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The thesis the data comes from analyses patterns of growth, decline, clustering and dispersal of live music in Sydney and Melbourne between the 1980s and 2000s. It demonstrates the use of historical Geographic Information Systems, combined with interviews, as a methodological approach for understanding the impacts of restructuring in cultural industries. It offers a practical example of applied social research with GIS.
The project developed a novel methodology combining GIS with interviews with music scene participants. A substantial part of the research project comprised the development of a historical geodatabase, leveraging the spatial and temporal data embedded in historical live music performance listings (‘gig listings’) sourced from archived publications in Sydney and Melbourne. This geodatabase ultimately incorporates over 20,000 live music listings and over 2500 geocoded venues.
The historical geodatabase was built incrementally to adapt to the format of the historical data. The structure maintains a one-to-one relationship to primary sources from different publications, allowing for quality checks, but can produce normalised outputs that allow live music venues, performances, and bands to be analysed separately. Outputs from the geodatabase have facilitated the quantitative analysis and geovisualisation of live music data over the study time frame in Sydney and Melbourne.
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These data sets were created as part of The Center for International Development’s ongoing research into the role of geography in economic development (see www.cid.harvard.edu/economic.htm). They have been created between 1998 and 1999.
The Geographic Management Information System (GeoMIS) is a FISMA Moderate minor application built using ArcGIS Server and portal, Microsoft SQL, and a web-facing front-end. The system can be accessed over the internet via https://www.usaidgiswbg.com using a web browser. GeoMIS is based on a commercial off-the-shelf product developed by Esri. Esri is creates geographic information system (GIS) software, web GIS and geodatabase management applications and is based in California. GeoMISIt is maintained by an Israeli company, Systematics (see Attachment 3) which is EsriI's agent in Israel. The mission has an annual maintenance contract with Systematics for GeoMIS. GeoMIS has 100 users from USAID staff (USA Direct Hire and Foreign Service Nationals) and 200 users from USAID contractors and grantees. The system is installed at USAID WBG office in Tel Aviv/Israel inside the computer room in the DMZ. It has no interconnections with any other system.
Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.
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How to cite
When you use the datasets or maps, please also cite to the following paper introducing the whole of process from data collection, harmonization and visualization until releasing the data:
Rantanen, T., Tolvanen, H., Roose, M., Ylikoski, J. & Vesakoski, O. (2022) “Best practices for spatial language data harmonization, sharing and map creation - A case study of Uralic” PLoS ONE 17(6): e0269648. https://doi.org/10.1371/journal.pone.0269648.
Overview
The Geographical database of the Uralic languages consists of past and current distributions of the Uralic languages both as the original digital spatial datasets and as finalized maps. The database has been collected by the interdisciplinary BEDLAN (Biological Evolution and Diversification of LANguages) research team in collaboration with experts of Uralic languages. The work has been financed by the University of Turku (UTU–BGG), Kone Foundation (UraLex, AikaSyyni), the Academy of Finland (URKO), UiT – The Arctic University of Norway and the University of Oulu, as well as the Finno-Ugrian Society. The data have been compiled for the purposes of doing spatial linguistic and multidisciplinary research, and to visually present the state-of-the-art knowledge of the Uralic languages and their dialects. Geographic distributions are visualized as vector data primarily by using polygon objects (speaker areas or language areas), and in some rare cases, by using points. Based on the language distributions, coordinates for the languages and their dialects (point locations) have also been defined.
https://borealisdata.ca/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.5683/SP3/VGIDRAhttps://borealisdata.ca/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.5683/SP3/VGIDRA
The aims of the Journal of Economic Geography are to redefine and reinvigorate the intersection between economics and geography, and to provide a world-class journal in the field. The journal is steered by a distinguished team of Editors and an Editorial Board, drawn equally from the two disciplines. It publishes original academic research and discussion of the highest scholarly standard in the field of 'economic geography' broadly defined. Submitted papers are refereed, and are evaluated on the basis of their creativity, quality of scholarship, and contribution to advancing understanding of the geographic nature of economic systems and global economic change.
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The global Geographic Information System (GIS) Software market size was valued at approximately USD 7.8 billion in 2023 and is projected to reach USD 15.6 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.3% during the forecast period. This impressive growth can be attributed to the increasing demand for efficient data management tools across various industries, which rely on spatial data for decision-making and strategic planning. The rapid advancements in technology, such as the integration of AI and IoT with GIS software, have further propelled the market, enabling organizations to harness the full potential of geographic data in innovative ways.
One of the primary growth drivers of the GIS Software market is the burgeoning need for urban planning and smart city initiatives worldwide. As urbanization trends escalate, cities are increasingly relying on GIS technology to manage resources more effectively, optimize transportation networks, and enhance public safety. The ability of GIS software to provide real-time data and spatial analysis is vital for city planners and administrators faced with the challenges of modern urban environments. Furthermore, the trend towards digital transformation in governmental organizations is boosting the adoption of GIS solutions, as they seek to improve operational efficiency and service delivery.
The agricultural sector is also experiencing significant transformations due to the integration of GIS software, which is another pivotal growth factor for the market. Precision agriculture, which involves the use of GIS technologies to monitor and manage farming practices, is enabling farmers to increase crop yields while reducing resource consumption. By leveraging spatial data, farmers can make informed decisions about planting, irrigation, and harvesting, ultimately leading to more sustainable agricultural practices. This trend is particularly prominent in regions where agriculture forms a substantial portion of the economy, encouraging the adoption of advanced GIS tools to maintain competitive advantage.
Another influential factor contributing to the growth of the GIS Software market is the increasing importance of environmental management and disaster response. GIS technology plays a crucial role in assessing environmental changes, managing natural resources, and planning responses to natural disasters. The ability to overlay various data sets onto geographic maps allows for better analysis and understanding of environmental phenomena, making GIS indispensable in tackling issues such as climate change and resource depletion. Moreover, governments and organizations are investing heavily in GIS tools that aid in disaster preparedness and response, ensuring timely and effective action during emergencies.
The evolution of GIS Mapping Software has been instrumental in transforming how spatial data is utilized across various sectors. These software solutions offer robust tools for visualizing, analyzing, and interpreting geographic data, enabling users to make informed decisions based on spatial insights. With the ability to integrate multiple data sources, GIS Mapping Software provides a comprehensive platform for conducting spatial analysis, which is crucial for applications ranging from urban planning to environmental management. As technology continues to advance, the capabilities of GIS Mapping Software are expanding, offering more sophisticated features such as 3D visualization and real-time data processing. These advancements are not only enhancing the utility of GIS tools but also making them more accessible to a wider range of users, thereby driving their adoption across different industries.
Regionally, North America and Europe have traditionally dominated the GIS Software market, thanks to their robust technological infrastructure and higher adoption rates of advanced technologies. However, Asia Pacific is expected to witness the highest growth rate during the forecast period, driven by rapid urbanization, increased government spending on infrastructure development, and the expanding telecommunications sector. The growing awareness and adoption of GIS solutions in countries like China and India are significant contributors to this regional growth. Furthermore, Latin America and the Middle East & Africa regions are slowly catching up, with ongoing investments in smart city projects and infrastructure development driving the demand for GIS software.
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The global Geographic Information System (GIS) tools market size was valued at approximately USD 10.8 billion in 2023, and it is projected to reach USD 21.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2032. The increasing demand for spatial data analytics and the rising adoption of GIS tools across various industries are significant growth factors propelling the market forward.
One of the primary growth factors for the GIS tools market is the surging demand for spatial data analytics. Spatial data plays a critical role in numerous sectors, including urban planning, environmental monitoring, disaster management, and natural resource exploration. The ability to visualize and analyze spatial data provides organizations with valuable insights, enabling them to make informed decisions. Advances in technology, such as the integration of artificial intelligence (AI) and machine learning (ML) with GIS, are enhancing the capabilities of these tools, further driving market growth.
Moreover, the increasing adoption of GIS tools in the construction and agriculture sectors is fueling market expansion. In construction, GIS tools are used for site selection, route planning, and resource management, enhancing operational efficiency and reducing costs. Similarly, in agriculture, GIS tools aid in precision farming, crop monitoring, and soil analysis, leading to improved crop yields and sustainable farming practices. The ability of GIS tools to provide real-time data and analytics is particularly beneficial in these industries, contributing to their widespread adoption.
The growing importance of location-based services (LBS) in various applications is another key driver for the GIS tools market. LBS are extensively used in navigation, logistics, and transportation, providing real-time location information and route optimization. The proliferation of smartphones and the development of advanced GPS technologies have significantly increased the demand for LBS, thereby boosting the GIS tools market. Additionally, the integration of GIS with other technologies, such as the Internet of Things (IoT) and Big Data, is creating new opportunities for market growth.
Regionally, North America holds a significant share of the GIS tools market, driven by the high adoption of advanced technologies and the presence of major market players. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, owing to increasing investments in infrastructure development, smart city projects, and the growing use of GIS tools in emerging economies such as China and India. Europe, Latin America, and the Middle East & Africa are also expected to contribute to market growth, driven by various government initiatives and increasing awareness of the benefits of GIS tools.
The GIS tools market can be segmented by component into software, hardware, and services. The software segment is anticipated to dominate the market due to the increasing demand for advanced GIS software solutions that offer enhanced data visualization, spatial analysis, and decision-making capabilities. GIS software encompasses a wide range of applications, including mapping, spatial data analysis, and geospatial data management, making it indispensable for various industries. The continuous development of user-friendly and feature-rich software solutions is expected to drive the growth of this segment.
Hardware components in the GIS tools market include devices such as GPS units, remote sensing devices, and plotting and digitizing tools. The hardware segment is also expected to witness substantial growth, driven by the increasing use of advanced hardware devices that provide accurate and real-time spatial data. The advancements in GPS technology and the development of sophisticated remote sensing devices are key factors contributing to the growth of the hardware segment. Additionally, the integration of hardware with IoT and AI technologies is enhancing the capabilities of GIS tools, further propelling market expansion.
The services segment includes consulting, integration, maintenance, and support services related to GIS tools. This segment is expected to grow significantly, driven by the increasing demand for specialized services that help organizations effectively implement and manage GIS solutions. Consulting services assist organizations in selecting the right GIS tools and optimizing their use, while integration services ensure seamless integr
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The Regional Crime Analysis GIS (RCAGIS) is an Environmental Systems Research Institute (ESRI) MapObjects-based system that was developed by the United States Department of Justice Criminal Division Geographic Information Systems (GIS) Staff, in conjunction with the Baltimore County Police Department and the Regional Crime Analysis System (RCAS) group, to facilitate the analysis of crime on a regional basis. The RCAGIS system was designed specifically to assist in the analysis of crime incident data across jurisdictional boundaries. Features of the system include: (1) three modes, each designed for a specific level of analysis (simple queries, crime analysis, or reports), (2) wizard-driven (guided) incident database queries, (3) graphical tools for the creation, saving, and printing of map layout files, (4) an interface with CrimeStat spatial statistics software developed by Ned Levine and Associates for advanced analysis tools such as hot spot surfaces and ellipses, (5) tools for graphically viewing and analyzing historical crime trends in specific areas, and (6) linkage tools for drawing connections between vehicle theft and recovery locations, incident locations and suspects' homes, and between attributes in any two loaded shapefiles. RCAGIS also supports digital imagery, such as orthophotos and other raster data sources, and geographic source data in multiple projections. RCAGIS can be configured to support multiple incident database backends and varying database schemas using a field mapping utility.
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Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.
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The global Geographic Information System (GIS) Analytics market size is projected to grow remarkably from $9.1 billion in 2023 to $21.7 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 10.2% during the forecast period. This substantial growth can be attributed to several factors such as technological advancements in GIS, increasing adoption in various industry verticals, and the rising importance of spatial data for decision-making processes.
The primary growth driver for the GIS Analytics market is the increasing need for accurate and efficient spatial data analysis to support critical decision-making processes across various industries. Governments and private sectors are investing heavily in GIS technology to enhance urban planning, disaster management, and resource allocation. With the world becoming more data-driven, the reliance on GIS for geospatial data has surged, further propelling its market growth. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) with GIS is revolutionizing the analytics capabilities, offering deeper insights and predictive analytics.
Another significant growth factor is the expanding application of GIS analytics in disaster management and emergency response. Natural disasters such as hurricanes, earthquakes, and wildfires have highlighted the importance of GIS in disaster preparedness, response, and recovery. The ability to analyze spatial data in real-time allows for quicker and more efficient allocation of resources, thus minimizing the impact of disasters. Moreover, GIS analytics plays a pivotal role in climate change studies, helping scientists and policymakers understand and mitigate the adverse effects of climate change.
The transportation sector is also a major contributor to the growth of the GIS Analytics market. With the rapid urbanization and increasing traffic congestion in cities, there is a growing demand for effective transport management solutions. GIS analytics helps in route optimization, traffic management, and infrastructure development, thereby enhancing the overall efficiency of transportation systems. The integration of GIS with Internet of Things (IoT) devices and sensors is further enhancing the capabilities of traffic management systems, contributing to the market growth.
Regionally, North America is the largest market for GIS analytics, driven by the high adoption rate of advanced technologies and significant investment in geospatial infrastructure by both public and private sectors. The Asia Pacific region is expected to witness the highest growth rate during the forecast period due to the rapid urbanization, infrastructural developments, and increasing government initiatives for smart city projects. Europe and Latin America are also contributing significantly to the market growth owing to the increasing use of GIS in urban planning and environmental monitoring.
The GIS Analytics market can be segmented by component into software, hardware, and services. The software segment holds the largest market share due to the continuous advancements in GIS software solutions that offer enhanced functionalities such as data visualization, spatial analysis, and predictive modeling. The increasing adoption of cloud-based GIS software solutions, which offer scalable and cost-effective options, is further driving the growth of this segment. Additionally, open-source GIS software is gaining popularity, providing more accessible and customizable options for users.
The hardware segment includes GIS data collection devices such as GPS units, remote sensing instruments, and other data acquisition tools. This segment is witnessing steady growth due to the increasing demand for high-precision GIS data collection equipment. Technological advancements in hardware, such as the development of LiDAR and drones for spatial data collection, are significantly enhancing the capabilities of GIS analytics. Additionally, the integration of mobile GIS devices is facilitating real-time data collection, contributing to the growth of the hardware segment.
The services segment encompasses consulting, implementation, training, and maintenance services. This segment is expected to grow at a significant pace due to the increasing demand for professional services to manage and optimize GIS systems. Organizations are seeking expert consultants to help them leverage GIS analytics for strategic decision-making and operational efficiency. Additionally, the growing complexity o
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Physical Points in the Geographic Names Information System (GNIS)This feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Geological Survey, displays physical points from the Geographic Names Information System (GNIS). Per USGS, “the Geographic Names Information System (GNIS) is the federal standard for geographic nomenclature. The U.S. Geological Survey developed the GNIS for the U.S. Board on Geographic Names, a Federal inter-agency body chartered by public law to maintain uniform feature name usage throughout the Government and to promulgate standard names to the public. The GNIS is the official repository of domestic geographic names data; the official vehicle for geographic names use by all departments of the Federal Government; and the source for applying geographic names to Federal electronic and printed products of all types.”Physical Points in the Western New York RegionData currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Physical Points) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 34 (Geographic Names Information System (GNIS) - USGS National Map Downloadable Data Collection)OGC API Features Link: (Physical Points in the Geographic Names Information System (GNIS) - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: U.S. Board on Geographic NamesFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Cultural Resources Theme Community. Per the Federal Geospatial Data Committee (FGDC), Cultural Resources are defined as "features and characteristics of a collection of places of significance in history, architecture, engineering, or society. Includes National Monuments and Icons."For other NGDA Content: Esri Federal Datasets
The U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration's (NOAA) National Marine Sanctuary Program, conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary region from 1993 to 2004. The mapped area is approximately 3,700 square km (1,100 square nm) in size and was subdivided into 18 quadrangles. Several series of sea floor maps of the region based on multibeam sonar surveys have been published. In addition, 2,628 seabed sediment samples were collected and analyzed and approximately 10,600 still photographs of the seabed were acquired during the project. These data provide the basis for scientists, policymakers, and managers for understanding the complex ecosystem of the sanctuary region and for monitoring and managing its economic and natural resources.
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Various Geospatial Data and Geographic Information Systems (GIS) presentations, workshops and tutorials. For the live versions of these files and material, please see uoft.me/GIS
This data collection uses a Geographic Information System (GIS) to organize and characterize information about benthic communities and substrates, which are ecological environments of the sea floor. The communities in this data collection include coral, seagrass, bare bottom, hard bottom, tidal flat, saltmarsh, and halophila communities. This coverage shows benthic distributions of various organisms for South Florida. The data provider included a metadata file in the FGDC description with the data files in this collection. Geographic Information System (GIS) software is required to fully utilize the contents of this accession.
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IntroductionGeographic Information Systems (GIS) and spatial analysis are emerging tools for global health, but it is unclear to what extent they have been applied to HIV research in Africa. To help inform researchers and program implementers, this scoping review documents the range and depth of published HIV-related GIS and spatial analysis research studies conducted in Africa.MethodsA systematic literature search for articles related to GIS and spatial analysis was conducted through PubMed, EMBASE, and Web of Science databases. Using pre-specified inclusion criteria, articles were screened and key data were abstracted. Grounded, inductive analysis was conducted to organize studies into meaningful thematic areas.Results and discussionThe search returned 773 unique articles, of which 65 were included in the final review. 15 different countries were represented. Over half of the included studies were published after 2014. Articles were categorized into the following non-mutually exclusive themes: (a) HIV geography, (b) HIV risk factors, and (c) HIV service implementation. Studies demonstrated a broad range of GIS and spatial analysis applications including characterizing geographic distribution of HIV, evaluating risk factors for HIV, and assessing and improving access to HIV care services.ConclusionsGIS and spatial analysis have been widely applied to HIV-related research in Africa. The current literature reveals a diversity of themes and methodologies and a relatively young, but rapidly growing, evidence base.
HCID is a global grid identification system offering users to refer the location and boundary of a grid cell, available at multiple spatial resolutions, using a single integer number. Instead of using the coordinates (latitude and longitude) of two corners of the grid cell bounding box (i.e., upper-left and lower-right), we assign each grid cell with a sequential integer number, or a grid cell ID, unique to each spatial resolution. This system was developed by HarvestChoice (http://harvestchoice.org) and is being widely used to facilitate analysis of spatial data layers, including the visualization, domain analysis, spatial aggregation/dis-aggregation, and general exchange of spatially-explicit data across disciplines - without needing to use a GIS software and spatial analysis skills. For the five arc-minute resolution of grids, we call the ID system as "CELL5M", whereas ones for 30 arc-second, 30-minute and 1 degree are called CELL30S, CELL30M and CELL1D, respectively. Assigning 0 starting at the upper-left corner (longitude: -180.0, latitude: 90.0) with a geographic projection, for example, CELL5M ranges up to 9,331,199 at the lower-right corner (longitude: 180.0, latitude: -90.0). The grid cell ID at a specific location can be easily computed mathematically, and this can be also easily converted to different resolutions.
The research project from which this dataset was produced was designed to help bridge the divide in understanding of the possible environmental causes of breast cancer in the United Kingdom. This divide exists between the official cancer research and treatment world, and other unofficial groups of diverse expertise. The geographic information system methodology used (Geographic Information Systems for Participation, or GIS-P) was intended to increase the understanding of the various positions in the debate both for the researchers, but also more importantly, between the communities of interest. The intention was to stimulate debate through the shared understanding that could be achieved by debating the knowledge and viewpoints expressed through the maps. In this respect, debate stimulation was more important than to capture detailed participatory derived spatial data (as has been the case with previous GIS-P projects). In practice, the process proved problematic, which explains the relatively limited quantity of GIS-P data collected.
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Understanding building metabolism is critical for guiding urban resource management and addressing challenges in urban sustainable development. Key attributes of buildings, including geolocation, footprint, height, and vintage, are crucial to characterizing spatiotemporal patterns of building metabolism. However, these attributes are usually challenging to obtain broadly and automatically, which obscures a comprehensive understanding and accurate assessment of urban metabolism. Moreover, the lack of a finer spatial pattern of these attributes shadows a spatially explicit characterization of material stock and flow in cities. In this study, we took Shenzhen—whose urbanization over the past three decades has been unprecedented in China and even around the world— has been taken as an example to develop a city-level building dataset based on a random-forest model and quantify the spatiotemporal patterns of material metabolism at relatively high spatial resolution (in 500 m × 500 m grids) by combing material flow analysis (MFA) with geographic information system (GIS). The results show that Shenzhen grew from a small town with 281.02 × 106 m3 of buildings in the 1990s to a mega-city with 3585.5 × 106 m3 of buildings in 2018 and expanded both outward and upward from downtown to suburban areas. The urban “weight” (material stock) increased from 92.69 Mt in the 1990s to 1667.8 Mt in 2018 and tended to be saturated, with an average growth rate of 9.5% per year. Spatially, the south-central areas were the largest container of material stocks and generated the most demolition waste. The spatially explicit maps of building three-dimensional (3-D) form and vintage provide detailed information for architectural conservation and could support the decision-making for urban renewal planning. The spatiotemporal patterns of in-use material stocks and potential generation of construction and demolition waste (CDW) provide a benchmark of environmental risk assessment and potential secondary resources to reduce “original” material consumption, which could help alter urban renewal to an environmental-friendly and sustainable trajectory.
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Satellite observations of night-time emitted lights describe a geography of the spatial distribution of resource use. Measurements of nocturnal lights enable the calculation of the total light emitted from each country of the world, and the light emitted per capita. We consider different groups of countries that share a land or maritime border and whose light per capita can be more equally/unequally distributed. A sharp difference in light per capita among neighboring countries reflects marked differences in economic welfare and in the extent of built environments. We demonstrate how this geography of nocturnal lights informs our understanding of the dynamics of conflict at the national and regional scale. We propose an index of regional disparity and test its ability to detect conflict dynamics by relating the index score with the occurrence and intensity of conflicts as classified by the Heidelberg Institute for International Conflict Research’s Conflict Barometer 2012 for the countries of the world. This method can be used to produce a global available temporal sampling of “cold spots” of disparity where conflicts are likely to occur. This will help foresee the identification and monitoring of regions of the world,which are becoming particularly unstable, assisting in the definition and execution of timely and proactive policies.
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The thesis the data comes from analyses patterns of growth, decline, clustering and dispersal of live music in Sydney and Melbourne between the 1980s and 2000s. It demonstrates the use of historical Geographic Information Systems, combined with interviews, as a methodological approach for understanding the impacts of restructuring in cultural industries. It offers a practical example of applied social research with GIS.
The project developed a novel methodology combining GIS with interviews with music scene participants. A substantial part of the research project comprised the development of a historical geodatabase, leveraging the spatial and temporal data embedded in historical live music performance listings (‘gig listings’) sourced from archived publications in Sydney and Melbourne. This geodatabase ultimately incorporates over 20,000 live music listings and over 2500 geocoded venues.
The historical geodatabase was built incrementally to adapt to the format of the historical data. The structure maintains a one-to-one relationship to primary sources from different publications, allowing for quality checks, but can produce normalised outputs that allow live music venues, performances, and bands to be analysed separately. Outputs from the geodatabase have facilitated the quantitative analysis and geovisualisation of live music data over the study time frame in Sydney and Melbourne.