THE U.S. HISTORY GEOINQUIRY COLLECTIONhttp://www.esri.com/geoinquiriesTo support Esri’s involvement in the White House ConnectED Initiative, GeoInquiry instructional materials using ArcGIS Online for Earth Science education are now freely available. The U.S. History GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading high school U.S. History textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device agnostic. The activities harmonize with the C3 curriculum standards for social studies education. Activity topics include:· The Great Exchange· The 13 Colonies - 1700s· The War Before Independence (The American Revolution)· The War of 1812· Westward, ho! (Trails west)· The Underground Railroad· From Compromise to Conflict· A nation divided: The Civil War· Native American Lands· Steel and the birth of a city (natural resources)· World War I· Dust Bowl· A day that lived in infamy (Pearl Harbor)· Operation Overlord - D-Day· Hot spots in the Cold WarTeachers, GeoMentors, and administrators can learn more at http://www.esri.com/geoinquiries

The Digital Geologic-GIS Map of War in the Pacific National Historical Park and Vicinity, Guam is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (wapa_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (wapa_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (wapa_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (wapa_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (wapa_geology_metadata_faq.pdf). Please read the wapa_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (wapa_geology_metadata.txt or wapa_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:50,000 and United States National Map Accuracy Standards features are within (horizontally) 25.4 meters or 83.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

CShapes is a new dataset that provides historical maps of state boundaries and capitals in the post-World War II period. The dataset is coded according to both the Correlates of War and the Gleditsch and Ward (1999) state lists, and is therefore compatible with a great number of existing databases in the discipline. Provided in a geographic data format, CShapes can be used directly with standard GIS software, allowing a wide range of spatial computations. In addition, we supply a CShapes package for the R statistical toolkit. This package enables researchers without GIS skills to perform various useful operations on the GIS maps.

Homepage: https://icr.ethz.ch/data/cshapes/

The contents of this feature layer provide a visual aid for homes constructed during the period between 1945 to 1960. Data supporting the visual aids list which neighborhood these post World War II homes resides in, the style of the homes, along with its condition and integrity.The Historic Preservation Office works with the community to preserve these homes by enhancing archaeological, prehistoric, and historic resources throughout the City of Tempe. This work includes a wide range of partnerships with local homeowners, neighborhoods, developers/architects, boards/commissions, state and national agencies, as well as volunteer and non-profit preservation groupsContact: Will DukeContact E-Mail: will_duke@tempe.govContact Phone: N/ALink: N/AData Source: SQL Server/ArcGIS ServerData Source Type: GeospatialPreparation Method: N/APublish Frequency: As information changesPublish Method: AutomaticData Dictionary

Index of symbols found in British, Italian and Austro-Hungarian maps, and guidelines that indicate to the scholar the most suitable methods for digitizing World War I military maps and interpreting their symbology.

I parsed Damascus' urban sprawl and its main suburbs into a one-mile by one-mile grid approximately 18 miles long and 14 miles wide. On this grid, I superimposed a detailed geolocated dataset of violent conflict locations in Damascus and its suburbs on a daily basis during 2012 (source: ISW). I use the GIS dataset to study the effects of a quasi-experimental intervention in the Syrian nation-wide communications in November 2012, and to detect network patterns of proliferation and escalation in the context of civil conflict in Damascus. Supplement to Chapter 4 in "Leading from the Periphery and Network Collective Action".

The downloadable ZIP file contains model documentation and contact information for the model creator. For more information, or a copy of the project report which provides greater model detail, please contact Ryan Urie - traigo12@gmail.com.This model was created from February through April 2010 as a central component of the developer's master's project in Bioregional Planning and Community Design at the University of Idaho to provide a tool for identifying appropriate locations for various land uses based on a variety of user-defined social, economic, ecological, and other criteria. It was developed using the Land-Use Conflict Identification Strategy developed by Carr and Zwick (2007). The purpose of this model is to allow users to identify suitable locations within a user-defined extent for any land use based on any number of social, economic, ecological, or other criteria the user chooses. The model as it is currently composed was designed to identify highly suitable locations for new residential, commercial, and industrial development in Kootenai County, Idaho using criteria, evaluations, and weightings chosen by the model's developer. After criteria were chosen, one or more data layers were gathered for each criterion from public sources. These layers were processed to result in a 60m-resolution raster showing the suitability of each criterion across the county. These criteria were ultimately combined with a weighting sum to result in an overall development suitability raster. The model is intended to serve only as an example of how a GIS-based land-use suitability analysis can be conceptualized and implemented using ArcGIS ModelBuilder, and under no circumstances should the model's outputs be applied to real-world decisions or activities. The model was designed to be extremely flexible so that later users may determine their own land-use suitability, suitability criteria, evaluation rationale, and criteria weights. As this was the first project of its kind completed by the model developer, no guarantees are made as to the quality of the model or the absence of errorsThis model has a hierarchical structure in which some forty individual land-use suitability criteria are combined by weighted summation into several land-use goals which are again combined by weighted summation to yield a final land-use suitability layer. As such, any inconsistencies or errors anywhere in the model tend to reveal themselves in the final output and the model is in a sense self-testing. For example, each individual criterion is presented as a raster with values from 1-9 in a defined spatial extent. Inconsistencies at any point in the model will reveal themselves in the final output in the form of an extent different from that desired, missing values, or values outside the 1-9 range.This model was created using the ArcGIS ModelBuilder function of ArcGIS 9.3. It was based heavily on the recommendations found in the text "Smart land-use analysis: the LUCIS model." The goal of the model is to determine the suitability of a chosen land-use at each point across a chosen area using the raster data format. In this case, the suitability for Development was evaluated across the area of Kootenai County, Idaho, though this is primarily for illustrative purposes. The basic process captured by the model is as follows: 1. Choose a land use suitability goal. 2. Select the goals and criteria that define this goal and get spatial data for each. 3. Use the gathered data to evaluate the quality of each criterion across the landscape, resulting in a raster with values from 1-9. 4. Apply weights to each criterion to indicate its relative contribution to the suitability goal. 5. Combine the weighted criteria to calculate and display the suitability of this land use at each point across the landscape. An individual model was first built for each of some forty individual criteria. Once these functioned successfully, individual criteria were combined with a weighted summation to yield one of three land-use goals (in this case, Residential, Commercial, or Industrial). A final model was then constructed to combined these three goals into a final suitability output. In addition, two conditional elements were placed on this final output (one to give already-developed areas a very high suitability score for development [a "9"] and a second to give permanently conserved areas and other undevelopable lands a very low suitability score for development [a "1"]). Because this model was meant to serve primarily as an illustration of how to do land-use suitability analysis, the criteria, evaluation rationales, and weightings were chosen by the modeler for expediency; however, a land-use analysis meant to guide real-world actions and decisions would need to rely far more heavily on a variety of scientific and stakeholder input.

Investigate the Italian Western Front through the Battles of the Isonzo region.

During this activity students learn about the key fronts of World War I and the impact of US involvement.THE U.S. HISTORY GEOINQUIRY COLLECTIONhttp://www.esri.com/geoinquiriesTo support Esri’s involvement in the White House ConnectED Initiative, GeoInquiry instructional materials using ArcGIS Online for Earth Science education are now freely available. The U.S. History GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading high school U.S. History textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device agnostic. The activities harmonize with the C3 curriculum standards for social studies education. Activity topics include:· The Great Exchange· The 13 Colonies - 1700s· The War Before Independence (The American Revolution)· The War of 1812· Westward, ho! (Trails west)· The Underground Railroad· From Compromise to Conflict· A nation divided: The Civil War· Native American Lands· Steel and the birth of a city (natural resources)· World War I· Dust Bowl· A day that lived in infamy (Pearl Harbor)· Operation Overlord - D-Day· Hot spots in the Cold WarTeachers, GeoMentors, and administrators can learn more at http://www.esri.com/geoinquiries.

This paper presents an analysis of an environmental conflict that arose in a Thai industrial zone. The authors analyse state policies to resolve the conflict, and draw lessons for other industrializing nations adopting industrial zone models. The study revealed that a root cause of the conflict was violation of land-use planning regulations and expansion of the industrial zone into community areas. Through legal action, civil society successfully forced the state and industries to halt unplanned expansion. However, inadequate commitment by the state and industry stakeholders seems to perpetuate the conflict. A Geographic Information Systems (GIS)-based analysis confirmed that the state policy interventions did not produce significant results. This paper highlights the need for GIS-based environmental quality monitoring to guide industrialization-based urban development towards sustainability.

This dataset contains three shapefiles with buildings, derived from three different VHR satellite images of 2005, 2010, and 2014 of the city of Goma in the eastern DR Congo. These layers have been generated by manually digitizing each individual building, based on visual interpretation of the imagery. These building layers serve as the base for quantitative analysis and mapping of urban development - and hence constitute the geodata the article is based on.

Conflicting interests amongst different stakeholder groups regarding land use challenge the protection of natural values in socio-ecological systems (SES). In this paper we show, based on a case study of Israel’s Makhteshim Country National Park, how mapping the different interests and analyzing the data with a GIS system allows us to locate significant conflict points between groups. Semi-structured interviews were conducted with 60 individuals from three major stakeholder groups in the region: semi-nomadic Bedouins, nature reserve rangers, and tourist operators. The qualitative findings were then mapped by a GIS platform. The mapping indicated that the stakeholder groups’ land-use is distributed in a manner that makes conflict unavoidable, but relatively limited to only certain specific areas. Moreover, in some areas, the three groups share similar or complementary values, reaping mutual benefits from shared use. We conclude that GIS mapping can serve as a powerful tool for conflict management in complex SES.

Mapping sunken ships from during the second world war - over 20,000 ships where sunk.Paul Heersink is the man behind the data.

Students will learn about the key fronts of World War I and the impact of the United States’ involvement. The activity uses a web-based map and is tied to the C3 Framework.

Learning outcomes:

Students will be able to identify the Allied Powers, Central Powers, Western Front, and Eastern Front.Students will be able to identify and explain how U.S. involvement changed the course of World War I.

Find more US History GeoInquiries here or explore all GeoInquiries at https://www.esri.com/geoinquiries

Data set that contains information on archaeological remains of the pre historic settlement of the Letolo valley on Savaii on Samoa. It is built in ArcMap from ESRI and is based on previously unpublished surveys made by the Peace Corps Volonteer Gregory Jackmond in 1976-78, and in a lesser degree on excavations made by Helene Martinsson Wallin and Paul Wallin. The settlement was in use from at least 1000 AD to about 1700- 1800. Since abandonment it has been covered by thick jungle. However by the time of the survey by Jackmond (1976-78) it was grazed by cattle and the remains was visible. The survey is at file at Auckland War Memorial Museum and has hitherto been unpublished. A copy of the survey has been accessed by Olof Håkansson through Martinsson Wallin and Wallin and as part of a Masters Thesis in Archeology at Uppsala University it has been digitised.

Olof Håkansson has built the data base structure in the software from ESRI, and digitised the data in 2015 to 2017. One of the aims of the Masters Thesis was to discuss hierarchies. To do this, subsets of the data have been displayed in various ways on maps. Another aim was to discuss archaeological methodology when working with spatial data, but the data in itself can be used without regard to the questions asked in the Masters Thesis. All data that was unclear has been removed in an effort to avoid errors being introduced. Even so, if there is mistakes in the data set it is to be blamed on the researcher, Olof Håkansson. A more comprehensive account of the aim, questions, purpose, method, as well the results of the research, is to be found in the Masters Thesis itself. Direkt link http://uu.diva-portal.org/smash/record.jsf?pid=diva2%3A1149265&dswid=9472

Purpose:

The purpose is to examine hierarchies in prehistoric Samoa. The purpose is further to make the produced data sets available for study.

Prehistoric remains of the settlement of Letolo on the Island of Savaii in Samoa in Polynesia

World War One was a global war that aligned the Allies (Britain, France, and the Russian Empire) against Germany and Austria - Hungary. As a dominion of the British Empire, New Zealand was called upon to defend the empire for king and country. The war took approximately 100,000 New Zealanders overseas, many for the first time. Some anticipated a great adventure but found the reality very different. Being so far from home made these New Zealanders very aware of who they were and where they were from. In battle, they were able to compare themselves with men from other nations. Out of this, many have argued, came a sense of a separate identity, and many New Zealand soldiers began to refer to themselves as ‘Kiwis’.

The Geological Atlas of the Western Canada Sedimentary Basin was designed primarily as a reference volume documenting the subsurface geology of the Western Canada Sedimentary Basin. This GIS dataset is one of a collection of shapefiles representing part of Chapter 24 of the Atlas, Uppermost Cretaceous and Tertiary Strata of the Western Canada Sedimentary Basin, Figure 14, Battle/Kneehills Tuff Structure. Shapefiles were produced from archived digital files created by the Alberta Geological Survey in the mid-1990s, and edited in 2005-06 to correct, attribute and consolidate the data into single files by feature type and by figure.

The Geological Atlas of the Western Canada Sedimentary Basin was designed primarily as a reference volume documenting the subsurface geology of the Western Canada Sedimentary Basin. This GIS dataset is one of a collection of shapefiles representing part of Chapter 24 of the Atlas, Uppermost Cretaceous and Tertiary Strata of the Western Canada Sedimentary Basin, Figure 4e, Schematic Battle Fm Paleogeography. Shapefiles were produced from archived digital files created by the Alberta Geological Survey in the mid-1990s, and edited in 2005-06 to correct, attribute and consolidate the data into single files by feature type and by figure.

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.