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.

This Africa Geocoding locator is a view of the World Geocoding Service constrained to search for places in the countries of Africa. The World Geocoding Service finds addresses and places in all supported countries around the world in a single geocoding service. The service can find point locations of addresses, cities, landmarks, business names, and other places. The output points can be visualized on a map, inserted as stops for a route, or loaded as input for a spatial analysis.The service is available as both a geosearch and geocoding service:Geosearch Services – The primary purpose of geosearch services is to locate a feature or point of interest and then have the map zoom to that location. The result might be displayed on the map, but the result is not stored in any way for later use. Requests of this type do not require a subscription or a credit fee. Geocoding Services – The primary purpose of geocoding services is to convert an address to an x,y coordinate and append the result to an existing record in a database. Mapping is not always involved, but placing the results on a map may be part of a workflow. Batch geocoding falls into this category. Geocoding requires a subscription. An ArcGIS Online subscription will provide you access to the World Geocoding service for batch geocoding.The service can be used to find address and places for many countries around the world. For detailed information on this service, including a data coverage map, visit the World Geocoding service documentation.

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.

The Urban Place GIS Coverage of Mexico is a vector based point Geographic Information System (GIS) coverage of 696 urban places in Mexico. Each Urban Place is geographically referenced down to one tenth of a minute. The attribute data include time-series population and selected census/geographic data items for Mexican urban places from from 1921 to 1990. The cartographic data include urban place point locations on a state boundary file of Mexico. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the Instituto Nacional de Estadistica Geografia e Informatica (INEGI) and the Environmental Research Institute (ERI) of Michigan.

Dataset for the textbook Computational Methods and GIS Applications in Social Science (3rd Edition), 2023 Fahui Wang, Lingbo Liu Main Book Citation: Wang, F., & Liu, L. (2023). Computational Methods and GIS Applications in Social Science (3rd ed.). CRC Press. https://doi.org/10.1201/9781003292302 KNIME Lab Manual Citation: Liu, L., & Wang, F. (2023). Computational Methods and GIS Applications in Social Science - Lab Manual. CRC Press. https://doi.org/10.1201/9781003304357 KNIME Hub Dataset and Workflow for Computational Methods and GIS Applications in Social Science-Lab Manual Update Log If Python package not found in Package Management, use ArcGIS Pro's Python Command Prompt to install them, e.g., conda install -c conda-forge python-igraph leidenalg NetworkCommDetPro in CMGIS-V3-Tools was updated on July 10,2024 Add spatial adjacency table into Florida on June 29,2024 The dataset and tool for ABM Crime Simulation were updated on August 3, 2023, The toolkits in CMGIS-V3-Tools was updated on August 3rd,2023. Report Issues on GitHub https://github.com/UrbanGISer/Computational-Methods-and-GIS-Applications-in-Social-Science Following the website of Fahui Wang : http://faculty.lsu.edu/fahui Contents Chapter 1. Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools Case Study 1: Mapping and Analyzing Population Density Pattern in Baton Rouge, Louisiana Chapter 2. Measuring Distance and Travel Time and Analyzing Distance Decay Behavior Case Study 2A: Estimating Drive Time and Transit Time in Baton Rouge, Louisiana Case Study 2B: Analyzing Distance Decay Behavior for Hospitalization in Florida Chapter 3. Spatial Smoothing and Spatial Interpolation Case Study 3A: Mapping Place Names in Guangxi, China Case Study 3B: Area-Based Interpolations of Population in Baton Rouge, Louisiana Case Study 3C: Detecting Spatiotemporal Crime Hotspots in Baton Rouge, Louisiana Chapter 4. Delineating Functional Regions and Applications in Health Geography Case Study 4A: Defining Service Areas of Acute Hospitals in Baton Rouge, Louisiana Case Study 4B: Automated Delineation of Hospital Service Areas in Florida Chapter 5. GIS-Based Measures of Spatial Accessibility and Application in Examining Healthcare Disparity Case Study 5: Measuring Accessibility of Primary Care Physicians in Baton Rouge Chapter 6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns Case Study 6: Analyzing Population Density Patterns in Chicago Urban Area >Chapter 7. Principal Components, Factor and Cluster Analyses and Application in Social Area Analysis Case Study 7: Social Area Analysis in Beijing Chapter 8. Spatial Statistics and Applications in Cultural and Crime Geography Case Study 8A: Spatial Distribution and Clusters of Place Names in Yunnan, China Case Study 8B: Detecting Colocation Between Crime Incidents and Facilities Case Study 8C: Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago Chapter 9. Regionalization Methods and Application in Analysis of Cancer Data Case Study 9: Constructing Geographical Areas for Mapping Cancer Rates in Louisiana Chapter 10. System of Linear Equations and Application of Garin-Lowry in Simulating Urban Population and Employment Patterns Case Study 10: Simulating Population and Service Employment Distributions in a Hypothetical City Chapter 11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers Case Study 11A: Measuring Wasteful Commuting in Columbus, Ohio Case Study 11B: Location-Allocation Analysis of Hospitals in Rural China Chapter 12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations Case Study 12A. Examining Zonal Effect on Urban Population Density Functions in Chicago by Monte Carlo Simulation Case Study 12B: Monte Carlo-Based Traffic Simulation in Baton Rouge, Louisiana Chapter 13. Agent-Based Model and Application in Crime Simulation Case Study 13: Agent-Based Crime Simulation in Baton Rouge, Louisiana Chapter 14. Spatiotemporal Big Data Analytics and Application in Urban Studies Case Study 14A: Exploring Taxi Trajectory in ArcGIS Case Study 14B: Identifying High Traffic Corridors and Destinations in Shanghai Dataset File Structure 1 BatonRouge Census.gdb BR.gdb 2A BatonRouge BR_Road.gdb Hosp_Address.csv TransitNetworkTemplate.xml BR_GTFS Google API Pro.tbx 2B Florida FL_HSA.gdb R_ArcGIS_Tools.tbx (RegressionR) 3A China_GX GX.gdb 3B BatonRouge BR.gdb 3C BatonRouge BRcrime R_ArcGIS_Tools.tbx (STKDE) 4A BatonRouge BRRoad.gdb 4B Florida FL_HSA.gdb HSA Delineation Pro.tbx Huff Model Pro.tbx FLplgnAdjAppend.csv 5 BRMSA BRMSA.gdb Accessibility Pro.tbx 6 Chicago ChiUrArea.gdb R_ArcGIS_Tools.tbx (RegressionR) 7 Beijing BJSA.gdb bjattr.csv R_ArcGIS_Tools.tbx (PCAandFA, BasicClustering) 8A Yunnan YN.gdb R_ArcGIS_Tools.tbx (SaTScanR) 8B Jiangsu JS.gdb 8C Chicago ChiCity.gdb cityattr.csv ...

This web map references the live tiled map service from the OpenStreetMap (OSM) project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: https://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in ESRI products under a Creative Commons Attribution-ShareAlike license. Tip: This service is one of the basemaps used in the ArcGIS.com map viewer. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10. Tip: Here are some well known locations as they appear in this web map, accessed by launching the web map with a URL that contains location parameters: Athens, Cairo, Jakarta, Moscow, Mumbai, Nairobi, Paris, Rio De Janeiro, Shanghai

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.

Web-based GIS mapping application.Contains all available GIS and mapping resources for Cuyahoga County.Use the application to explore data using the available search, identify, and query tools; markup the map with the drawing tools; export the map to a geo-referenced image file; print the map to PDF with a custom title and include a legend and scale.View the 'Help Guide' for FAQs, tool tips, and additional information about the application and the data.

Includes: IDOT, NAIP, NAPP data and IL geography shapefiles ISGS data from Don

This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

Abstract : The search for the most appropriate GIS data model to integrate, manipulate and analyse spatio-temporal data raises several research questions about the conceptualisation of geographic spaces. Although there is now a general consensus that many environmental phenomena require field and object conceptualisations to provide a comprehensive GIS representation, there is still a need for better integration of these dual representations of space within a formal spatio-temporal database. The research presented in this paper introduces a hybrid and formal dual data model for the representation of spatio-temporal data. The whole approach has been fully implemented in PostgreSQL and its spatial extension PostGIS, where the SQL language is extended by a series of data type constructions and manipulation functions to support hybrid queries. The potential of the approach is illustrated by an application to underwater geomorphological dynamics oriented towards the monitoring of the evolution of seabed changes. A series of performance and scalability experiments are also reported to demonstrate the computational performance of the model.Data Description : The data set used in our research is a set of bathymetric surveys recorded over three years from 2009 to 2011 as Digital Terrain Models (DTM) with 2m grid spacing. The first survey was carried out in February 2009 by the French hydrographic office, the second one was recorded on August-September 2010 and the third in July 2011, both by the “Institut Universitaire Européen de la Mer”.

GapMaps Live is an easy-to-use location intelligence platform available across 25 countries globally that allows you to visualise your own store data, combined with the latest demographic, economic and population movement intel right down to the micro level so you can make faster, smarter and surer decisions when planning your network growth strategy.

With one single login, you can access the latest estimates on resident and worker populations, census metrics (eg. age, income, ethnicity), consuming class, retail spend insights and point-of-interest data across a range of categories including fast food, cafe, fitness, supermarket/grocery and more.

Some of the world's biggest brands including McDonalds, Subway, Burger King, Anytime Fitness and Dominos use GapMaps Live as a vital strategic tool where business success relies on up-to-date, easy to understand, location intel that can power business case validation and drive rapid decision making.

Primary Use Cases for GapMaps Live includes:

1. Retail Site Selection - Identify optimal locations for future expansion and benchmark performance across existing locations.
2. Customer Profiling: get a detailed understanding of the demographic profile of your customers and where to find more of them.
3. Analyse your catchment areas at a granular grid levels using all the key metrics
4. Target Marketing: Develop effective marketing strategies to acquire more customers.
5. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)
6. Customer Profiling
7. Target Marketing
8. Market Share Analysis

Some of features our clients love about GapMaps Live include: - View business locations, competitor locations, demographic, economic and social data around your business or selected location - Understand consumer visitation patterns (“where from” and “where to”), frequency of visits, dwell time of visits, profiles of consumers and much more. - Save searched locations and drop pins - Turn on/off all location listings by category - View and filter data by metadata tags, for example hours of operation, contact details, services provided - Combine public data in GapMaps with views of private data Layers - View data in layers to understand impact of different data Sources - Share maps with teams - Generate demographic reports and comparative analyses on different locations based on drive time, walk time or radius. - Access multiple countries and brands with a single logon - Access multiple brands under a parent login - Capture field data such as photos, notes and documents using GapMaps Connect and integrate with GapMaps Live to get detailed insights on existing and proposed store locations.

Users can browse the map interactively or search by lot ID or address. Available basemaps include aerial images, topographic contours, roads, town landmarks, conserved lands, and individual property boundaries. Overlays display landuse, zoning, flood, water resources, and soil characteristics in relation to neighborhoods or parcels. Integration with Google Street View offers enhanced views of the 2D map location. Other functionality includes map markup, printing, viewing the property record card, and links to official tax maps where available.NRPC's implementation of MapGeo dates back to 2013, however it is the decades of foundational GIS data development at NRPC and partner agencies that has enabled its success. NRPC refreshes the assessing data yearly; the map data is maintained in an ongoing manner.

The GIS of Mexican States, Municipalities and Islands consists of attribute and boundary data for 1990. The attribute data include population, language, education, literacy, housing Units and land cover classification from the 1990 Mexican population and housing census. The boundary data associated with the United States-Mexico border are consistent with the U.S. Census Bureau TIGER95 data. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

This is a GIS file set of the Gede ruins. The data was generated from laser scans, photogrammetric techniques and GPS data. The data maps the site of the Gede ruins in Kilifi County in Kenya. All data is in either the unprojected Geographic (GCS WGS84) or the projected Universal Transverse Mercator 37 South (UTM37S WGS84) coordinate system.The data is packaged as an ESRI Map Package (.mpk). If you are not an ESRI user and wish to unpack the package please rename the file extension to .zip and use a programme, such as 7-Zip, to unpack the package. The package contains shapefiles and images which are compatible with most GIS software. The ruins of Gede (also Gedi), a traditional Arab-African Swahili town, are located just off Kenya’s coastline, some 90km north of Mombasa. Gede was a small town built entirely from stones and rocks, and most of the original foundations are still visible today. Remaining structures at the site include coral stone buildings, mosques, houses and a palace. The town was abandoned in the early 17th century, and Gede’s buildings date back to the 15th century, although it is believed that the site could have been inhabited as early as the 11th or 12th century. The Zamani Project spatially documented the Gede ruins in 2010. In addition to the three principal structures of the Great Mosque, the Small Mosque and the Palace, remains of other structures in the immediate vicinity were also documented.The Zamani Project seeks to increase awareness and knowledge of tangible cultural heritage in Africa and internationally by creating metrically accurate digital representations of historical sites. Digital spatial data of cultural heritage sites can be used for research and education, for restoration and conservation and as a record for future generations. The Zamani Project operates as a non-profit organisation within the University of Cape Town.This text has been adapted from the UNESCO website (https://whc.unesco.org/en/tentativelists/5501/).The Zamani Project received funding from the Andrew W Mellon Foundation at the time of the project.

Basic raster layers from the MCM-LTER spatial data holdings have been exported and symbolized. The dataset files offered here include: 30m DEM made from USGS Topo map SPOT Satellite Image 39-558 LANDSAT 7 Satellite Image Note - the SPOT and LANDSAT layers are not MCM-LTER data products.  These resources were updated last in 2007, for more up-to-date layers, and potentially, higher resolution layers, please visit the Polar Geospatial Center and other affine geospatial data clearinghouses.Â

The ArcGIS World Geocoding Service finds addresses and places in all supported countries around the world in a single geocoding service. The service can find point locations of addresses, cities, landmarks, business names, and other places. The output points can be visualized on a map, inserted as stops for a route, or loaded as input for a spatial analysis.The service is available as both a geosearch and geocoding service:Geosearch Services – The primary purpose of geosearch services is to locate a feature or point of interest and then have the map zoom to that location. The result might be displayed on the map, but the result is not stored in any way for later use. Requests of this type do not require a subscription or a credit fee. Geocoding Services – The primary purpose of geocoding services is to convert an address to an x,y coordinate and append the result to an existing record in a database. Mapping is not always involved, but placing the results on a map may be part of a workflow. Batch geocoding falls into this category. Geocoding requires a subscription. An ArcGIS Online Subscription, or ArcGIS Location Platform Subscription, will provide you access to the ArcGIS World Geocoding service for batch geocoding.The service can be used to find address and places for many countries around the world. For detailed information on this service, including a data coverage map, visit the ArcGIS World Geocoding service documentation.

Some of the finest mountain scenery in the Southwest is found in the 1.6-million-acre Santa Fe National Forest. Here, you can find the headwaters of Pecos, Jemez, and Gallinas Rivers; mountain streams; lakes; and trout fishing. Travel into Pecos, San Pedro Parks, Chama, and Dome Wildernesses via wilderness pack trips, saddle, or on 1,000 miles of hiking trails. Try whitewater rafting on the Rio Chama or Rio Grande from May to September. Consider turkey, elk, deer, and bear hunting, or visit one of many nearby Indian pueblos, Spanish missions, and Indian ruins. Golden aspen grace the high country from September to October and snow blankets Santa Fe Ski Basin in winter. The Santa Fe National Forest GIS data available for download includes Santa Fe National Forest Geospatial (GIS) Datasets, Motor Vehicle Use Map (MVUM) Travel Aids - digital maps and data of the SFNF to upload to GPS units or Smart Phones, 7.5 Minute Topographic Maps (PDF and GeoTIFF) - US Forest Service topo maps only, USFS Geospatial Clearinghouse - includes GIS data of vegetation treatments, administrative boundaries, inventoried roadless areas, FSTopo datasets, USGS Map Locator and Downloader - download current and historic topo maps, Hardcopy Maps with information on how to purchase hard copy visitor, wilderness, or topographic maps. Resources in this dataset:Resource Title: Santa Fe National Forest Geospatial Data. File Name: Web Page, url: https://www.fs.usda.gov/main/santafe/landmanagement/gis

This presentation provides an overview of Atlantic provincial and city GIS resources.

Web application with the ability to search any geographical feature in Saskatchewan including city, town, lake, etc., and Provincial Highway