The World Cities Culture Forum, established in 2012, is a leading global network of civic leaders from over 40 creative cities across six continents, representing a combined population of over 245 million. The forum fosters collaborations to place culture at the core of urban development, addressing 21st-century challenges such as climate change, affordable workspaces, cultural tourism, and diversity in public spaces. Through its Global Summit, partnerships, and programs like the Leadership Exchange Programme and Digital Dialogue Masterclasses, the forum promotes cultural integration in city planning. The World Cities Culture Report 2022 provides comprehensive open-source data on culture, including over 60 datasets from 40 cities. Contextual Data: Includes demographics such as characteristics of the overall and working-age populations (including percent who were foreign born) and of the geographical area, such as the percentage of national population living in the city and the percentage of the area devoted to parks and other public green spaces. Cultural Infrastructure: Provides counts (and rates) of various facilities and venues, including art galleries, artists' studios, rehearsal spaces, bars, bookshops, cinemas, community centers, concert halls, museums, nightclubs, libraries, video game arcades, and theatres. Participation and Tourism: Focuses on cultural participation metrics, such as cinema and theatre admissions, festival attendance, museum visits, average daily attendance at the top five art exhibits, and international tourist numbers. Creative Economy: Encompasses data on book publishing, creative industries employment, film festivals, restaurant ratings, and performances. Education: Includes statistics on public library book loans, higher education levels, international student enrollment, and specialist institutes in art and design education. The source for each number is identified within the dataset. Data users can freely download selected datasets as .csv files.

All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

The World Council on City Data (WCCD) awarded the City of Melbourne a platinum designation for its compliance with ISO 37120 (http://www.iso.org/iso/catalogue_detail?csnumber=62436), the world’s first international standard for city indicators. Reporting to the standard allows cities to compare their service delivery and quality of life to other cities globally. The City of Melbourne was one on 20 cities to, globally to help pilot this program and is one of sixteen cities to receive the highest level of accreditation (platinum). \r
Having an international standard methodology to measure city performance allows the City of Melbourne to share data about practices in service delivery, learn from other global cities, rank its results relative to those cities, and address common challenges through more informed decision making. \r
Indicators include: Fire and emergency response; Governance; Health; Recreation; Safety; Shelter; Solid Waste; Telecommunications and Innovation; Transportation; Urban Planning; Wastewater; Water and Sanitation; Economy; Education; Energy; Environment; and Finance.\r
City of Melbourne also submitted an application for accreditation, on behalf of ‘Greater Melbourne’, to the World Council on City Data and this resulted in an ‘Aspirational’ accreditation awarded to wider Melbourne. \r
A summary of Melbourne's results is available here (http://open.dataforcities.org/). Visit the World Council on City Data’s Open Data Portal to compare our results to other cities from around the world.

A global self-hosted Market Research dataset containing all administrative divisions, cities, addresses, and zip codes for 247 countries. All geospatial data is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.

Use cases for the Global Zip Code Database (Market Research data)

• Address capture and validation

• Map and visualization

• Reporting and Business Intelligence (BI)

• Master Data Mangement

• Logistics and Supply Chain Management

• Sales and Marketing

Data export methodology

Our map data packages are offered in variable formats, including .csv. All geographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Product Features

• Fully and accurately geocoded

• Administrative areas with a level range of 0-4

• Multi-language support including address names in local and foreign languages

• Comprehensive city definitions across countries

For additional insights, you can combine the map data with:

• UNLOCODE and IATA codes

• Time zones and Daylight Saving Times

Why do companies choose our Market Research databases

• Enterprise-grade service

• Reduce integration time and cost by 30%

• Weekly updates for the highest quality

Note: Custom geographic data packages are available. Please submit a request via the above contact button for more details.

Some say climate change is the biggest threat of our age while others say it’s a myth based on dodgy science. We are turning some of the data over to you so you can form your own view.

Even more than with other data sets that Kaggle has featured, there’s a huge amount of data cleaning and preparation that goes into putting together a long-time study of climate trends. Early data was collected by technicians using mercury thermometers, where any variation in the visit time impacted measurements. In the 1940s, the construction of airports caused many weather stations to be moved. In the 1980s, there was a move to electronic thermometers that are said to have a cooling bias.

Given this complexity, there are a range of organizations that collate climate trends data. The three most cited land and ocean temperature data sets are NOAA’s MLOST, NASA’s GISTEMP and the UK’s HadCrut.

We have repackaged the data from a newer compilation put together by the Berkeley Earth, which is affiliated with Lawrence Berkeley National Laboratory. The Berkeley Earth Surface Temperature Study combines 1.6 billion temperature reports from 16 pre-existing archives. It is nicely packaged and allows for slicing into interesting subsets (for example by country). They publish the source data and the code for the transformations they applied. They also use methods that allow weather observations from shorter time series to be included, meaning fewer observations need to be thrown away.

In this dataset, we have include several files:

Global Land and Ocean-and-Land Temperatures (GlobalTemperatures.csv):

• Date: starts in 1750 for average land temperature and 1850 for max and min land temperatures and global ocean and land temperatures
• LandAverageTemperature: global average land temperature in celsius
• LandAverageTemperatureUncertainty: the 95% confidence interval around the average
• LandMaxTemperature: global average maximum land temperature in celsius
• LandMaxTemperatureUncertainty: the 95% confidence interval around the maximum land temperature
• LandMinTemperature: global average minimum land temperature in celsius
• LandMinTemperatureUncertainty: the 95% confidence interval around the minimum land temperature
• LandAndOceanAverageTemperature: global average land and ocean temperature in celsius
• LandAndOceanAverageTemperatureUncertainty: the 95% confidence interval around the global average land and ocean temperature

Other files include:

• Global Average Land Temperature by Country (GlobalLandTemperaturesByCountry.csv)
• Global Average Land Temperature by State (GlobalLandTemperaturesByState.csv)
• Global Land Temperatures By Major City (GlobalLandTemperaturesByMajorCity.csv)
• Global Land Temperatures By City (GlobalLandTemperaturesByCity.csv)

The raw data comes from the Berkeley Earth data page.

This table contains 45 series, with data for years 2014 - 2014 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Countries visited (15 items: United States; Mexico; United Kingdom; France; ...) Travel characteristics (3 items: Visits; Nights; Spending in country).

Key information about Poland Visitor Arrivals

• Poland Visitor Arrivals recorded 18,986,700 person in Dec 2023, compared with 15,947,700 person in the previous year
• Poland Visitor Arrivals data is updated yearly, available from Dec 1995 to Dec 2023
• The data reached an all-time high of 89,118,000 person in Dec 1999 and a record low of 8,418,000 person in Dec 2020

The number of international tourist arrivals worldwide rose sharply in 2023 compared to the previous year across all the most visited destinations in the world. Overall, France was the most visited country by inbound travelers worldwide in 2023, with *** million international tourist arrivals. Spain, the United States, and Italy followed in the ranking that year. Has global inbound tourism recovered from the impact of COVID-19? In 2023, the number of international tourist arrivals worldwide totaled approximately *** billion. While this figure represented a ** percent annual increase, it remained below the peak in inbound tourist arrivals reported in 2019, the year before the onset of the COVID-19 pandemic. That said, international tourism receipts worldwide exceeded pre-pandemic levels in 2023, peaking at *** trillion U.S. dollars. What are the most popular global regions for inbound tourism? When breaking down the number of international tourist arrivals worldwide by region, Europe has consistently reported the highest volume of inbound travelers, both before and after the impact of the health crisis. In 2023, this region alone accounted for roughly ** percent of global inbound tourist arrivals. Meanwhile, Asia and the Pacific recorded the second-highest number of inbound tourist arrivals worldwide in 2023.

Our location data powers the most advanced address validation solutions for enterprise backend and frontend systems.

A global, standardized, self-hosted location dataset containing all administrative divisions, cities, and zip codes for 247 countries.

All geospatial data for address data validation is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.

Use cases for the Address Validation at Zip Code Level Database (Geospatial data)

• Address capture and address validation

• Address autocomplete

• Address verification

• Reporting and Business Intelligence (BI)

• Master Data Mangement

• Logistics and Supply Chain Management

• Sales and Marketing

Product Features

• Dedicated features to deliver best-in-class user experience

• Multi-language support including address names in local and foreign languages

• Comprehensive city definitions across countries

Data export methodology

Our location data packages are offered in variable formats, including .csv. All geospatial data for address validation are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why do companies choose our location databases

• Enterprise-grade service

• Full control over security, speed, and latency

• Reduce integration time and cost by 30%

• Weekly updates for the highest quality

• Seamlessly integrated into your software

Note: Custom address validation packages are available. Please submit a request via the above contact button for more details.

This dataset describes Airbnb homestay listing activity in New Orleans, Louisiana. Compiled on 7 November 2021, it is part of the Inside Airbnb initiative, which aims to quantify the impact of short-term rentals on housing and residential communities. The data includes listing details and reviews, with personally identifying information removed.

It offers insights into the New Orleans short-term rental market, a city significantly impacted by Hurricane Katrina and subsequent redevelopment efforts, which have raised concerns about gentrification and resident displacement. The dataset allows users to explore fundamental questions about Airbnb's presence, such as the number of listings in a neighbourhood, how many properties are rented to tourists versus long-term residents, host earnings, and the prevalence of hosts operating multiple listings. It can also inform discussions around city and state legislation concerning residential housing, short-term rentals, and zoning.

Columns

• id: Airbnb's unique identifier for each listing.
• name: The name given to the listing.
• description: A detailed account of the listing.
• neighborhood_overview: The host's description of the local area.
• host_id: Airbnb's unique identifier for the host or user.
• host_since: The date the host or user account was created. For hosts who also use Airbnb as guests, this may be their guest registration date.
• host_location: The self-reported location of the host.
• host_response_time: The average duration it takes for a host to reply to a message on the Airbnb platform.
• host_response_rate: The percentage of messages a host responds to on the Airbnb platform.
• host_acceptance_rate: The rate at which a host accepts booking requests.

Distribution

The dataset is provided in CSV format, including new_orleans_airbnb_listings.csv and reviews.csv. Specific total row or record counts are not available within the provided information.

However, details on value distribution for certain columns are present: * host_id: 5,752 unique values. * host_location: 5,487 unique values, with 68% reporting 'New Orleans, Louisiana, United States', 12% from 'US', and 20% from 'Other'. * host_response_time: 61% of hosts respond 'within an hour', with 26% being null. * host_response_rate: 58% of hosts have a '100%' response rate, with 26% being null. * host_acceptance_rate: 28% of hosts have a '100%' acceptance rate, with 24% being null. * host_since dates range from 13 December 2008 to 20 October 2021.

Usage

This dataset is ideal for: * Predicting short-term rental charges in New Orleans based on location and amenities. * Describing the 'vibe' of each neighbourhood using listing descriptions, suitable for Natural Language Processing (NLP) tasks. * Identifying the most common amenities offered in short-term rental listings. * Determining factors that contribute to popular or highly-rated listings. * Analysing differences in favourability among different New Orleans neighbourhoods. * Exploratory Data Analysis (EDA) and Regression modelling. * Researching the impact of short-term rentals on housing affordability and community dynamics.

Coverage

The dataset focuses on New Orleans, Louisiana, United States. It covers a time range for host activity from 13 December 2008 to 20 October 2021, with the data compilation date being 7 November 2021. While not directly demographic, the context addresses concerns about gentrification and the displacement of longtime residents in the city.

License

CC-BY

Who Can Use It

• Data Scientists and Analysts: For data science projects, statistical analysis, machine learning model building, and deriving insights from listing and review data.
• Urban Planners and Policy Makers: To understand the spread of short-term rentals, their impact on local housing markets, and to inform regulations and zoning decisions.
• Researchers and Activists: Studying the socio-economic effects of tourism and short-term rentals on urban communities, particularly concerning housing and gentrification.
• Real Estate Professionals: To gain market intelligence on short-term rental trends, pricing, and amenities in New Orleans.
• Hospitality Industry Stakeholders: To analyse competition and market demand in the New Orleans accommodation sector.

Dataset Name Suggestions

• New Orleans Airbnb Listings and Reviews
• New Orleans Airbnb Host and Listing Data
• NOLA Airbnb Activity Dataset
• Inside Airbnb New Orleans
• New Orleans Short-Term Rental Analysis Data

Attributes

Original Data Source: New Orleans Airbnb Listings and Reviews

At Echo, our dedication to data curation is unmatched; we focus on providing our clients with an in-depth picture of a physical location based on activity in and around a point of interest over time. Our dataset empowers you to explore the “what” by allowing you to dig deeper into customer movement behaviors, eliminate gaps in your trade area and discover untapped potential. Leverage Echo's Activity datasets to identify new growth opportunities and gain a competitive advantage.

This sample of our Area Activity data provides you insights into the estimated total unique visitors and visits in an area. This helps you understand frequentation dynamics over time, identify emerging trends in people movements and measure the impact of external factors on how people move across a city.

Additional Information: - Understand the actual movement patterns of consumers without using PII data, gaining a 360-degree consumer view. Complement your online behavior knowledge with actual offline actions, and better attribute intent based on real-world behaviors. - Echo collects, cleans and updates its footfall on a daily basis. Normalization of the data occurs on a monthly basis. - We provide data aggregation on a weekly, monthly and quarterly basis. - Information about our country offering and data schema can be found here:

1) Data Schema: https://docs.echo-analytics.com/activity/data-schema
2) Country Availability: https://docs.echo-analytics.com/activity/country-coverage
3) Methodology: https://docs.echo-analytics.com/activity/methodology

Echo's commitment to customer service is evident in our exceptional data quality and dedicated team, providing 360° support throughout your location intelligence journey. We handle the complex tasks to deliver analysis-ready datasets to you.

Business Needs: 1. Site Selection: Leverage footfall data to identify the best location to open a new store. By analyzing areas with high footfall you can select sites that are likely to attract more customers. 2. Urban Planning Development: City planners can use footfall data to optimize the layout and infrastructure of urban areas, guide the development of commercial areas by indicating where pedestrian traffic is heaviest, and aid in traffic management and safety measures. 3. Real Estate Investment: Leverage footfall data to identify lucrative investment opportunities and optimize property management by analyzing pedestrian traffic patterns.

Data from the following digital consultation campaign: "Assises du Tourisme durable Paris 2021"

The consultation was open on idee.paris from May 20 to June 23, 2021.

Paris is one of the most visited cities in the world. Struck by the health crisis, the City of Paris presented a support plan in May 2020 for the most affected players (commerce, culture, tourism). The City was preparing the revival with the actors of the sector and wished to play a particular role in the invention of a more sustainable and local tourism, more eco-responsible, more resistant to crises, more respectful of its territory and its inhabitants, and thus becoming exemplary in the emergence of tourism with a positive impact in the light of the 2024 Olympic and Paralympic Games.

Through the questionnaire, the vision of Parisians provided food for thought and discussions with industry players. The sharing of practices and desires has helped the city to better shape the tourism of tomorrow.

Data from the following digital consultation campaign: “Assises du Tourisme durable Paris 2021”

The consultation was open on idee.paris from May 20 to June 23, 2021.

Paris is one of the most visited cities in the world. Hit by the health crisis, the City of Paris presented a support plan in May 2020 for those most affected (commerce, culture, tourism). The City was preparing the relaunch with players in the sector and wanted to play a particular role in the invention of more sustainable and local tourism, more eco-responsible, more resistant to crises, more respectful of its territory and its inhabitants, and thus becoming exemplary in the emergence of tourism with a positive impact in the light of the 2024 Olympic and Paralympic Games.

Through the questionnaire, the vision of Parisians helped to fuel the reflection and the debates held with stakeholders in the sector. Sharing practices and desires helped the city better shape the tourism of tomorrow.

(UNCLASSIFIED) Since the end of its 14-year civil war in 2003, Liberia has made significant progress in developing its tourism industry. The U.S. has been an instrumental partner in this regard, contributing as much as US $1 billion in bilateral assistance to the Liberian government for reconstruction purposes. Given the extent of structural and societal damage incurred during the war-era, Liberia’s most visited tourist attractions are now mostly ecological, including 350 miles of Atlantic beaches, the Sapo National Park (comprised of a sprawling tropical rainforest), and various rivers, islands, and mountains across the country. In late 2011, Liberia was granted full membership status by the United Nations World Tourism Organization, which guaranteed the country international assistance in policy drafting and development of its tourism industry. In late-2010, Delta Airlines responded to increased demand for air transport to the country by becoming the first American carrier to fly to Liberia in twenty years. In 2012, the Emerging Business Lab published a tourist map of Monrovia with directions to the city’s historic highlights, hotels, and restaurants. The map is now available online and has expanded since its first issue to include amenities such as cafes and Wi-Fi hotspots. Exact statistics on the impact of Ebola on Liberia’s tourism sector are unavailable. The U.S. Department of State issued a press release in August 2014 ordering the departure of family members of Embassy employees in Monrovia. Though the Embassy has retained its staff and additional personnel have been deployed to assist Liberian authorities, all other U.S. citizens are warned to defer any non-essential travel to the country. Given burgeoning travel restrictions and the ongoing inability of Liberian and international authorities to contain the virus, regression in Liberia’s tourism industry is likely.Attribute Table Field DescriptionsISO3 - International Organization for Standardization 3-digit country code ADM0_NAME - Administration level zero identification / name ADM1_NAME - Administration level one identification / name ADM2_NAME - Administration level two identification / name NAME - Name of tourist attraction TYPE - Classification in the geodatabase CITY - City location available SPA_ACC - Spatial accuracy of site location (1 – high, 2 – medium, 3 – low) COMMENTS - Comments or notes regarding the tourist attraction SOURCE_DT - Source one creation date SOURCE - Source one SOURCE2_DT - Source two creation date SOURCE2 - Source two CollectionThe feature class was generated utilizing data from OpenStreetMap, Wikimapia, GeoNames and other sources. OpenStreetMap is a free worldwide map, created by crowd-sourcing. Wikimapia is open-content mapping focused on gathering all geographical objects in the world. Consistent naming conventions for geographic locations were attempted but name variants may exist, which can include historical or less widespread interpretations.The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe is not responsible for the accuracy and completeness of data compiled from outside sources.Metadata information was collected primarily from travel blogs and news media articles.Sources (HGIS)DigitalGlobe, “DigitalGlobe Imagery Archive.” Accessed October 01, 2014. GeoNames, “Liberia.” September 23, 2014. Accessed October 01, 2014. http://www.geonames.org.Google, September 2014. Accessed October 01, 2014. www.google.com.OpenStreetMap, “Liberia.” September 2014. Accessed October 01, 2014. http://www.openstreetmap.org.Wikimapia, “Liberia.” September 2014. Accessed October 01, 2014. http://wikimapia.org.Sources (Metadata)“Country Report: Travel and Tourism in Liberia.” Euromonitor International. December 01, 2012. Accessed October 02, 2014. http://www.euromonitor.com.Hirsch, Afua. “Monrovia tourist guide taps into Liberian capital’s growing potential: New map aims to show off city more renowned for war and strife, pointing way to historic sites and cocktail bars.” The Guardian. October 17, 2012. Accessed October 02, 2014. http://www.theguardian.com.“Sector Profile: Liberia - Principle Economic Sectors of Liberia.” Focus: Africa. January 01, 2010. Accessed October 02, 2014. http://focusafrica.gov.in.“Travel security advisories – Flight bans and closures.” International SOS. October 01, 2014. Accessed October 02, 2014. https://www.internationalsos.com.“Travel and Tourism – Liberia.” World Travel Market. May 01, 2010. Accessed October 02, 2014. http://www.wtmlondon.com.

The shape of urban settlements plays a fundamental role in their sustainable planning. Properly defining the boundaries of cities is challenging and remains an open problem in the science of cities. Here, we propose a worldwide model to define urban settlements beyond their administrative boundaries through a bottom-up approach that takes into account geographical biases intrinsically associated with most societies around the world, and reflected in their different regional growing dynamics. The generality of the model allows one to study the scaling laws of cities at all geographical levels: countries, continents and the entire world. Our definition of cities is robust and holds to one of the most famous results in social sciences: Zipf's law. According to our results, the largest cities in the world are not in line with what was recently reported by the United Nations. For example, we find that the largest city in the world is an agglomeration of several small settlements close to each other, connecting three large settlements: Alexandria, Cairo and Luxor. Our definition of cities opens the doors to the study of the economy of cities in a systematic way independently of arbitrary definitions that employ administrative boundaries.

Smart City & Connected City Solutions Market Outlook

The global market size for Smart City & Connected City Solutions is poised to grow from $520 billion in 2023 to an impressive $1.2 trillion by 2032, exhibiting a robust CAGR of 9.5% over the forecast period. This substantial growth is driven by advancements in IoT technology, increased urbanization, and the rising demand for energy-efficient systems and infrastructure.

One of the primary growth factors for this market is the rapid urbanization across the globe. More than half of the world’s population now resides in urban areas, and this figure is expected to rise exponentially over the coming decades. As cities grow, the strain on infrastructure, energy resources, and governance systems increases, creating a necessity for smarter and more efficient solutions. The integration of IoT and AI technologies into urban planning and management is enabling cities to meet these demands by optimizing resource use, reducing waste, and improving the quality of life for residents.

Another significant driver is the rising governmental and private sector investment in smart city initiatives. Governments worldwide are recognizing the benefits of smart city solutions in terms of energy conservation, better traffic management, enhanced security, and improved public services. For example, the European Union has committed substantial funding for smart city projects under its Horizon 2020 initiative, focusing on sustainability and technological innovation. Similarly, various countries in Asia-Pacific, North America, and the Middle East are launching extensive smart city programs, backed by both public and private investments.

The proliferation of advanced technologies such as 5G, blockchain, and AI is also playing a crucial role in the market's growth. 5G technology, in particular, is set to revolutionize smart city infrastructure by providing faster, more reliable connectivity. This will enable the high-speed data transfer required for real-time applications in smart governance, smart healthcare, and smart mobility. Additionally, blockchain technology offers enhanced security and transparency for various smart city applications, including energy grids, public services, and transportation systems.

The regional outlook for the Smart City & Connected City Solutions market is highly promising, with Asia-Pacific and North America leading the charge. Asia-Pacific is expected to witness the highest growth rate due to the rapid urbanization in countries like China and India and substantial government initiatives focused on building smart cities. North America, with its advanced technological infrastructure and significant investments in smart city projects, is also poised for considerable growth.

Component Analysis

The Smart City & Connected City Solutions market can be segmented by components into hardware, software, and services. Each of these components plays a critical role in the development and implementation of smart city solutions. The hardware segment includes sensors, cameras, smart meters, and other connected devices that form the backbone of smart city infrastructure. These devices collect vast amounts of data, which is crucial for monitoring and managing various urban functions. The increasing adoption of IoT devices is driving the growth of this segment, as cities aim to become more efficient and responsive.

Software solutions are essential for analyzing the data collected by hardware components and transforming it into actionable insights. This segment covers a wide range of applications, including data analytics platforms, urban planning software, and smart governance solutions. The demand for such software is growing as cities seek to harness the power of big data and AI to improve decision-making processes. Cloud-based software solutions have become particularly popular due to their scalability, flexibility, and cost-effectiveness, contributing to the overall growth of the software segment.

Services are another vital component of the Smart City & Connected City Solutions market. These services include consulting, system integration, and maintenance services, which are crucial for the successful implementation and ongoing operation of smart city projects. The complexity of integrating various hardware and software components into a cohesive system necessitates specialized expertise. As a result, there is a growing market for service providers who can offer end-to-end solutions, from initial planning and design to implementation and continuous support.<

Geometry information for commercial POIs that includes the polygon of the POI and spatial hierarchy metadata defining whether the polygon is contained within another POI. Available for ~22M POI. SafeGraph helps organizations unlock innovation with the most accurate geospatial dataset on physical places. We provide anonymized and aggregated building footprints, and core information on millions of points-of-interest (POI) and thousands of brands in globally.

This layer presents the number of water sources (surface and non-surface) from which cities around the world harvest water. On average, cities retrieve water from 4 different sources. Note that if a city gets a small fraction of its water from surface water, there will be calculated values for this metric, but it is not particularly meaningful for a city's water risk or opportunity profile.For more information, access the Urban Water Blueprint report here: http://www.iwa-network.org/wp-content/uploads/2016/06/Urban-Water-Blueprint-Report.pdfYou can also visit the Urban Water Blueprint website here: http://water.nature.org/waterblueprint/#/intro=true

This layer highlights the authorized vehicle routes for the 2015 World Meeting of Families. The routes will be held for public safety vehicles, emergency operations, and other mission critical traffic. Regular traffic will not be permitted on the routes. Check for updates frequently as information is subject to change. For a more detailed description of the event and operations: http://www.phila.gov/informationcenters/pope/.

Trouble downloading or have questions about this City dataset? Visit the OpenDataPhilly Discussion Group

This feature class is part of the Cadastral National Spatial Data Infrastructure (NSDI) CADNSDI publication data set for rectangular and non-rectangular Public Land Survey System (PLSS) data set. The metadata description in the Cadastral Reference System Feature Data Set more fully describes the entire data set. These are the corners of the PLSS. This feature class contains summary information about the coordinate location and reliability of corner coordinate information. alternate names or aliases for corners are also inlcuded in this feature class.