Proof web map for GeoInquiries Advanced Environmental Science lesson on Tropical Deforestation.THE ADVANCED ENVIRONMENTAL SCIENCE AND BIOLOGY GEOINQUIRY COLLECTIONhttp://www.esri.com/geoinquiriesTo support Esri’s involvement in the White House ConnectED Initiative, GeoInquiry instructional materials using ArcGIS Online for high school biology education are now freely available.The Advanced Environmental Science and Biology GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading elementary textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device/laptop agnostic. The activities harmonize with the Next Generation Science Standards. Activity topics include:• Population dynamics • Megacities • Down to the last drop • Dead zones (water pollution) • The Beagle’s Path • Primary productivity • Tropical Deforestation • Marine debris • El Nino (and climate) • Slowing malaria • Altered biomes • Spinning up wind power • Resource consumption and wealthTeachers, GeoMentors, and administrators can learn more at http://www.esri.com/geoinquiries

This Innovative Technology Experiences for Students and Teachers (ITEST) project has developed, implemented, and evaluated a series of innovative Socio-Environmental Science Investigations (SESI) using a geospatial curriculum approach. It is targeted for economically disadvantaged 9th grade high school students in Allentown, PA, and involves hands-on geospatial technology to help develop STEM-related skills. SESI focuses on societal issues related to environmental science. These issues are multi-disciplinary, involve decision-making that is based on the analysis of merged scientific and sociological data, and have direct implications for the social agency and equity milieu faced by these and other school students. This project employed a design partnership between Lehigh University natural science, social science, and education professors, high school science and social studies teachers, and STEM professionals in the local community to develop geospatial investigations with Web-based Geographic Information Systems (GIS). These were designed to provide students with geospatial skills, career awareness, and motivation to pursue appropriate education pathways for STEM-related occupations, in addition to building a more geographically and scientifically literate citizenry. The learning activities provide opportunities for students to collaborate, seek evidence, problem-solve, master technology, develop geospatial thinking and reasoning skills, and practice communication skills that are essential for the STEM workplace and beyond. Despite the accelerating growth in geospatial industries and congruence across STEM, few school-based programs integrate geospatial technology within their curricula, and even fewer are designed to promote interest and aspiration in the STEM-related occupations that will maintain American prominence in science and technology. The SESI project is based on a transformative curriculum approach for geospatial learning using Web GIS to develop STEM-related skills and promote STEM-related career interest in students who are traditionally underrepresented in STEM-related fields. This project attends to a significant challenge in STEM education: the recognized deficiency in quality locally-based and relevant high school curriculum for under-represented students that focuses on local social issues related to the environment. Environmental issues have great societal relevance, and because many environmental problems have a disproportionate impact on underrepresented and disadvantaged groups, they provide a compelling subject of study for students from these groups in developing STEM-related skills. Once piloted in the relatively challenging environment of an urban school with many unengaged learners, the results will be readily transferable to any school district to enhance geospatial reasoning skills nationally.

Data for maps and figures in "Global Potential for Harvesting Drinking Water from Air using Solar Energy" in Nature.

THE ADVANCED ENVIRONMENTAL SCIENCE AND BIOLOGY GEOINQUIRY COLLECTIONhttp://www.esri.com/geoinquiriesTo support Esri’s involvement in the White House ConnectED Initiative, GeoInquiry instructional materials using ArcGIS Online for high school biology education are now freely available.The Advanced Environmental Science and Biology GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading elementary textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device/laptop agnostic. The activities harmonize with the Next Generation Science Standards. Activity topics include:• Population dynamics • Megacities • Down to the last drop • Dead zones (water pollution) • The Beagle’s Path • Primary productivity • Tropical Deforestation • Marine debris • El Nino (and climate) • Slowing malaria • Altered biomes • Spinning up wind power • Resource consumption and wealthTeachers, GeoMentors, and administrators can learn more at http://www.esri.com/geoinquiries

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 ...

GIS dataset with TIFFs and tsw files

THE ADVANCED ENVIRONMENTAL SCIENCE AND BIOLOGY GEOINQUIRY COLLECTIONhttp://www.esri.com/geoinquiriesTo support Esri’s involvement in the White House ConnectED Initiative, GeoInquiry instructional materials using ArcGIS Online for high school biology education are now freely available.The Advanced Environmental Science and Biology GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading elementary textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device/laptop agnostic. The activities harmonize with the Next Generation Science Standards. Activity topics include:• Population dynamics • Megacities • Down to the last drop • Dead zones (water pollution) • The Beagle’s Path • Primary productivity • Tropical Deforestation • Marine debris • El Nino (and climate) • Slowing malaria • Altered biomes • Spinning up wind power • Resource consumption and wealthTeachers, GeoMentors, and administrators can learn more at http://www.esri.com/geoinquiries

GIS Layers used to create the hunting habitat model, which include Cattle density, Distance from edge, Dominant landcover, Forest edge density, Forest patch size, Improved pasture patch size, Landcover, and Percent forest cover. Area of analysis defined by Minimum Convex Polygons created from Florida panther GPS data.

Environmental pollution is a persistent problem in terrestrial ecosystems, including remote mountain areas. This study investigates the extent and patterns of littering on three popular hiking trails among mountaineers and tourists in the Dolomites range located in northeastern Italy. The data was collected adopting a citizen science approach with the participation of university students surveying the trails and recording the macroscopic waste items through a GPS-based offline platform. The waste items were categorized according to their material type, usage, and geographical location, and the sorted data was applied to Esri GIS ArcMapTM 10.8.1.

Explore water pollution and its impact on marine life.THE ADVANCED ENVIRONMENTAL SCIENCE AND BIOLOGY GEOINQUIRY COLLECTIONhttp://www.esri.com/geoinquiriesTo support Esri’s involvement in the White House ConnectED Initiative, GeoInquiry instructional materials using ArcGIS Online for high school biology education are now freely available.The Advanced Environmental Science and Biology GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading elementary textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device/laptop agnostic. The activities harmonize with the Next Generation Science Standards. Teachers, GeoMentors, and administrators can learn more at http://www.esri.com/geoinquiries

THE ADVANCED ENVIRONMENTAL SCIENCE AND BIOLOGY GEOINQUIRY COLLECTIONhttp://www.esri.com/geoinquiriesTo support Esri’s involvement in the White House ConnectED Initiative, GeoInquiry instructional materials using ArcGIS Online for high school biology education are now freely available.The Advanced Environmental Science and Biology GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading elementary textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device/laptop agnostic. The activities harmonize with the Next Generation Science Standards and AP Environmental Science benchmarks. Activity topics include:Teachers, GeoMentors, and administrators can learn more at http://www.esri.com/geoinquiries

Litter surveys using GPS.

This folder contains the hydrological and geological data from DK-model2019. Grid files and .shp files are assembled in ArcGIS Pro v.3.0.1. DK-model2019 setup and calibration is described in GEUS report 2019/31.

GIS Layers used to create the hunting habitat model, which include Cattle density, Distance from edge, Dominant landcover, Forest edge density, Forest patch size, Improved pasture patch size, Landcover, and Percent forest cover. Area of analysis defined by Minimum Convex Polygons created from Florida panther GPS data.

Shapefile used in the various maps in the study. Visit https://dataone.org/datasets/sha256%3A2fdaa83821076dc77d906d53f13fd8aaa6ecb2f8bf1e16082352037b5459f465 for complete metadata about this dataset.

A platform-agnostic and living geographic information data dictionary for trafficking of wild flora and fauna based on diverse stakeholder input and with the potential to accelerate convergence of information and increase efficacy of interventions.

The research focus in the field of remotely sensed imagery has shifted from collection and warehousing of data ' tasks for which a mature technology already exists, to auto-extraction of information and knowledge discovery from this valuable resource ' tasks for which technology is still under active development. In particular, intelligent algorithms for analysis of very large rasters, either high resolutions images or medium resolution global datasets, that are becoming more and more prevalent, are lacking. We propose to develop the Geospatial Pattern Analysis Toolbox (GeoPAT) a computationally efficient, scalable, and robust suite of algorithms that supports GIS processes such as segmentation, unsupervised/supervised classification of segments, query and retrieval, and change detection in giga-pixel and larger rasters. At the core of the technology that underpins GeoPAT is the novel concept of pattern-based image analysis. Unlike pixel-based or object-based (OBIA) image analysis, GeoPAT partitions an image into overlapping square scenes containing 1,000'100,000 pixels and performs further processing on those scenes using pattern signature and pattern similarity ' concepts first developed in the field of Content-Based Image Retrieval. This fusion of methods from two different areas of research results in orders of magnitude performance boost in application to very large images without sacrificing quality of the output.

GeoPAT v.1.0 already exists as the GRASS GIS add-on that has been developed and tested on medium resolution continental-scale datasets including the National Land Cover Dataset and the National Elevation Dataset. Proposed project will develop GeoPAT v.2.0 ' much improved and extended version of the present software. We estimate an overall entry TRL for GeoPAT v.1.0 to be 3-4 and the planned exit TRL for GeoPAT v.2.0 to be 5-6. Moreover, several new important functionalities will be added. Proposed improvements includes conversion of GeoPAT from being the GRASS add-on to stand-alone software capable of being integrated with other systems, full implementation of web-based interface, writing new modules to extent it applicability to high resolution images/rasters and medium resolution climate data, extension to spatio-temporal domain, enabling hierarchical search and segmentation, development of improved pattern signature and their similarity measures, parallelization of the code, implementation of divide and conquer strategy to speed up selected modules.

The proposed technology will contribute to a wide range of Earth Science investigations and missions through enabling extraction of information from diverse types of very large datasets. Analyzing the entire dataset without the need of sub-dividing it due to software limitations offers important advantage of uniformity and consistency. We propose to demonstrate the utilization of GeoPAT technology on two specific applications. The first application is a web-based, real time, visual search engine for local physiography utilizing query-by-example on the entire, global-extent SRTM 90 m resolution dataset. User selects region where process of interest is known to occur and the search engine identifies other areas around the world with similar physiographic character and thus potential for similar process. The second application is monitoring urban areas in their entirety at the high resolution including mapping of impervious surface and identifying settlements for improved disaggregation of census data.

Updated Prefecture Polygons now have mostly complete spatial coverage for the Dynastic administrative units from 1350 - 1911 CE. Prefectures from earlier periods, 221 BCE to 1350 CE, still have gaps in spatial coverage.

This folder contains contain various results simulated with DK-model2019. Grid files and .shp files are assembled in ArcGIS Pro v.3.0.1. For results regarding streamflow, seepage from groundwater to streams, depth to groundwater table, net precipitation, recharge and water velocity, refer to GEUS report 2019/32. For results regarding delineation of groundwater bodies, contact between groundwater bodies and surface water, abstractions linked to the groundwater bodies, refer to GEUS report 2020/1. For results, regarding changes in simulated groundwater head levels, change in depth to the groundwater table and change in stream runoff, refer again to GEUS report 2019/32. For a detailed description of the procedure, including the distribution of extracted amounts per water plant, connection to groundwater, etc., refer to GEUS report 2021/19 Annex 6.

Taken from the survey report:

Documentation is provided for surveying tasks - by Tom Velthuis - at Macquarie Island and Casey, during the summer of 2000/1. The report is presented in five key sections: 1. GPR related surveying in Thala Valley - Casey; 2. Non GPR related surveying in Thala Valley; 3. Surveys conducted outside of Thala Valley; 4. Surveys at Macquarie Island; and 5. Survey data to GIS. The first three sections relate to Casey; the fourth section to Macquarie Island; and the fifth section documents the transfer of data to GIS.

For more details see the report available as part of the download.

Taken from the readme file accompanying the data:

The folder named, 'shape' contains projected (UTM) and unprojected shapefiles, based on WGS84, relating to surveys by Tom Velthuis at Macquarie Island and Casey during the summer 2000/2001 season. See report: Survey Report.doc.

The folder named, 'excel_files' contains excel files by Tom Velthuis used for computing surveying work performed at Macquarie Island and Casey during the summer 2000/1. The 'Windmill Islands control' file is a file given to Tom by Tom Gordon.

The folder labelled, 'tomv pics scanned' contains photographs (by Tom Velthuis) relating to surveying work conducted at Casey during the summer 2000/1. Most of the photos are in the report labelled, 'Survey Report.doc'.

The folder labelled, 'TomVforGIS' contains files generated by Tom Velthuis, for the creation of shapefiles in ArcView. The files relate to Surveying work conducted at Macquarie Island and Casey during Summer 2000/1.

macca_levels.xls has additional notes on the levelling of buildings at Macquarie Island.

Also, map number 13248 in the SCAR Map Catalogue shows crosses on the buildings at Macquarie Island indicating the approximate location of levelling to the buildings. macca_levels.xls has the same content as the dbf file referred to on the map. See Related URL below for the SCAR Map Catalogue entry.