In Module 2 Lesson 1, we will take a deeper dive into Geographic Information Systems (GIS) technology. We'll explore different types of GIS data, the importance of data attributes and queries, data symbolization, and ways to access GIS technology.

The U.S. Fish and Wildlife Service Corporate Master Table (CMT) is the official source of Service organization codes and related information. Information in the CMT includes, but is not limited to, organization codes, organization names, Federal Budget Management System (FBMS), cost center codes, fire unit identifiers, program names, mailing and physical/shipping addresses, telephone and fax numbers as well as latitude and longitude coordinates. The CMT enables all Service automated systems to utilize a corporate data set of known quality, eliminating the workload required to maintain each system's data set, and thereby facilitating data sharing. Other customers for the CMT are Service personnel who maintain directories, communicate with Congress and with the Public, maintain World Wide Web sites, etc. These spatial data were created using the information in the CMT. The CMT contains location information on all the offices within the Service that have an organization code. Unstaffed offices and some other facilities may not be included. The latitude and longitude points used are usually the location of the main administrative site. The latitude and longitude data is not completely verified but is the best we have at this time. This data set is intended to give an overview of where USFWS has stations across the United States and Territories, including locations outside the 50 states. It is not intended to be the exact location of every USFWS office. The CMT is primarily used for accounting purposes and therefore one location in the CMT can represent many different offices. Some points are duplicates where a station, most usually an Ecological Field Office, may be associated with more than one USFWS program. This data is updated from an internal authoritative source every night at 2:30am EST.For a direct link to the official Enterprise Geospatial dataset and metadata: https://ecos.fws.gov/ServCat/Reference/Profile/60076.Dataset contact: fwsgis@fws.gov

The Kansas Master Ground-water Well Inventory (MWI) is a central repository that imports and links together the State's primary ground-water well data sets- KDHE's WWC5, KDA-DWR's WIMAS, and KGS' WIZARD into a single, online source. The most "accurate" of the common source fields are used to represent the well sites, for example- GPS coordinates if available are used over other methods to locate a well. The MWI maintains the primary identification tags to allow specific well records to be linked back to the original data sources.This mapper is managed by the Kansas Geological Survey. For more information about the data, please see the Groundwater Master Well Inventory page.

This metadata record describes the acquisition and production of 1 foot contours for 5 coastal counties Hancock, Harrison, Jackson, Pearl River and Stone. The breaklines were collected from digital imagery with a 15 cmground sample distance (GSD) for the project area for the 1 foot contour area and 30 cm for the 5 foot contour area. All imagery was acquired in spring 2007 and processed during the spring & summer of 2007. The imagery is from a project tasked by Mississippi Geographic Information, LLC (MGI) with Work Orders ED-9 & ED-9A. EarthData International, Inc. was authorized to undertake this project in accordance with the terms and conditions of the professional service agreement between MGI and EarthData International, Inc., dated February 14, 2007.

This metadata record describes the acquisition and production of 1 foot contours for 5 coastal counties Hancock, Harrison, Jackson, Pearl River and Stone. The breaklines were collected from digital imagery with a 15 cmground sample distance (GSD) for the project area for the 1 foot contour area and 30 cm for the 5 foot contour area. All imagery was acquired in spring 2007 and processed during the spring & summer of 2007. The imagery is from a project tasked by Mississippi Geographic Information, LLC (MGI) with Work Orders ED-9 & ED-9A. EarthData International, Inc. was authorized to undertake this project in accordance with the terms and conditions of the professional service agreement between MGI and EarthData International, Inc., dated February 14, 2007.

Deprecated as of 4/27/2023On 4/27/2023 several COVID-19 datasets were retired and no longer included in public COVID-19 data dissemination. For more information, visit https://imap.maryland.gov/pages/covid-dataSummaryThe cumulative number of positive COVID-19 cases among Maryland residents within a single Maryland ZIP code.DescriptionThe MD COVID-19 - Cases by ZIP Code data layer is a collection of positive COVID-19 test results that have been reported each day by the local health department via the NEDSS system.COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

This layer shows the Cavern Master Plan of Hong Kong. It is a subset of the geo-referenced data made available by the Civil Engineering and Development Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data has been processed and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. States and equivalent entities are the primary governmental divisions of the United States. In addition to the fifty states, the Census Bureau treats the District of Columbia, Puerto Rico, and each of the Island Areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands) as the statistical equivalents of states for the purpose of data presentation.

This web map shows the Invigorating Island South Conceptual Master Plan 3.0 - Wong Chuk Hang, Aberdeen and Ap Lei Chau. It is a set of data made available by the Development Bureau under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data has been processed and converted into Esri File Geodatabase format and uploaded to Esri's ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Hong Kong CSDI Portal at https://portal.csdi.gov.hk.

Summary: NEW VERSION is at https://esriurl.com/agoschoolcompStorymap metadata page: URL forthcoming Possible K-12 Next Generation Science standards addressed:Grade level(s) 6-8: Standard MS-LS4-4 - Biological Evolution: Unity and Diversity - Construct an explanation based on evidence that describes how genetic variations of traits in a population increase some individuals’ probability of surviving and reproducing in a specific environmenGrade level(s) 6-8: Standard MS-LS4-6 - Biological Evolution: Unity and Diversity - Use mathematical representations to support explanations of how natural selection may lead to increases and decreases of specific traits in populations over timeGrade level(s) 6-8: Standard MS-ESS1-2 - Earth’s Place in the Universe - Develop and use a model to describe the role of gravity in the motions within galaxies and the solar systemGrade level(s) 6-8: Standard MS-ESS2-4 - Earth’s Systems - Develop a model to describe the cycling of water through Earth’s systems driven by energy from the sun and the force of gravityGrade level(s) 9-12: Standard HS-PS1-2 - Matter and Its Interactions - Construct and revise an explanation for the outcome of a simple chemical reaction based on the outermost electron states of atoms, trends in the periodic table, and knowledge of the patterns of chemical propertiesGrade level(s) 9-12: Standard HS-LS2-1 - Ecosystems: Interactions, Energy, and Dynamics - Use mathematical and/or computational representations to support explanations of factors that affect carrying capacity of ecosystems at different scalesGrade level(s) 9-12: Standard HS-LS4-2 - Biological Evolution: Unity and Diversity - Construct an explanation based on evidence that the process of evolution primarily results from four factors: (1) the potential for a species to increase in number, (2) the heritable genetic variation of individuals in a species due to mutation and sexual reproduction, (3) competition for limited resources, and (4) the proliferation of those organisms that are better able to survive and reproduce in the environment.Most frequently used words:competitionesrihsstateApproximate Flesch-Kincaid reading grade level: 10.3. The FK reading grade level should be considered carefully against the grade level(s) in the NGSS content standards above.

Zoning designations of land use within the unincorporated areas of Napa County.

See 2018 IPTP report for more detailed methodology results discussions. The IPTP analysis parameters and spatial units were determined by available data and expert opinion. An advisory panel comprised of local, state, and federal natural resource managers and invasive plant experts suggested a number of managerial and environmental measures to be considered in the analysis. The expert panel included professionals from Arizona Department of Agriculture (ADA), Arizona Department of Transportation (ADOT), Arizona Game and Fish Department (AGFD), Arizona State Land Department (ASLD), Arizona-Sonora Desert Museum, Bureau of Land Management (BLM), DFFM, U.S. Fish and Wildlife Service (US FWS), University of Arizona Cooperative Extension, USDA FS. The initial list of general topics included: fire risk, riparian areas, protected species, spread corridors, Invasive Plant Threat Levels, areas of prior treatments, economic impact, accessibility for treatment, higher risk to introduction (Wildland Urban Interface - WUI), water bodies of high value, undeveloped areas, and sustainability. Existing local, state-, and nation-wide datasets were a good fit for most topics; but, in a few cases, alternate datasets had to be created or found. Economic impact, accessibility for treatments, water bodies of high value, and sustainability parameters were not included because of quantification difficulties, due to limited data availability, and to reduce double counting. We attempted to capture a measure of invasive plants treatment sustainability by supporting areas with active, local weed or invasive plant management groups but were not able to capture it spatially in a representative manner at the time of analysis.For better cross comparison, the selected dataset's scores were converted into a normalized index with a value range between 0 (“cool”) and 1 (“hot”):normalized index value = (score value – score min) / (score max – score min)All indices have been calculated for a 1 square mile hexagon analysis area. A hexagon GIS layer provided by AGFD ensured a standardized spatial unit at an appropriate resolution which was unmistakable from land ownership boundaries.The 8 normalized indices were averaged by adding them together and dividing them by 8 to generate a final score. Besides normalizing all scores between 0 and 1, we did not apply any statistical corrections or preference weights to the 8 sub-indices.

Access the file geodatabase source data in SC State Plane coordinate system

To interpret these datasets, it is essential that you have a copy of the hand-annotated survey instrument, "Boulder OSMP Codebook Version A.pdf," along with all three of the following csv files described below. In addition, these datasets were released in coordination with a detailed report describing the survey results, which will be helpful in providing more context. The report can be found on the City of Boulder Open Space and Mountain Parks (OSMP) website. Note, open ended comments have been removed from this dataset, consistent with the Open Data Policy.OSMP Master Plan Survey Data (This file): Contains the data (survey responses) for three different surveys: (1) that from the "Scientific Survey," in which a random sample of households were invited to participate, (2) that from an "Open Participation (Opt-In) Survey," an online survey to which all residents were invited, and (3) that from a special effort made to reach Boulder’s Latino population through the promotoras network to invite them to participate (Promotoras). The data field "type" corresponds to the survey type. The files listed below contain supporting information that is necessary to interpret the dataset.OSMP Master Plan Survey - Survey Question Labels This file list the variable names found in the previous csv, and then gives a few words describing what the variable means, with reference to the survey. You will need to refer to "Boulder OSMP Codebook Version A.pdf" for the full name of the survey question being referenced.OSMP Master Plan Survey - Survey Response Option Labels For each variable, the numeric values that are possible, and their associated labels.VERY IMPORTANT NOTE: The scientific survey data were weighted, meaning that the demographic profile of respondents was compared to the demographic profile of adults in Boulder from US Census data. Statistical adjustments were made to bring the respondent profile into balance with the population profile. This means that some records were given more "weight" and some records were given less weight. The weights that were applied are found in the field "wt". If you do not apply these weights, you will not obtain the same results as can be found in the report delivered to the City of Boulder. Please read the Instructions for Working with Survey Weights document for more information.This survey was implemented by Erin Caldwell of the National Research Center, under contract with City of Boulder's Open Space and Mountain Parks Department.Note: The data file contains survey responses from three different surveys. Use the Data column "Type" to distinguish among the surveys. Type=1 is the statistically valid survey, Type=2 is the open participation survey, and Type=3 is the promotoras survey.

The 2017 Coastal Master Plan articulates a clear statement of priorities and focuses development and implementation efforts to achieve comprehensive coastal restoration and protection for Louisiana. Developed using the best available science and engineering, the 2017 Coastal Master Plan focuses our efforts and guides the actions needed to improve the sustainability of our coastal ecosystem, safeguard coastal populations, and protect vital economic and cultural resources. The 2017 Coastal Master Plan is much more than just a plan. It is the guiding document of CPRA and our efforts to protect and restore the Louisiana coast, built on a solid foundation of scientific and engineering principles. The master plan identifies specific actions for addressing land loss and reducing storm surge flooding risks in coastal Louisiana. Predictive models were used to assess coastal change over the next 50 years and to evaluate over 200 restoration and risk reduction projects. This analysis formed the foundation of the plan and led to selection of the projects that provide the greatest return on investment while also considering the constraints of the natural system. To estimate current and future flooding potential, we included a range of storm intensities, sizes, and landfall locations across the coast. This information, along with the relative likelihood of each storm occurring, gave us a rough idea of how flooding could occur across Louisiana’s coast now and over the next 50 years. This data set explores potential current and future flood depths under different environmental scenarios (Low, Medium, and High), as well as future conditions without any further protection and restoration actions versus with implementation of the 2017 Coastal Master Plan at three time steps (year 10, year 25, and year 50).

The 2017 Coastal Master Plan articulates a clear statement of priorities and focuses development and implementation efforts to achieve comprehensive coastal restoration and protection for Louisiana. Developed using the best available science and engineering, the 2017 Coastal Master Plan focuses our efforts and guides the actions needed to improve the sustainability of our coastal ecosystem, safeguard coastal populations, and protect vital economic and cultural resources. The 2017 Coastal Master Plan is much more than just a plan. It is the guiding document of CPRA and our efforts to protect and restore the Louisiana coast, built on a solid foundation of scientific and engineering principles. The master plan identifies specific actions for addressing land loss and reducing storm surge flooding risks in coastal Louisiana. Predictive models were used to assess coastal change over the next 50 years and to evaluate over 200 restoration and risk reduction projects. This analysis formed the foundation of the plan and led to selection of the projects that provide the greatest return on investment while also considering the constraints of the natural system. To estimate current and future flooding potential, we included a range of storm intensities, sizes, and landfall locations across the coast. This information, along with the relative likelihood of each storm occurring, gave us a rough idea of how flooding could occur across Louisiana’s coast now and over the next 50 years. This data set explores potential current and future flood depths under different environmental scenarios (Low, Medium, and High), as well as future conditions without any further protection and restoration actions versus with implementation of the 2017 Coastal Master Plan at three time steps (year 10, year 25, and year 50).

The 2017 Coastal Master Plan articulates a clear statement of priorities and focuses development and implementation efforts to achieve comprehensive coastal restoration and protection for Louisiana. Developed using the best available science and engineering, the 2017 Coastal Master Plan focuses our efforts and guides the actions needed to improve the sustainability of our coastal ecosystem, safeguard coastal populations, and protect vital economic and cultural resources. The 2017 Coastal Master Plan is much more than just a plan. It is the guiding document of CPRA and our efforts to protect and restore the Louisiana coast, built on a solid foundation of scientific and engineering principles. The master plan identifies specific actions for addressing land loss and reducing storm surge flooding risks in coastal Louisiana. Predictive models were used to assess coastal change over the next 50 years and to evaluate over 200 restoration and risk reduction projects. This analysis formed the foundation of the plan and led to selection of the projects that provide the greatest return on investment while also considering the constraints of the natural system. To estimate current and future flooding potential, we included a range of storm intensities, sizes, and landfall locations across the coast. This information, along with the relative likelihood of each storm occurring, gave us a rough idea of how flooding could occur across Louisiana’s coast now and over the next 50 years. This data set explores potential current and future flood depths under different environmental scenarios (Low, Medium, and High), as well as future conditions without any further protection and restoration actions versus with implementation of the 2017 Coastal Master Plan at three time steps (year 10, year 25, and year 50).

City of New Orleans street centerlines. Available on the City of New Orleans ArcGIS Online Data Portal at the above link.The City of New Orleans is moving into the Local Government Information Model, which follows the Federal Geographic Data Commission (FGDC) standards. �Changes to the structure of street names continues as we move to consolidate street name databases from several city agencies. �The names represented here are those found in city ordinances where possible or other references which feature the intended name. �Please understand that the spelling and structure of these names may be significantly different than what you are used to seeing and may not match those currently on street signs displayed by the Department of Public Works.The New Orleans street centerline is a dynamic dataset which changes as our city evolves. �The consolidation of nearly 300 years of records in multiple languages (Spanish, French, English, Native American, Vietnamese, etc) is a difficult task. �We welcome any assistance in getting our historical names correct. �Thank you for your patience as we continue to work toward one master street name inventory.The street centerlines reflect known rights-of-way in the City of New Orleans--improved or not. �While FGDC standards and consolidation needs require a full road name field, we have included an additional field with a CASS certified abbreviated road name. �Some freeway ramps and overpass names remain nonstandard as they may lack a true legal name. �These will be altered as needed.

This layer shows the Cavern Master Plan of Hong Kong. It is a subset of the geo-referenced data made available by the Civil Engineering and Development Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data has been processed and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.