This repository contains two Microsoft Excel documents:A quiz with eight questions, assigned to students in a graduate-level GIS programming course as part of Homework Assignment 2. The quiz assesses students' understanding of basic Python programming principles (such as loops and conditional statements).An Excel document with three worksheets, each corresponding to one homework assignment from the same graduate GIS programming course. The document includes self-reported background information (e.g., students' prior programming experience), details about the use of various resources (e.g., websites) for completing assignments, the perceived helpfulness of these resources, and scores for the homework assignments and quizzes.

The Gas Insulated Switchgear (GIS) Test Kit market is experiencing robust growth, driven by the increasing adoption of GIS in power transmission and distribution networks globally. The rising demand for reliable and efficient power systems, coupled with stringent safety regulations, is fueling the market expansion. While precise market size data for GIS Test Kits is not explicitly provided, we can infer a substantial market value based on the broader context of the Partial Discharge (PD) Test Kit market and related equipment. Considering a conservative estimate, let's assume the GIS Test Kit segment constitutes approximately 15% of the overall PD Test Kit market. If we further posit that the overall PD Test Kit market size is $500 million in 2025 (a reasonable estimate given the scale of the broader electrical testing market), the GIS Test Kit market size would be around $75 million in 2025. With a projected Compound Annual Growth Rate (CAGR) of 7% (a conservative estimate considering technological advancements and infrastructural development), the market is poised to reach approximately $115 million by 2033. Key drivers include the increasing complexity of GIS systems necessitating sophisticated testing equipment, growing investments in renewable energy infrastructure (which often utilizes GIS), and stringent grid modernization initiatives globally. Market trends point toward increasing demand for integrated testing solutions, portable and user-friendly devices, and advanced diagnostic capabilities. Constraints may include high initial investment costs for sophisticated testing equipment and the need for specialized expertise in operating and interpreting test results. However, these challenges are likely to be offset by the long-term benefits of enhanced grid reliability and reduced downtime. Major players in the market are leveraging technological innovations and strategic partnerships to solidify their market positions.

Paired sample t-tests comparing modeled distance, time, and kilocalorie expenditure to those recorded by the Fitbit® Surge.

COVID-19 Testing sites dataset provided by the City Managers department. Updated on 10/25/2021. Projected Coordinate System: NAD 1983 StatePlane California VI FIPS 0406 (US Feet)Projection: Lambert Conformal Conic

Feature service for test editing of points lines and polygon feature class.Data Distribution and Retention:• Data is copied nightly from ArcGIS Online into a GIS Database located on the Skagit County Network. Important Notes:• This data is integrated into automated processes (nightly copy), with dependencies. Changes to the data schema, will affect these processes and dependencies. Any changes to the data schema should be coordinated with the GIS Department.

Announcement: Project Ended on October 15, 2021After over 18 months of collaboration between hundreds of GISCorps volunteers, Esri's Disaster Response Program, Coders Against COVID, HERE Technologies, dozens of government agencies, and hundreds of testing providers, GISCorps has decided to end our COVID-19 Testing and Vaccination Sites Data Creation Project as of October 15th, 2021. Our data will remain available for use by researchers and analysts, but it should not be considered a reliable source of current testing and vaccination site location information after October 15th. We are grateful for the support we have received by so many throughout the life of this monumental undertaking. Read more about this effort https://covid-19-giscorps.hub.arcgis.com/pages/contribute-covid-19-testing-sites-data.Item details page: https://giscorps.maps.arcgis.com/home/item.html?id=d7d10caf1cec43e0985cc90fbbcf91cbThis view is the original COVID-19 Testing Locations in the United States - public dataset. A backup copy also exists: https://giscorps.maps.arcgis.com/home/item.html?id=11fe8f374c344549815a716c8472832f. The parent hosted feature service is the same. This version is symbolized by type of test (molecular, antibody, antigen, or combinations thereof).This feature layer view contains information about COVID-19 screening and testing locations. It is made available to the public using the GISCorps COVID-19 Testing Site Locator app (https://giscorps.maps.arcgis.com/apps/webappviewer/index.html?id=2ec47819f57c40598a4eaf45bf9e0d16) and on findcovidtesting.com. All information was sourced from public information shared by health departments, local governments, and healthcare providers. The data are aggregated by GISCorps volunteers in collaboration with volunteers from Coders Against COVID and should not be considered complete or authoritative. Please contact testing sites or your local health department directly for official information and testing requirements.The objective of this application is to aggregate and facilitate the public communications of local governments, health departments, and healthcare providers with regard to testing site locations. GISCorps does not share any screening or testing site location information not previously made public or provided to us by one of those entities.Data dictionary document: https://docs.google.com/document/d/1HlFmtsT3GzibixPR_QJiGqGOuia9r-exN3i5UK8c6h4/edit?usp=sharingArcade code for popups: https://docs.google.com/document/d/1PDOq-CxUX9fuC2v3N8muuuxN5mLMinWdf7fiwUt1lOM/edit?usp=sharing

A test to adjust the NHD flowline according the underlying DEM on Rolling Wood catchment, Texas

Coastlines for the Northwest Hawaiian Islands. Created by NOS National Geodetic Survey, 2001. Downloaded by Esri Hawaii staff from NOS National Geodetic Survey website, 2016. For more information, please see metadata at https://files.hawaii.gov/dbedt/op/gis/data/coastline_nwhi.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, HI 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

Data was collected from GRD-TRT-BUF-4I (Ground Truth Buffer for Idling), a realtime detection systemthat records the geolocation and idling duration of urban transit bus fleets internationally. test-data-a.csv was collected from December 31, 2023 00:01:30 UTC to January 1, 2024 00:01:30 UTC. test-data-b.csv was collected from January 4, 2024 01:30:30 UTC to January 5, 2024 01:30:30 UTC.test-data-c.csv was collected from January 10, 2024 16:05:30 UTC to January 11,2024 16:05:30 UTC.

This dataset explains validation testing in a study of the Samarinda Seberang flood vulnerability map. There are two test methods, namely the Kappa accuracy test and the 3D simulation visualization test. The Kappa accuracy test tab displays a table of Kappa calculation results, and the second tab contains a 3D simulation scenario image.

The global Partial Discharge Testing System market is experiencing robust growth, driven by the increasing demand for reliable and efficient power grids and the rising adoption of smart grid technologies. The market is projected to reach a significant size, exhibiting a substantial Compound Annual Growth Rate (CAGR). While precise figures for market size and CAGR are not provided, based on industry trends and the prevalence of aging infrastructure requiring regular maintenance, a reasonable estimate for the 2025 market size could be around $800 million, with a CAGR of 7% projected for the forecast period 2025-2033. This growth is fueled by factors such as the expanding electricity generation and transmission infrastructure, particularly in developing economies, and stringent regulations aimed at improving grid reliability and safety. Furthermore, technological advancements leading to more compact, portable, and user-friendly partial discharge testers are boosting market adoption. Key segments driving market growth include portable partial discharge testers, owing to their ease of use and adaptability in various field applications, and applications focused on GIS (Gas Insulated Switchgear), transformers, and power cables, where timely and accurate partial discharge detection is critical for preventing costly equipment failures and potential power outages. Despite these positive trends, market expansion is somewhat restrained by the high initial investment costs associated with procuring advanced testing systems, and the relatively specialized skill set required for accurate interpretation of test results. However, increasing awareness of the long-term cost-benefits of preventative maintenance and the availability of training programs are gradually mitigating these constraints. This market presents significant opportunities for manufacturers who can innovate in areas like improved accuracy, enhanced portability, and the integration of advanced data analytics capabilities into their systems.

In March 2001, the New Jersey Private Well Testing Act (PWTA) was signed into law, and its regulations became effective in September 2002. The PWTA is a consumer information law that requires sellers or buyers of property with wells in NJ to test the untreated ground water for a variety of water quality parameters. The test data is submitted electronically by the test laboratories to the NJ Department of Environmental Protection for statewide analysis of ground water quality. These data presented here provide a summary of the percentage of wells within each municipality that exceeded a maximum contaminant level (MCL) or secondary standard for the period September 2002 to December 2023.

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Significant clusters with high HCV risk as determined by the spatial scan statistic.

Images created to test the variability of landscape metrics for maps with different Aggregation Index values.
Sets fig1.zip, fig2.zip and fig3.zip contain synthetic images described in Section 2 "Aggregation index" of the paper "Relationship between aggregation index and change in the values of some landscape metrics as a function of cell neighborhood choice" in publication. File names correspond to figures in this paper. Some images are original creations based on figures in: He, H.; Dezonia, B.; Mladenoff, D. An Aggregation Index (AI) to Quantify Spatial Patterns of Landscapes. Landscape Ecology 2000, 15, 591–601. https://doi.org/10.1023/A:1008102521322.
File Bosco_94fassa_10m.tiff contains a binary map representing forest coverage (value 1) in the Val di Fassa, in the eastern Italian Alps, in 1994. It has been created by image classification on a set of 1994 grayscale orthophotos. The map is in the ETRS89/UTM 32N (EPSG: 25832) datum.

The Aggregate Resource Mapping Program (ARMP) began in 1984 when the Minnesota Legislature passed a law (Minnnesota Statutes, section 84.94) to:
- Identify and classify aggregate resources outside of the Twin Cities metropolitan area;
- Give aggregate resource information to local units of government and others for making comprehensive land-use and zoning plans;
- Introduce aggregate resource protection; and Promote orderly and environmentally sound development of the resource.

Provided here is a compilation of GIS data produced by the DNR's Aggregate Resource Mapping Program. Also provided is the aggregate resource GIS data from the 7-County Metropolitan Area mapped by the Minnesota Geological Survey (MGS). Please see the layer-specific metadata for each of the 9 layers for more details:

ARMP:
Compilation of Gravel Pits, Quarries, and Prospects
Compilation of Crushed Stone Resource Potential
Compilation of Geologic Field Observations
Compilation of Sand and Gravel Resource Potential
Compilation of DNR Test Holes
Status Map

7-County Metro Area:
Compilation of Pits and Quarries
Bedrock Aggregate Sources
Sand and Gravel Sources

A feature layer view used by the public containing information about COVID-19 screening and testing locations using the GISCorps COVID-19 Testing Site Locator app (https://giscorps.maps.arcgis.com/apps/webappviewer/index.html?id=2ec47819f57c40598a4eaf45bf9e0d16). Please submit updates to testing site information via this form: https://arcg.is/10S1ibAll information is sourced from public information shared by health departments, local governments, and healthcare providers. The data are aggregated by GISCorps volunteers in collaboration with volunteers from Coders Against COVID and should not be considered authoritative. Please contact testing sites or your local health department directly for official information and testing requirements.The objective of this application is to aggregate and facilitate the public communications of local governments, health departments, and healthcare providers. GISCorps does not share any screening or testing site location information not previously made public by one of those entities.

100 wells of groundwater resources.

This is the static test data from the study "Global Geolocated Realtime Data of Interfleet Urban Transit Bus Iding" collected by GRD-TRT-BUF-4I. Updated versions are available here.test-data-a.csv was collected from December 31, 2023 00:01:30 UTC to January 1, 2024 00:01:30 UTC.test-data-b.csv was collected from January 4, 2024 01:30:30 UTC to January 5, 2024 01:30:30 UTC.test-data-c.csv was collected from January 10, 2024 16:05:30 UTC to January 11, 2024 16:05:30 UTC.test-data-d.csv was collected from January 15, 2024 22:30:21 UTC to January 16, 2024 22:30:17 UTC.test-data-e.csv was collected from February 16, 2024 22:30:21 UTC to February 17, 2024 22:30:20 UTC.test-data-f.csv was collected from February 21, 2024 22:30:21 UTC to February 22, 2024 22:30:20 UTC.

Supplementary Tables S1–S6