Map in the form of a grid, where the density of economic activities of the municipality is represented. Activity data have been obtained from the IAE. The cell size is 100 meters. The data is provided in PDF and SHP.

This dataset presents the footprint of economic activity for Australia's capital cities. The data is aggregated to Statistical Area Level 2 (SA2) from the 2011 Australian Statistical Geography Standard (ASGS) and spans the year of 2014. This data has been created by the Grattan Institute for the Mapping Australia's Economy: Cities as Engines of Prosperity Report, Kelly, J-F., Donegan, P., Chisholm, C., & Oberklaid, M. published 20 July 2014. The report maps the Australian economy by the location of economic activity, defined as the dollar value of goods and services produced by workers within a particular area. It finds that economic activity is concentrated most heavily in the central business districts (CBDs) and inner areas of large cities. For more information including the data creation methodology, please refer to the Mapping Australia's Economy: Cities as Engines of Prosperity Report. Please note: AURIN has spatially enabled the original data using the ASGS 2011 SA2 Digital Boundaries.

Available data for gross domestic product (GDP) and population density are useful for defining divisions in socio-economic gradients across Europe, since economic power and human population pressure are recognised as two of the most critical factors causing ecosystem changes. To overcome both the limitations in data availability and in the distortions caused by using administrative regions, we decided to base the socio-economic dimension on an economic density indicator, defined as the income generated per square kilometre (EUR km-2), which can be mapped at a 1km2 spatial resolution. Economic density forms an integrative indicator that is based on two key drivers that were identified above: economic power and human population pressure. The indicator, which has been used to rank countries by their level of development, can be considered a crude measure for impacts on the environment caused by economic activity. An economic density map (EUR km-2) at 1 km2 spatial resolution was constructed by multiplying economic power (EUR person-1) with population density (person km-2). Subsequent logarithmic divisions resulted in an aggregated map of four economic density zones. Although the map has a fine spatial resolution it has to be realised that they form a spatial disaggregation of coarser census statistics. Importantly, the finer resolution discerns regional gradients in human activity that are required for many environmental studies, whilst broad gradients in economic activity is also treated consistently across Europe. GDP and population density data used were for the year 2001. The dataset consists of GeoTiff files of the economic density map and the four economic density zones.

This map is part of SDGs Today. Please see sdgstoday.orgGross Domestic Product (GDP) is one of the most commonly used measures for tracking national accounts and economic activity. Tracking growth over time can provide insights into the growth or decline of a nation’s economic activities following global/national events, policy changes, and other large-scale phenomena.The OECD's quarterly national accounts (QNA) dataset presents GDP growth data collected from all the OECD member countries and some other major economies on the basis of a standardised questionnaire. It contains a wide selection of generally seasonally adjusted quarterly series most widely used for economic analysis from 1960 or whenever available. These indicators include measures such as GDP expenditure/output and industry-based employment rates. All available OECD QNA measurements are made available to the public here.For more information, contact STAT.Contact@oecd.org.

This map shows the use of space in the potentially affected area of ​​a flood due to intense precipitation with a low probability, medium probability and high probability in future climate (with climate projection 2050). A more detailed Flemish land use map based on the Biological Valuation Map is used for this purpose.

This dataset contains Saudi Arabia Operating Expenditures by Establishment Size and Economic Activity for 2005-2017. Data From the Annual Economic Establishment Survey by General Authority for Statistics ,Follow datasource.kapsarc.org for timely data to advance energy economics research.Data from the Annual Economic Establishment Survey.Does not include establishments operating in the governmental and external sectors. Includes establishments operating in the private and public sector and non-profit.

Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures.

This dataset features a detailed map of material stocks for the whole of Austria on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors.

Temporal extent The map is representative for ca. 2018.

Data format Per federal state, the data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (.tif). There is a mosaic in GDAL Virtual format (.vrt), which can readily be opened in most Geographic Information Systems.

The dataset features

area and mass for different street types

area and mass for different rail types

area and mass for other infrastructure

area, volume and mass for different building types

Masses are reported as total values, and per material category.

Units

area in m²

height in m

volume in m³

mass in t for infrastructure and buildings

Further information For further information, please see the publication or contact Helmut Haberl (helmut.haberl@boku.ac.at). A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.

Publication Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G. , Fishman, T., Lanau, M., Gattringer, A., Kemper, T., Liu, G., Tanikawa, H., van der Linden, S., Hostert, P. (accepted): High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany. Environmental Science & Technology

Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). ML and GL acknowledge funding by the Independent Research Fund Denmark (CityWeight, 6111-00555B), ML thanks the Engineering and Physical Sciences Research Council (EPSRC; project Multi-Scale, Circular Economic Potential of Non-Residential Building Scale, EP/S029273/1), JL acknowledges funding by the Vienna Science and Technology Fund (WWTF), project ESR17-067, TF acknowledges the Israel Science Foundation grant no. 2706/19.

This map shows the use of space in the potentially affected area of ​​a flood from watercourses with a low probability, medium probability and high probability in the current climate. A more detailed Flemish land use map based on the Biological Valuation Map is used for this purpose.

This map shows the use of space in the potentially affected area of ​​a flood from the sea with a low probability, medium probability and high probability in the current climate. A more detailed Flemish land use map based on the Biological Valuation Map is used for this purpose.

포털 유럽연합 데이터 Map Viewing Service (WMS) of the dataset: Built sectors dedicated to economic activity in 2010 on Les Deux-Sèvres

The Gross Domestic Product per capita (gross domestic product divided by mid-year population converted to international dollars, using purchasing power parity rates) has been identified as an important determinant of susceptibility and vulnerability by different authors and used in the Disaster Risk Index 2004 (Peduzzi et al. 2009, Schneiderbauer 2007, UNDP 2004) and is commonly used as an indicator for a country's economic development (e.g. Human Development Index). Despite some criticisms (Brooks et al. 2005) it is still considered useful to estimate a population's susceptibility to harm, as limited monetary resources are seen as an important factor of vulnerability. However, collection of data on economic variables, especially sub-national income levels, is problematic, due to various shortcomings in the data collection process. Additionally, the informal economy is often excluded from official statistics. Night time lights satellite imagery of NOAA grid provides an alternative means for measuring economic activity. NOAA scientists developed a model for creating a world map of estimated total (formal plus informal) economic activity. Regression models were developed to calibrate the sum of lights to official measures of economic activity at the sub-national level for some target Country and at the national level for other countries of the world, and subsequently regression coefficients were derived. Multiplying the regression coefficients with the sum of lights provided estimates of total economic activity, which were spatially distributed to generate a 30 arc-second map of total economic activity (see Ghosh, T., Powell, R., Elvidge, C. D., Baugh, K. E., Sutton, P. C., & Anderson, S. (2010).Shedding light on the global distribution of economic activity. The Open Geography Journal (3), 148-161). We adjusted the GDP to the total national GDPppp amount as recorded by IMF (International Monetary Fund) for 2010 and we divided it by the population layer from Worldpop Project. Further, we ran a focal statistics analysis to determine mean values within 10 cell (5 arc-minute, about 10 Km) of each grid cell. This had a smoothing effect and represents some of the extended influence of intense economic activity for local people. Finally we apply a mask to remove the area with population below 1 people per square Km.

This dataset has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 4 (WP4). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

Data publication: 2014-06-01

Supplemental Information:

ClimAfrica was an international project funded by European Commission under the 7th Framework Programme (FP7) for the period 2010-2014. The ClimAfrica consortium was formed by 18 institutions, 9 from Europe, 8 from Africa, and the Food and Agriculture Organization of United Nations (FAO).

ClimAfrica was conceived to respond to the urgent international need for the most appropriate and up-to-date tools and methodologies to better understand and predict climate change, assess its impact on African ecosystems and population, and develop the correct adaptation strategies. Africa is probably the most vulnerable continent to climate change and climate variability and shows diverse range of agro-ecological and geographical features. Thus the impacts of climate change can be very high and can greatly differ across the continent, and even within countries.

The project focused on the following specific objectives:

1. Develop improved climate predictions on seasonal to decadal climatic scales, especially relevant to SSA;

2. Assess climate impacts in key sectors of SSA livelihood and economy, especially water resources and agriculture;

3. Evaluate the vulnerability of ecosystems and civil population to inter-annual variations and longer trends (10 years) in climate;

4. Suggest and analyse new suited adaptation strategies, focused on local needs;

5. Develop a new concept of 10 years monitoring and forecasting warning system, useful for food security, risk management and civil protection in SSA;

6. Analyse the economic impacts of climate change on agriculture and water resources in SSA and the cost-effectiveness of potential adaptation measures.

The work of ClimAfrica project was broken down into the following work packages (WPs) closely connected. All the activities described in WP1, WP2, WP3, WP4, WP5 consider the domain of the entire South Sahara Africa region. Only WP6 has a country specific (watershed) spatial scale where models validation and detailed processes analysis are carried out.

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Selvaraju Ramasamy

Resource constraints:

copyright

Online resources:

GDP per capita

Project deliverable D4.1 - Scenarios of major production systems in Africa

Climafrica Website - Climate Change Predictions In Sub-Saharan Africa: Impacts And Adaptations

Type of economic activity of the flood hazard map (HWGK) for floods with medium probability, as of December 1st, 2019.

Area defined by Article R2224-10 of the General Code of Local and Regional Authorities (transposition of the European Directive of 21 May 1991). An agglomeration is an area in which the population or economic activities are sufficiently concentrated so that domestic waste water can be collected and transported to a single sewage treatment system. Areas served by a collection network connected to a single sewage treatment system and those in which such a system has been set up by a decision of the competent authority shall be considered to be included in the same agglomeration. The map of the agglomeration is stopped by the prefect. Agglomerations are codified by a SANDRE code. Area defined by Article R2224-10 of the General Code of Local and Regional Authorities (transposition of the European Directive of 21 May 1991). An agglomeration is an area in which the population or economic activities are sufficiently concentrated so that domestic waste water can be collected and transported to a single sewage treatment system. Areas served by a collection network connected to a single sewage treatment system and those in which such a system has been set up by a decision of the competent authority shall be considered to be included in the same agglomeration. The map of the agglomeration is stopped by the prefect. Agglomerations are codified by a SANDRE code.

Diese Karte zeigt die Raumnutzung im potenziell betroffenen Gebiet einer Meeresflut mit geringer Wahrscheinlichkeit, mittlerer Wahrscheinlichkeit und hoher Wahrscheinlichkeit im zukünftigen Klima (mit Klimaprojektion 2050). Zu diesem Zweck wird eine detailliertere flämische Landnutzungskarte auf der Grundlage der biologischen Bewertungskarte verwendet.

The Quart Business Map is a set of cartographic data that, through a map, shows with points the location of each commercial establishment and equipment within the urban nucleus of Quart. The points are divided into four types: municipal facilities and services, economic activities and services, shops and restaurants.

This dataset consists of a series of maps of the EU in TIFF format with the demand of the main groups of energy products from each category of economic activity, according to the energy balances for 2019 and the 1x1 km reference grid from EUROSTAT. The energy demand is expressed in tonnes of oil equivalent (toe). The dataset also includes for each TIFF map the corresponding OVR and XML files that might be needed by some users. Each map is named as "product_activity_demand_2019.tif". The groups of energy products considered are: solid (solid fossil fuels), oil (oil and petroleum products), gas (natural gas), others (manufactured gases, oil shale, and peat and peat products), renewables (renewables and biofuels), nuclear (nuclear heat), heat, and electricity. The economic activities are: tri (transformation inputs), neu (non-energy use), ind (industry), tra (transport), and oth (other sectors: commercial and public services, households, agriculture and fishing).

Map Drawing Services Market Outlook

The global map drawing services market size was valued at approximately $1.2 billion in 2023 and is projected to reach $2.3 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.1% during the forecast period. This growth can be attributed to the increasing demand for precise and customized mapping solutions across various industries such as urban planning, environmental management, and tourism.

One of the primary growth factors of the map drawing services market is the rapid advancement in Geographic Information Systems (GIS) technology. The integration of advanced GIS tools allows for the creation of highly accurate and detailed maps, which are essential for urban planning and environmental management. Additionally, the growing emphasis on smart city initiatives worldwide has led to an increased need for customized mapping solutions to manage urban development and infrastructure efficiently. These technological advancements are not only improving the quality of map drawing services but are also making them more accessible to a broader range of end-users.

Another significant growth factor is the rising awareness and adoption of map drawing services in the tourism sector. Customized maps are increasingly being used to enhance the tourist experience by providing detailed information about destinations, routes, and points of interest. This trend is particularly prominent in regions with rich cultural and historical heritage, where detailed thematic maps can offer tourists a more immersive and informative experience. Furthermore, the digitalization of the tourism industry has made it easier to integrate these maps into various applications, further driving the demand for map drawing services.

Environmental management is another key area driving the growth of the map drawing services market. With the increasing focus on sustainable development and environmental conservation, there is a growing need for accurate maps to monitor natural resources, track changes in land use, and plan conservation efforts. Map drawing services provide essential tools for environmental scientists and policymakers to analyze and visualize data, aiding in better decision-making and management of natural resources. The rising environmental concerns globally are expected to continue driving the demand for these services.

From a regional perspective, North America is anticipated to hold a significant share of the map drawing services market due to the high adoption rate of advanced mapping technologies and the presence of major market players in the region. Furthermore, the region's focus on smart city projects and environmental conservation initiatives is expected to fuel the demand for map drawing services. Meanwhile, the Asia Pacific region is projected to witness the highest growth rate, driven by rapid urbanization, industrialization, and the growing need for efficient infrastructure planning and management.

Service Type Analysis

The map drawing services market is segmented into several service types, including custom map drawing, thematic map drawing, topographic map drawing, and others. Custom map drawing services cater to specific client needs, offering tailored mapping solutions for various applications. This segment is expected to witness significant growth due to the increasing demand for personalized maps in sectors such as urban planning, tourism, and corporate services. Businesses and government agencies are increasingly relying on custom maps to support their operations, leading to the expansion of this segment.

Thematic map drawing services focus on creating maps that highlight specific themes or topics, such as population density, climate patterns, or economic activities. These maps are particularly useful for educational purposes, research, and community planning. The growing emphasis on data-driven decision-making and the need for visual representation of complex datasets are driving the demand for thematic maps. Additionally, thematic maps play a crucial role in public health, disaster management, and policy formulation, contributing to the segment's growth.

Topographic map drawing services offer detailed representations of physical features of a landscape, including elevation, terrain, and landforms. These maps are essential for various applications, such as environmental management, military ope

- This dataset provides global sector-specific GDP distribution maps (in GeoTIFF format) with a 30-second spatial resolution. It allocates GDP at the 30-arcsecond grid level for three sectors (services, industry, and agriculture) by the distribution of country-level GDP data using high-resolution land cover map.
- The source GDP data for allocation is based on nominal GDP for the years 2010, 2015, and 2020, obtained from the World Bank. As the high-resolution land cover map, it uses the built-up area and non-residential area data by the Global Human Settlement Layer (Pesaresi and Politis, 2022) for the service and industrial sectors and the Global cropland map by Potapov et al. (2022) for the agriculture sector. Detailed descriptions of the data creation methodology can be found in Shoji et al. (In Review).
- Each pixel represents the monetary value of added value generated by economic activity hypothetically occurring within that pixel. The unit of each pixel value is in millions of USD (current prices for 2010, 2015, and 2020).

(Updated to v2.0 on July 1, 2025)

This update includes a major change to the spatial allocation method for service and agricultural GDP. For details on the new GDP mapping methodology, please refer to Shoji et al. (In Review). There are no changes to the industrial GDP map.

Reference:
- Pesaresi M, Politis P.: GHS-BUILT-S R2022A: GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975–2030). European Commission, Joint Research Centre (JRC), 2022.
- Potapov P, Svetlana T, Matthew CH, Alexandra T, Viviana Z, Ahmad K, Xiao-Peng S, Amy P, Quan S, Jocelyn C.: Global maps of cropland extent and change show accelerated cropland expansion in the twenty-first century. Nature Food 3: 19–28, 2022.
- Shoji T, Kajiyama K, Yamazaki D, Kita Y, Watanabe M.: Global spatially-distributed sectoral GDP map for disaster risk analysis. In Review.

Special Service Areas (SSA) boundaries in Chicago. The Special Service Area program is a mechanism used to fund expanded services and programs through a localized property tax levy within contiguous industrial, commercial and residential areas. The enhanced services and programs are in addition to services and programs currently provided through the city. SSA-funded projects could include, but are not limited to, security services, area marketing and advertising assistance, promotional activities such as parades and festivals, or any variety of small scale capital improvements that could be supported through a modest property tax levy. 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).

Business activities of Castellar del Vallès is a set of cartographic files that represent spatial information related to the companies, industries and establishments of the city through a geoportal that uses Google Maps and ICGC maps as base maps. We find the different economic activities of the municipality located with points. For each point, the information corresponding to the economic activity is displayed interactively.