching firmographic gaps at scale • Comply with local and international KYB regulations with standardized firmographic data structures

Financial Intelligence & Private Market Benchmarking • Use estimated firmographic variables like annual revenue range, employee count, and industry focus to model private market behavior • Benchmark companies against similar-sized peers within the same vertical, region, or revenue bracket • Replace missing financials with proxy signals from enriched firmographic datasets for internal modeling and client analysis • Feed investor signals and fund models with data on size trends, regional density, and revenue tier shifts • Correlate firmographic data with job postings, hiring behavior, and sentiment for growth prediction models

Market Research, TAM/SAM Modeling & Industry Intelligence • Conduct high-resolution market mapping by combining industry codes, company counts, and firm size across specific geographies • Map sector saturation and whitespace using city, ZIP code, or state-level firmographic intelligence • Analyze shifts in vertical presence, workforce concentration, and mid-market vs. enterprise distribution • Tailor customer segmentation models using clean and consistent firmographic fields • Build TAM/SAM datasets using industry, employee size, revenue tier, and location granularity

B2B Lead Generation & RevOps Segmentation • Score and segment inbound leads using enriched firmographic attributes such as company size, region, industry, and revenue • Eliminate low-value or unqualified leads from prospecting databases by applying firmographic filters • Route leads to the right sales reps or vertical pods based on company headcount, location, and category • Enrich lead records automatically with up-to-date firmographic data pulled from verified external sources • Build ABM lists using revenue-based tiers, industry verticals, and mapped branch data via Google Maps enrichment

What Makes This Firmographic Data Unique Deep Enrichment with Verified Firmographic Attributes • Our firmographic data includes revenue range, employee size bracket, industry classification, company type, and regional identifiers — all normalized to enable aggregation, filtering, and modeling.

Matchable with Google Maps for Accuracy and Context • Match your firmographic records with Google Maps to verify physical branch presence, exact addresses, latitude/longitude, phone numbers, and ratings. This adds a real-world signal layer to abstract company data and supports KYB, lead scoring, and risk assessment.

Continuously Updated and Scalable • Weekly refreshes ensure your firmographi...

This land cover data set is derived from the original raster based Globcover regional (Africa) archive. It has been post-processed to generate a vector version at national extent with the LCCS regional legend (46 classes). This database can be analyzed in the GLCN software Advanced Database Gateway (ADG), which provides a user-friendly interface and advanced functionalities to breakdown the LCCS classes in their classifiers for further aggregations and analysis.

The data set is intended for free public access.

The shape file's attributes contain the following fields: -Area (sqm) -ID -Gridcode (Globcover cell value) -LCCCode (unique LCCS code)

You can download a zip archive containing: -the shape file (.shp) -the ArcGis layer file with global legend (.lyr) -the ArcView 3 legend file (.avl) -the LCCS legend tables (.xls)

Supplemental Information:

This land cover product is a vector version (ESRI shape) of the Globcover archive that was published in 2008 as result of an initiative launched in 2004 by the European Space Agency (ESA). Globcover is currently the most recent (2005) and resoluted (300 m) datasets on land cover globally. Given the need of this valuable information for environmental studies, natural resources management and policy formulation, through activities of the Global Land Cover Network (GLCN) programme, the Globcover has been reprocessed to generate databases at national extent that can be analyzed through the Advanced Database Gateway software (ADG) by GLCN. ADG is a cross-cutting interrogation software that allows the easy and fast recombination of land cover polygons according to the individual end-user requirements. Aggregated land cover classes can be generated not only by name, but also using the set of existing classifiers. ADG uses land cover data with a Land Cover Classification System (LCCS) legend. The ADG software is available for download on the GLCN web site at http://www.glcn.org/sof_7_en.jsp

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Antonio Martucci

Data lineage:

This land cover database is provided as ESRI shape file (vector format) and derives from reprocessing the raster based Globcover database (regional version). Globcover has undergone the following process: a) vectoralization at the national extent using ESRI ArcGis (arcinfo) 9.3; b) topological reconstruction (custom AML scripts launched inside ArcGis-arcinfo 9.3); c) simplification of areas according to a minimum mapping unit of 0.1 skim (10 ha) (custom AML scripts launched inside ArcGis-arcinfo 9.3); application of the FAO/UNEP Land Cover Classification System (LCCS) legend (46 classes); final processing to assure full compatibility with the GLCN software Advanced Database Gateway (ADG).

Online resources:

Download - Land cover of Ethiopia - Shape file format

GLOBCOVER on the ESA Web site

Global Land Cover Network - GLCN

We combined regeneration density observations from the German NFI to map the forest regeneration across Germany and evaluate potential regeneration gaps using a three-step approach. First, we combined the NFI regeneration data with environmental data to construct species-specific regeneration models. Second, we evaluated the predictive performance of the regeneration models using 10-fold blocked cross-validation and used the validated models to predict regeneration densities for the forest area of Germany. Third, we mapped indicators of regeneration quantity and quality, demonstrating their potential application for Bavaria.

Here this repository consists of:

• data.zip (input data)
• output.zip (output data)
• GermanRegenerationMaps2012_workflow.png (code workflow to generate output.zip from data.zip)
• Predictors.png (information on predictor variables)

See additional information in related works:

• for full data references please look up our preprint
• for related code see GitHub and Zenodo
• to view and explore the generated regeneration maps online please see Google Earth Engine