The United States has an average elevation of roughly 2,500 feet (763m) above sea level, however there is a stark contrast in elevations across the country. Highest states Colorado is the highest state in the United States, with an average elevation of 6,800 feet (2,074m) above sea level. The 10 states with the highest average elevation are all in the western region of the country, as this is, by far, the most mountainous region in the country. The largest mountain ranges in the contiguous western states are the Rocky Mountains, Sierra Nevada, and Cascade Range, while the Appalachian Mountains is the longest range in the east - however, the highest point in the U.S. is Denali (Mount McKinley), found in Alaska. Lowest states At just 60 feet above sea level, Delaware is the state with the lowest elevation. Delaware is the second smallest state, behind Rhode Island, and is located on the east coast. Larger states with relatively low elevations are found in the southern region of the country - both Florida and Louisiana have an average elevation of just 100 feet (31m) above sea level, and large sections of these states are extremely vulnerable to flooding and rising sea levels, as well as intermittent tropical storms.

The idea of security in International Relations has for a long time been identified by the vague pursuance of national interests by states. Traditionally, concepts of security focused on the aspect of military protection of a state’s borders and territory. This view has changed over the years to focus on more on human security. The United States (US) foreign policy since the cold war, through the demise of the Soviet Union in the 90s, up to the advent of US unipolarity, has gone through corresponding changes, to guarantee the protection of US citizens at home and abroad. After the September 11 (9/11) terrorist attacks on the US, the Bush administration adopted a pragmatic realist basis of foreign policy. The assumption of power by the Obama administration however ushered in a more progressive liberal tone to US foreign policy in the Middle East. This change in foreign policy approach was expected by the US population, the Iraqi people and the international community, to bring about a matching change in the state of peace and security in the Middle East. The Region has however remained gripped in violent conflict, despite these changes. This study focuses on the effects of the transformation from the Bush administration’s neo-conservative unilateral approach to the Obama administration’s multi-lateral approach in US foreign policy in the Middle East Peace. Focus will be on Iraq between the years 2000-2013. Qualitative research methodology, focusing on documentary search will be the main tool of research in this study. This methodology will be used to explore the underlying principles of US foreign policy in the Middle East which have always been understood to be; safeguarding US access to Middle East oil reserves’, supporting Israel as a strategic ally in the region, prevent any state from dominating the region and spreading of democracy and human rights. This study reflects the view that the prevailing conditions of insecurity in Middle East are despite the diplomatic maneuvers adopted by the Obama administration in US foreign policy. Currently in the Middle East, there is continued sectarian violence in Iraq, the ongoing war in Syria and the continued Israeli-Palestine conflict over the West Bank, is nowhere near a peaceful resolve. This study recommends that any meaningful drive towards peace and security in the Middle East should address the divide on ethnic and sectarian lines as the clashes of these groups are leading to escalating conflict.

New York was the most populous state in the union in the year 1900. It had the largest white population, for both native born and foreign born persons, and together these groups made up over 7.1 million of New York's 7.2 million inhabitants at this time. The United States' industrial centers to the north and northeast were one of the most important economic draws during this period, and states in these regions had the largest foreign born white populations. Ethnic minorities Immigration into the agricultural southern states was much lower than the north, and these states had the largest Black populations due to the legacy of slavery - this balance would begin to shift in the following decades as a large share of the Black population migrated to urban centers to the north during the Great Migration. The Japanese and Chinese populations at this time were more concentrated in the West, as these states were the most common point of entry for Asians into the country. The states with the largest Native American populations were to the west and southwest, due to the legacy of forced displacement - this included the Indian Territory, an unorganized and independent territory assigned to the Native American population in the early 1800s, although this was incorporated into Oklahoma when it was admitted into the union in 1907. Additionally, non-taxpaying Native Americans were historically omitted from the U.S. Census, as they usually lived in separate communities and could not vote or hold office - more of an effort was made to count all Native Americans from 1890 onward, although there are likely inaccuracies in the figures given here. Changing distribution Internal migration in the 20th century greatly changed population distribution across the country, with California and Florida now ranking among the three most populous states in the U.S. today, while they were outside the top 20 in 1900. The growth of Western states' populations was largely due to the wave of internal migration during the Great Depression, where unemployment in the east saw many emigrate to "newer" states in search of opportunity, as well as significant immigration from Latin America (especially Mexico) and Asia since the mid-1900s.

Natural and anthropogenic land use are integral to the climate system and land use change is both a driver of, and responder to changes in climate. The potential for land use and land use change to affect global and regional climate plays a central role in the development of scenarios for greenhouse gas emissions that are used in climate model simulations. Climate models are well suited for exploring interactions with land use and land use change and a number of global and regional modeling studies have investigated past, present, and potential future climate responses induced by land use change. We assess climate responses to the land use change in the Eastern United States and Cuba during four epochs (1650, 1850, 1920, and 1992) with ensemble simulations conducted with the RegCM4 regional climate model. The 8-member ensembles for each land use epoch were driven by perturbing 1990-2002 atmospheric boundary conditions derived from the National Center for Environmental Prediction (NCEP) global reanalysis. The applied version of the model includes the Biosphere Atmosphere Transfer Scheme (BATS1e) surface physics package. We derived the land use data sets by harmonizing a previous reconstruction with updated observations and modeled potential vegetation.

World Elevation layers are compiled from many authoritative data providers, and are updated quarterly. This map shows the extent of the various datasets comprising the World Elevation dynamic (Terrain, TopoBathy) and tiled (Terrain 3D, TopoBathy 3D, World Hillshade, World Hillshade (Dark)) services.The tiled services (Terrain 3D, TopoBathy 3D, World Hillshade, World Hillshade (Dark)) also include an additional data source from Maxar's Precision3D covering parts of the globe.Topography sources listed in the table below are part of Terrain, TopoBathy, Terrain 3D, TopoBathy 3D, World Hillshade and World Hillshade (Dark), while bathymetry sources are part of TopoBathy and TopoBathy 3D only. Data Source Native Pixel Size Approximate Pixel Size (meters) Coverage Primary Source Country/Region

Topography

Australia 1m 1 meter 1 Partial areas of Australia Geoscience Australia Australia

Moreton Bay, Australia 1m 1 meter 1 Moreton Bay region, Australia Moreton Bay Regional Council Australia

New South Wales, Australia 5m 5 meters 5 New South Wales State, Australia DFSI Australia

SRTM 1 arc second DEM-S 0.0002777777777779 degrees 31 Australia Geoscience Australia Australia

Burgenland 50cm 0.5 meters 0.5 Burgenland State, Austria Land Burgenland Austria

Upper Austria 50cm 0.5 meters 0.5 Upper Austria State, Austria Land Oberosterreich Austria

Austria 1m 1 meter 1 Austria BEV Austria

Austria 10m 10 meters 10 Austria BEV Austria

Wallonie 50cm 0.5 meters 0.5 Wallonie state, Belgium Service public de Wallonie (SPW) Belgium

Vlaanderen 1m 1 meter 1 Vlaanderen state, Belgium agentschap Digitaal Vlaanderen Belgium

Canada HRDEM 1m 1 meter 1 Partial areas of Canada Natural Resources Canada Canada

Canada HRDEM 2m 2 meter 2 Partial areas of the southern part of Canada Natural Resources Canada Canada

Denmark 40cm 0.4 meters 0.4 Denmark KDS Denmark

Denmark 10m 10 meters 10 Denmark KDS Denmark

England 1m 1 meter 1 England Environment Agency England

Estonia 1m 1 meter 1 Estonia Estonian Land Board Estonia

Estonia 5m 5 meters 5 Estonia Estonian Land Board Estonia

Estonia 10m 10 meters 10 Estonia Estonian Land Board Estonia

Finland 2m 2 meters 2 Finland NLS Finland

Finland 10m 10 meters 10 Finland NLS Finland

France 1m 1 meter 1 France IGN-F France

Bavaria 1m 1 meter 1 Bavaria State, Germany Bayerische Vermessungsverwaltung Germany

Berlin 1m 1 meter 1 Berlin State, Germany Geoportal Berlin Germany

Brandenburg 1m 1 meter 1 Brandenburg State, Germany GeoBasis-DE/LGB Germany

Hamburg 1m 1 meter 1 Hamburg State, Germany LGV Hamburg Germany

Hesse 1m 1 meter 1 Hesse State, Germany HVBG Germany

Nordrhein-Westfalen 1m 1 meter 1 Nordrhein-Westfalen State, Germany Land NRW Germany

Saxony 1m 1 meter 1 Saxony State, Germany Landesamt für Geobasisinformation Sachsen (GeoSN) Germany

Sachsen-Anhalt 2m 2 meters 2 Sachsen-Anhalt State, Germany LVermGeo LSA Germany

Hong Kong 50cm 0.5 meters 0.5 Hong Kong CEDD Hong Kong SAR

Italy TINITALY 10m 10 meters 10 Italy INGV Italy

Japan DEM5A *, DEM5B * 0.000055555555 degrees 5 Partial areas of Japan GSI Japan

Japan DEM10B * 0.00011111111 degrees 10 Japan GSI Japan

Latvia 1m 1 meters 1 Latvia Latvian Geospatial Information Agency Latvia

Latvia 10m 10 meters 10 Latvia Latvian Geospatial Information Agency Latvia

Latvia 20m 20 meters 20 Latvia Latvian Geospatial Information Agency Latvia

Lithuania 1m 1 meters 1 Lithuania NZT Lithuania

Lithuania 10m 10 meters 10 Lithuania NZT Lithuania

Netherlands (AHN3/AHN4) 50cm 0.5 meters 0.5 Netherlands AHN Netherlands

Netherlands (AHN3/AHN4) 10m 10 meters 10 Netherlands AHN Netherlands

New Zealand 1m 1 meters 1 Partial areas of New Zealand Land Information New Zealand (Sourced from LINZ. CC BY 4.0) New Zealand

Northern Ireland 10m 10 meters 10 Northern Ireland OSNI Northern Ireland

Norway 10m 10 meters 10 Norway NMA Norway

Poland 1m 1 meter 1 Partial areas of Poland GUGIK Poland

Poland 5m 5 meters 5 Partial areas of Poland GUGIK Poland

Scotland 1m 1 meter 1 Partial areas of Scotland Scottish Government et.al Scotland

Slovakia 1m 1 meter 1 Slovakia ÚGKK SR Slovakia

Slovakia 10m 10 meters 10 Slovakia GKÚ Slovakia

Slovenia 1m 1 meter 1 Slovenia ARSO Slovenia

Madrid City 1m 1 meter 1 Madrid city, Spain Ayuntamiento de Madrid Spain

Spain 2m (MDT02 2019 CC-BY 4.0 scne.es) 2 meters 2 Partial areas of Spain IGN Spain

Spain 5m 5 meters 5 Spain IGN Spain

Spain 10m 10 meters 10 Spain IGN Spain

Varnamo 50cm 0.5 meters 0.5 Varnamo municipality, Sweden Värnamo Kommun Sweden

Canton of Basel-Landschaft 25cm 0.25 meters 0.25 Canton of Basel-Landschaft, Switzerland Geoinformation Kanton Basel-Landschaft Switzerland

Grand Geneva 50cm 0.5 meters 0.5 Grand Geneva metropolitan, France/Switzerland SITG Switzerland and France

Switzerland swissALTI3D 50cm 0.5 meters 0.5 Switzerland and Liechtenstein swisstopo Switzerland and Liechtenstein

Switzerland swissALTI3D 10m 10 meters 10 Switzerland and Liechtenstein swisstopo Switzerland and Liechtenstein

OS Terrain 50 50 meters 50 United Kingdom Ordnance Survey United Kingdom

Douglas County 1ft 1 foot 0.3048 Douglas County, Nebraska, USA Douglas County NE United States

Lancaster County 1ft 1 foot 0.3048 Lancaster County, Nebraska, USA Lancaster County NE United States

Sarpy County 1ft 1 foot 0.3048 Sarpy County, Nebraska, USA Sarpy County NE United States

Cook County 1.5 ft 1.5 foot 0.46 Cook County, Illinois, USA ISGS United States

3DEP 1m 1 meter 1 Partial areas of the conterminous United States, Puerto Rico USGS United States

NRCS 1m 1 meter 1 Partial areas of the conterminous United States NRCS USDA United States

San Mateo County 1m 1 meter 1 San Mateo County, California, USA San Mateo County CA United States

FEMA LiDAR DTM 3 meters 3 Partial areas of the conterminous United States FEMA United States

NED 1/9 arc second 0.000030864197530866 degrees 3 Partial areas of the conterminous United States USGS United States

3DEP 5m 5 meter 5 Alaska, United States USGS United States

NED 1/3 arc second 0.000092592592593 degrees 10 conterminous United States, Hawaii, Alaska, Puerto Rico, and Territorial Islands of the United States USGS United States

NED 1 arc second 0.0002777777777779 degrees 31 conterminous United States, Hawaii, Alaska, Puerto Rico, Territorial Islands of the United States; Canada and Mexico USGS United States

NED 2 arc second 0.000555555555556 degrees 62 Alaska, United States USGS United States

Wales 1m 1 meter 1 Wales Welsh Government Wales

WorldDEM4Ortho 0.00022222222 degrees 24 Global (excluding the countries of Azerbaijan, DR Congo and Ukraine) Airbus Defense and Space GmbH World

SRTM 1 arc second 0.0002777777777779 degrees 31 all land areas between 60 degrees north and 56 degrees south except Australia NASA World

EarthEnv-DEM90 0.00083333333333333 degrees 93 Global N Robinson,NCEAS World

SRTM v4.1 0.00083333333333333 degrees 93 all land areas between 60 degrees north and 56 degrees south except Australia CGIAR-CSI World

GMTED2010 7.5 arc second 0.00208333333333333 degrees 232 Global USGS World

GMTED2010 15 arc second 0.00416666666666666 degrees 464 Global USGS World

GMTED2010 30 arc second 0.0083333333333333 degrees 928 Global USGS World

Bathymetry

Bass Strait 30m 2022 0.0003 degrees 30 area of seabed between the coastlines of Victoria and northern Tasmania, extending approximately 460 km from west of King Island to east of Flinders Island. Geoscience Australia Australia

AusBathyTopo 2024 0.0025 degrees 250 Australian continent and Tasmania, and surrounding Macquarie Island and the Australian Territories of Norfolk Island, Christmas Island, and Cocos (Keeling) Islands. Geoscience Australia Australia

Canada west coast 10 meters 10 Canada west coast Natural Resources Canada Canada

Gulf of Mexico 40 feet 12 Northern Gulf of Mexico BOEM Gulf of Mexico

MH370 150 meters 150 MH370 flight search area (Phase 1) of Indian Ocean Geoscience Australia Indian Ocean

Switzerland swissBATHY3D 1 - 3 meters 1, 2, 3 Lakes of Switzerland swisstopo Switzerland

NCEI 1/9 arc second 0.000030864197530866 degrees 3 Puerto Rico, U.S Virgin Islands and partial areas of eastern and western United States coast NOAA NCEI United States

NCEI 1/3 arc second 0.000092592592593 degrees 10 Partial areas of eastern and western United States

This sampling frame is a set of grid-based finite-area frames spanning Canada, the United States, and Mexico. The grid for the United States is broken into individual grids for the continental United States, Hawaii, and Puerto Rico. Alaska is combined with Canada into a single grid. Each country/state/territory extent consists of four nested sampling grids at 50x50km, 10x10km, 5x5km, and 1x1km resolutions. The original 10x10km continental United States grid was developed by the Forest Service, U.S. Department of Agriculture for use in the interagency "Bat Grid" monitoring program in the Pacific Northwest and was expanded program in the Pacific Northwest and was expanded across Canada, the United States, and Mexico for the North American Bat Monitoring Program (NABat). Additional grids for Hawaii and Puerto Rico were created for this data release. This vector dataset is the individual grid-based sampling grid for Alaska and Canada at a 1x1km resolution. Because of the resulting size of this dataset the 1km sampling grid for Alaska and Canada was split into a western and eastern half.

This data was created to depict portions of state-owned Sovereign Lands that are under the jurisdiction of the California State Lands Commission. Data coverage is currently limited to reaches 1A, 4A and 4B1 of the San Joaquin River.

The California State Lands Commission (CSLC) was created by the California Legislature in 1938 and given the authority and responsibility to manage certain public lands within the state. The public lands under the Commission’s jurisdiction are of two distinct types—sovereign lands acquired upon California’s admission into the Union in 1850; and certain federally granted lands including school lands, and swamp and overflowed lands. For purposes of this GIS data, sovereign lands are considered to be further divided into two general categories—fixed-boundary sovereign lands and ambulatory-boundary sovereign lands.

The following lands are included in this data:

· Portions of the ambulatory-boundary for state sovereign lands at a specific point in time, for portions of the San Joaquin River.

NOT INCLUDED IN THIS DATA:

· School lands: These are what remains of nearly 5.5 million acres throughout the state originally granted to California by Congress in 1853 to benefit public education.

· Fixed-boundary sovereign lands: These are sovereign, public trust lands having fixed boundaries as the result of land exchanges, boundary line agreements or court orders.

· Swamps and overflowed lands: These are what remain of federal lands granted to California by Congress in 1850 to encourage reclamation and development of agricultural lands.

ALSO NOT INCLUDED IN THIS DATA: Ownership details within the U.S. Government meanders of Owens Lake.

THIS DATA SUPERSEDES all previously published GIS information with respect to the above described state-owned lands under the jurisdiction of the CSLC.

This polyline feature class represents the arc features that will define the boundaries of the Bureau of Land Management (BLM) Eastern States (ES) Land Use Planning Areas (LUPA) polygons. Land Use Planning Areas are geographic areas within which the BLM makes decisions during land use planning efforts.

Analysis of ‘NNDSS - TABLE 1A. Anthrax to Arboviral diseases, Eastern equine encephalitis virus disease’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/7332d823-f023-4749-941c-f94b3d20d196 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

NNDSS - TABLE 1A. Anthrax to Arboviral diseases, Eastern equine encephalitis virus disease – 2021. In this Table, provisional cases* of notifiable diseases are displayed for United States, U.S. territories, and Non U.S. residents.

Notice: Due to data processing issues at CDC, data for the following jurisdictions may be incomplete for week 7: Alaska, Arizona, California, Connecticut, Delaware, Florida, Hawaii, Louisiana, Maryland, Michigan, Missouri, North Dakota, New Hampshire, New York City, Oregon, Pennsylvania, and Rhode Island.

Note: This table contains provisional cases of national notifiable diseases from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data from the 50 states, New York City, the District of Columbia and the U.S. territories are collated and published weekly on the NNDSS Data and Statistics web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html.

Footnotes: U: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data. -: No reported cases — The reporting jurisdiction did not submit any cases to CDC. N: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction. NN: Not nationally notifiable — This condition was not designated as being nationally notifiable. NP: Nationally notifiable but not published. NC: Not calculated — There is insufficient data available to support the calculation of this statistic. Cum: Cumulative year-to-date counts. Max: Maximum — Maximum case count during the previous 52 weeks. * Case counts for reporting years 2020 and 2021 are provisional and subject to change. Cases are assigned to the reporting jurisdiction submitting the case to NNDSS, if the case's country of usual residence is the U.S., a U.S. territory, unknown, or null (i.e. country not reported); otherwise, the case is assigned to the 'Non-U.S. Residents' category. Country of usual residence is currently not reported by all jurisdictions or for all conditions. For further information on interpretation of these data, see https://wwwn.cdc.gov/nndss/document/Users_guide_WONDER_tables_cleared_final.pdf. †Previous 52 week maximum and cumulative YTD are determined from periods of time when the condition was reportable in the jurisdiction (i.e., may be less than 52 weeks of data or incomplete YTD data).

--- Original source retains full ownership of the source dataset ---

The Public Land spatial data sets (shapefile) contains Public Land Survey section polygons that had mining claims recorded in the U.S. Bureau of Land Management's LR2000 database as of December 31, 2010 (from a March 1, 2011 data extraction) for the period from 1976 to 2010 in Arizona, Arkansas, California, Colorado, Florida, Idaho, Montana, Nebraska, New Mexico, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, and Wyoming. Alaska was not updated in version 4.

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

In 2023, California had the highest Hispanic population in the United States, with over 15.76 million people claiming Hispanic heritage. Texas, Florida, New York, and Illinois rounded out the top five states for Hispanic residents in that year. History of Hispanic people Hispanic people are those whose heritage stems from a former Spanish colony. The Spanish Empire colonized most of Central and Latin America in the 15th century, which began when Christopher Columbus arrived in the Americas in 1492. The Spanish Empire expanded its territory throughout Central America and South America, but the colonization of the United States did not include the Northeastern part of the United States. Despite the number of Hispanic people living in the United States having increased, the median income of Hispanic households has fluctuated slightly since 1990. Hispanic population in the United States Hispanic people are the second-largest ethnic group in the United States, making Spanish the second most common language spoken in the country. In 2021, about one-fifth of Hispanic households in the United States made between 50,000 to 74,999 U.S. dollars. The unemployment rate of Hispanic Americans has fluctuated significantly since 1990, but has been on the decline since 2010, with the exception of 2020 and 2021, due to the impact of the coronavirus (COVID-19) pandemic.

Agricultural land cover for the western United States. This dataset was developed from Sagestitch, the Eastern Washington Shrubsteppe Mapping Project, and several state level GAP products (AZ, CA, NM, OR, and WA).

Spatial information about the seafloor is critical for decision-making by marine resource science, management and tribal organizations. Coordinating data needs can help organizations leverage collective resources to meet shared goals. To help enable this coordination, the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) developed a spatial framework, process and online application to identify common data collection priorities for seafloor mapping, sampling and visual surveys off the US Caribbean territories of Puerto Rico and the US Virgin Islands. Fifteen participants from local federal, state, and academic institutions entered their priorities in an online application, using virtual coins to denote their priorities in 2.5x2.5 kilometer (nearshore) and 10x10 kilometer (offshore) grid size. Grid cells with more coins were higher priorities than cells with fewer coins. Participants also reported why these locations were important and what data types were needed. Results were analyzed and mapped using statistical techniques to identify significant relationships between priorities, reasons for those priorities and data needs. Fifteen high priority locations were broadly identified for future mapping, sampling and visual surveys. These locations include: (1) a coastal location in northwest Puerto Rico (Punta Jacinto to Punta Agujereada), (2) a location approximately 11 km off Punta Agujereada, (3) coastal Rincon, (4) San Juan, (5) Punta Arenas (west of Vieques Island), (6) southwest Vieques, (7) Grappler Seamount, (8) southern Virgin Passage, (9) north St. Thomas, (10) east St. Thomas, (11) south St. John, (12) west offshore St. Croix, (13) west nearshore St. Croix, (14) east nearshore St. Croix, and (15) east offshore St. Croix. Participants consistently selected (1) Biota/Important Natural Area, (2) Commercial Fishing and (3) Coastal/Marine Hazards as their top reasons (i.e., justifications) for prioritizing locations, and (1) Benthic Habitat Map and (2) Sub-bottom Profiles as their top data or product needs. This ESRI shapefile summarizes the results from this spatial prioritization effort. This information will enable US Caribbean organization to more efficiently leverage resources and coordinate their mapping of high priority locations in the region.

This effort was funded by NOAA’s NCCOS and supported by CRCP. The overall goal of the project was to systematically gather and quantify suggestions for seafloor mapping, sampling and visual surveys in the US Caribbean territories of Puerto Rico and the US Virgin Islands. The results are will help organizations in the US Caribbean identify locations where their interests overlap with other organizations, to coordinate their data needs and to leverage collective resources to meet shared goals.

There were four main steps in the US Caribbean spatial prioritization process. The first step was to identify the technical advisory team, which included the 4 CRCP members: 2 from each the Puerto Rico and USVI regions. This advisory team recommended 33 organizations to participate in the prioritization. Each organization was then requested to designate a single representative, or respondent, who would have access to the web tool. The respondent would be responsible for communicating with their team about their needs and inputting their collective priorities. Step two was to develop the spatial framework and an online application. To do this, the US Caribbean was divided into 4 sub regions: nearshore and offshore for both Puerto Rico and USVI. The total inshore regions had 2,387 square grid cells approximately 2.5x2.5 km in size. The total offshore regions consisted of 438 square grid cells 10x10 km in size. Existing relevant spatial datasets (e.g., bathymetry, protected area boundaries, etc.) were compiled to help participants understand information and data gaps and to identify areas they wanted to prioritize for future data collections. These spatial datasets were housed in the online application, which was developed using Esri’s Web AppBuilder. In step three, this online application was used by 15 participants to enter their priorities in each subregion of interest. Respondents allocated virtual coins in the grid cells to denote their priorities for each region. Respondents were given access to all four regions, despite which territory they represented, but were not required to provide input into each region. Grid cells with more coins were higher priorities than cells with fewer coins. Participants also reported why these locations were important and what data types were needed. Coin values were standardized across the nearshore and offshore zones and used to identify spatial patterns across the US Caribbean region as a whole. The number of coins were standardized because each subregion had a different number of grid cells and participants. Standardized coin values were analyzed and mapped using statistical techniques, including hierarchical cluster analysis, to identify significant relationships between priorities, reasons for those priorities and data needs. This ESRI shapefile contains the 2.5x2.5 km and 10x10 km grid cells used in this prioritization effort and associated the standardized coin values overall, as well as by organization, justification and product. For a complete description of the process and analysis please see: Kraus et al. 2020.

We have taken the Uso del Suelo y Vegetacion land cover classification products for Mexico (courtesy of Mexico's Instituto Nacional de Estadistica y Geografia, or INEGI) for years 1985, 1993, 2002, 2007, and 2011 (INEGI, 2015); harmonized their classes with the classes of the Multi-Resolution Land Characteristics Consortium (MRLC) National Land Cover Database (NLCD) (Homer et al., 2015), and merged the two datasets to form a single land cover product covering the continental US and Mexico, for years 1992/3, 2001/2, and 2011. Details of processing, along with the processing scripts, are archived in GitHub in the NLCD_INEGI project (Bohn, 2019).

Output files are ESRI ascii-format raster files, geographic projection, 0.000350884 degree cellsize. Each file contains a 1x1 degree box or "tile", named nlcd_inegi.lat0_lat1n.lon0_lon1w.asc, where lat0 and lat1 are the south and north boundaries of the box and lon0 and lon1 are the west and east boundaries (west = positive).

This project contains the following g-zipped tar files:

• 1992.tgz - land cover from 1992 (NLCD) and 1993 (INEGI)
• 2001.tgz - land cover from 2001 (NLCD) and 2002 (INEGI)
• 2011.tgz - land cover from 2011 (both NLCD and INEGI)
• stable_2001-2011.tgz - land cover from those pixels that had the same class in 2001 and 2011 ("stable" pixels)

On LINUX, the contents of these files can be extracted via "tar":

tar -xvzf 1992.tgz >& log.tar.txt

On Windows, applications such as "7-zip" can extract the contents.

Each of these .tgz files contain a folder with the same name but without the ".tgz". Within each of these folders is a sub-folder called "asc.clip.1deg". This folder contains the 1x1 tiles.

Meeting increasing future electricity demand in the United States will require extensive and explorative planning due to advancing climatic, socioeconomic, and decarbonization policy drivers. Accounting for the response of changes in these drivers on the energy system are made even more complex when considering them in aggregate form with regionally relevant land and technology constraints that narrow where power plants capable of supporting increasing demand will be feasible to operate under uncertain futures. We offer the Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package as a high-resolution product to readily evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States for alternative energy futures. GRIDCERF provides 269 suitability layers for use with 56 power plant technology configurations in a harmonized format readily ingestible by geospatially-enabled modeling software. GRIDCERF comes equipped with pre-compiled technology-specific suitability layers but also allows for user customization to robustly address science objectives when evaluating varying future conditions.

Contents:

Common Rasters:

Suitability Layer	GRIDCERF Raster Name
Agricultural Research Service Lands33	gridcerf_ars_lands_2020_conus.tif
Bureau of Indian Affairs (BIA) Land Area Representation Dataset34	cerf_bia_tribal_lands_2019.tif
Bureau of Land Management (BLM) National Landscape Conservation System (NLCS) - National Monuments35	gridcerf_blm_nlcs_national_monument_2021_conus.tif
BLM NLCS - Outstanding Natural Areas36	gridcerf_blm_nlcs_outstanding_natural_areas_2017_conus.tif
BLM NLCS - Trails Historic West37	gridcerf_blm_nlcs_trails_historic_west_buff_1km_2019_conus.tif
BLM NLCS System - Trails Scenic East37	gridcerf_blm_nlcs_trails_scenic_east_buff_1km_2019_conus.tif
BLM NLCS System – Wilderness38	gridcerf_blm_nlcs_wilderness_2021_conus.tif
BLM NLCS - Wilderness Study Areas38	gridcerf_blm_nlcs_wilderness_study_areas_2021_conus.tif
BLM NLCS - Scenic Rivers39	gridcerf_blm_scenic_rivers_1km_2009_conus.tif
National Park Service (NPS) Class 1 airsheds40	gridcerf_class1_airsheds_2015_conus.tif
BLM NLCS National Conservation Areas35	gridcerf_cons_monu_desig_2021_conus.tif
U.S. Fish and Wildlife Service (USFWS) - Critical Habitat41	gridcerf_fws_critical_habitat_2019_conus.tif
USFWS - Land Interests42	gridcerf_fws_land_interests_2019_conus.tif
USFWS - Lands43	gridcerf_fws_lands_2021_conus.tif
USFWS - National Wildlife Refuges42	gridcerf_fws_national_wildlife_refuges_2019_conus.tif
USFWS - Special Designation42	gridcerf_fws_special_designation_2019_conus.tif
National Land Cover Dataset (NLCD) Wetlands44	gridcerf_nlcd_wetlands_1km_2019_conus.tif
NPS Administrative Boundaries45	gridcerf_nps_administrative_boundaries_2020_conus.tif
NPS Lands46	gridcerf_nps_lands_2019_conus.tif
BLM NLCS - Wild & Scenic Rivers39	gridcerf_nwrs_buff_1km_2021_conus.tif
U.S. Forest Service (USFS) Administrative Boundaries47	gridcerf_usfs_administrative_boundaries_2021_conus.tif
USFS lands43	gridcerf_usfs_lands_2021_conus.tif
U.S. Geological Survey (USGS) National Wilderness Lands48	gridcerf_wilderness_lands_2021_conus.tif
USGS Protected Areas of the U.S - Class 1&249	gridcerf_usgs_padus_class_1_to_2_2018_conus.tif
U.S. State Protected Lands50	gridcerf_wdpa_state_protected_lands_2021_conus.tif
Nature Conservancy lands51	gridcerf_wdpa_tnc_managed_lands_2016_conus.tif
USFS Wilderness Areas52	gridcerf_usfs_wilderness_ares_2015_conus.tif

Technology-specific Rasters:

Suitability Layer	GRIDCERF Raster Name
Slope 10% or less suitable22	gridcerf_srtm_slope_5pct_or_less.tif
Slope 10% or less suitable22	gridcerf_srtm_slope_10pct_or_less.tif
Slope 12% or less suitable22	gridcerf_srtm_slope_12pct_or_less.tif
Slope 20% or less suitable22	gridcerf_srtm_slope_20pct_or_less.tif
Airports (10-mile buffer)53	gridcerf_airports_10mi_buffer_conus.tif
Airports (3-mile buffer)53	gridcerf_airports_3mi_buffer_conus.tif
Proximity to Railroad and Navigable Waters (< 5 km)54,55	gridcerf_railnodes5km_navwaters5km_conus.tif
Coal Supply54–56	gridcerf_coalmines20km_railnodes5km_navwaters5km_conus.tif
NTAD CO Non-attainment Areas57	gridcerf_naa_co_1km_2013_conus.tif
NTAD NOx Non-attainment Areas57	gridcerf_naa_nox_1km_2013_conus.tif
NTAD Ozone Non-attainment Areas57	gridcerf_naa_ozone_1km_2018_conus.tif
NTAD Lead Non-attainment Areas57	gridcerf_naa_pb_1km_2017_conus.tif
NTAD PM10 Non-attainment Areas57	gridcerf_naa_pm10_1km_2013_conus.tif
NTAD PM2.5 Non-attainment Areas57	gridcerf_naa_pm25_1km_2016_conus.tif
NTAD SOx Non-attainment Areas57	gridcerf_naa_sox_1km_2021_conus.tif
Earthquake Potential58	gridcerf_earthquake_pga_0.3g_at_2pct_in_50yrs_2016_conus.tif
Densely population areas12	gridcerf_densely_populated_ssp[2,3,5]_[year].tif
Densely population areas buffered by 25 miles12	gridcerf_densely_populated_ssp[2,3,5]_[year]_buff25mi.tif
Densely population areas – nuclear12	gridcerf_densely_populated_ssp[2,3,5]_[year]_nuclear.tif
National Hydrography Dataset (version 2;

At 20,310 feet (6.2km) above sea level, the highest point in the United States is Denali, Alaska (formerly known as Mount McKinley). The highest point in the contiguous United States is Mount Whitney, in the Sierra Nevada mountain range in California; followed by Mount Elbert, Colorado - the highest point in the Rocky Mountains. When looking at the highest point in each state, the 13 tallest peaks are all found in the western region of the country, while there is much more diversity across the other regions and territories.

Despite being approximately 6,500 feet lower than Denali, Hawaii's Mauna Kea is sometimes considered the tallest mountain (and volcano) on earth. This is because its base is well below sea level - the mountain has a total height of 33,474 feet, which is almost 4,500 feet higher than Mount Everest.

21 of the 50 U.S. states have been the birthplace of U.S. presidents. Historically, Virginia has been the most common birthplace of U.S. presidents, with eight in total; although seven of these were born in the 1700s, and Woodrow Wilson is the most recent Virginian to have been elected president, in 1912. Similarly to Virginia, Ohio has produced seven U.S. presidents, although they were all born between 1822 and 1865, and all served as president between 1845 and 1923. Born in the USA Five presidents, including the incumbent President Donald Trump, were born in New York; the first of which, Martin Van Buren, also has the distinction of being the first president born in the independent United States. Eight of the first nine presidents, all born in Massachusetts, South Carolina or Virginia, were born as British subjects when these states were still part of the Thirteen Colonies. Since then, no other presidents were born in areas that had not yet been admitted into the United States, and no U.S. presidents were ever born in the Confederate States of America, a U.S. territory or any foreign country. The U.S. Constitution includes the "natural-born-citizen clause", which is generally understood to mean that only those born in the U.S. may be elected to the office of president or vice president; however, the exact meaning of the phrase "natural-born-citizen" has never been finally clarified and remains open to interpretation. Increasing variety With President Joe Biden's victory in the 2020 election, he became just the second president to have been born in Pennsylvania (the other being James Buchanan). Today, there have been 13 states which were the birthplace of just one president, and, apart from Biden, Donald Trump and George H. W. Bush, seven of the most recent ten presidents were born in these states. Barack Obama is the only U.S. president not to have been born on the U.S. mainland, as he was born in Honolulu, Hawaii, in 1961. There are 29 states, along with the District of Columbia, that are yet to produce a U.S. president.

This dataset includes high quality (800 Dots Per Inch - DPI), 24 bit color images of Minnesota's original Public Land Survey (PLS) plats created during the first government land survey of the state from 1848 to 1907. Currently housed at the Office of the Secretary of State, these plats were created by the U.S. Surveyor General's Office. This collection of more than 3,600 maps also includes later General Land Office (GLO) and the Bureau of Land Management (BLM) maps - up to the year 2001.

Minnesota's survey plat maps serve as the fundamental legal records for real estate in the state; all property titles and descriptions stem from them. They also serve as an essential resource for surveyors and as an analytical tool for the state's physical geography prior to European settlement. Finally, they serve as a testimony to years and years of hard work by the surveying community, often under challenging conditions.

In recent years the deteriorating physical condition of the older maps and the needs of technologically more sophisticated researchers, who require access to the maps, have made handling the original paper records increasingly less practical. To meet this challenge, the Office of the Secretary of State, the State Archives of the Minnesota Historical Society, the Minnesota Department of Transportation, MnGeo (formerly the Land Management Information Center - LMIC) and the Minnesota Association of County Surveyors collaborated in a digitization project which produced images of the maps in standard TIFF, JPEG and PDF formats - nearly 1.5 terabytes worth of data. Funding was provided by the Minnesota Department of Transportation.

This map shows the extents of the various datasets comprising the World Elevation dynamic (Terrain, TopoBathy) and tiled (Terrain 3D, TopoBathy 3D, World Hillshade, World Hillshade (Dark)) services.The map has pop-ups defined. Click anywhere on the map to reveal details about the data sources.Topography sources listed in the table below are part of Terrain, TopoBathy, Terrain 3D, TopoBathy 3D, World Hillshade and World Hillshade (Dark), while bathymetry sources are part of TopoBathy and TopoBathy 3D only. Data Source Native Pixel Size Approximate Pixel Size (meters) Coverage Primary Source Country/Region

Topography

Australia 1m 1 meter 1 Partial areas of Australia Geoscience Australia Australia

Moreton Bay, Australia 1m 1 meter 1 Moreton Bay region, Australia Moreton Bay Regional Council Australia

New South Wales, Australia 5m 5 meters 5 New South Wales State, Australia DFSI Australia

SRTM 1 arc second DEM-S 0.0002777777777779 degrees 31 Australia Geoscience Australia Australia

Burgenland 50cm 0.5 meter 0.5 Burgenland State, Austria Land Burgenland Austria

Upper Austria 50cm 0.5 meter 0.5 Upper Austria State, Austria Land Oberosterreich Austria

Austria 1m 1 meter 1 Austria BEV Austria

Austria 10m 10 meters 10 Austria Geoland Austria

Canada HRDEM 1m 1 meter 1 Partial areas of the southern part of Canada Natural Resources Canada Canada

Canada HRDEM 2m 2 meters 2 Partial areas of the southern part of Canada Natural Resources Canada Canada

Denmark 40cm 0.4 meter 0.4 Denmark SDFE Denmark

Denmark 10m 10 meters 10 Denmark SDFE Denmark

England 2m 2 meters 2 70 % of England Environment Agency England

Estonia 1m 1 meter 1 Estonia Estonian Land Board Estonia

Estonia 5m 5 meters 5 Estonia Estonian Land Board Estonia

Estonia 10m 10 meters 10 Estonia Estonian Land Board Estonia

Finland 2m 2 meters 2 Finland NLS Finland

Finland 10m 10 meters 10 Finland NLS Finland

Berlin 1m 1 meter 1 Berlin State, Germany Geoportal Berlin Germany

Hamburg 1m 1 meter 1 Hamburg State, Germany LGV Hamburg Germany

Nordrhein-Westfalen 1m 1 meter 1 Nordrhein-Westfalen State, Germany Land NRW Germany

Sachsen-Anhalt 2m 2 meters 2 Sachsen-Anhalt State, Germany LVermGeo LSA Germany

Hong Kong 50cm 0.5 meter 0.5 Hong Kong CEDD Hong Kong SAR

Italy TINITALY 10m 10 meters 10 Italy INGV Italy

Japan DEM5A *, DEM5B * 0.000055555555 degrees 5 Partial areas of Japan GSI Japan

Japan DEM10B * 0.00011111111 degrees 10 Japan GSI Japan

Latvia 1m 1 meter 1 Latvia Latvian Geospatial Information Agency Latvia

Latvia 10m 10 meters 10 Latvia Latvian Geospatial Information Agency Latvia

Latvia 20m 20 meters 20 Latvia Latvian Geospatial Information Agency Latvia

Lithuania 1m 1 meter 1 Lithuania NZT Lithuania

Lithuania 10m 10 meters 10 Lithuania NZT Lithuania

Netherlands (AHN3/AHN4) 50cm 0.5 meter 0.5 Netherlands AHN Netherlands

Netherlands (AHN3/AHN4) 10m 10 meters 10 Netherlands AHN Netherlands

New Zealand 1m 1 meter 1 Partial areas of New Zealand Land Infromation New Zealand (Sourced from LINZ. CC BY 4.0) New Zealand

Northern Ireland 10m 10 meters 10 Northern Ireland OSNI Northern Ireland

Norway 10m 10 meters 10 Norway NMA Norway

Poland 1m 1 meter 1 Partial areas of Poland GUGIK Poland

Poland 5m 5 meters 5 Partial areas of Poland GUGIK Poland

Scotland 1m 1 meter 1 Partial areas of Scotland Scottish Government et.al Scotland

Slovakia 10m 10 meters 10 Slovakia GKÚ Slovakia

Slovenia 1m 1 meter 1 Slovenia ARSO Slovenia

Madrid City 1m 1 meter 1 Madrid city, Spain Ayuntamiento de Madrid Spain

Spain 2m (MDT02 2019 CC-BY 4.0 scne.es) 2 meters 2 Partial areas of Spain IGN Spain

Spain 5m 5 meters 5 Spain IGN Spain

Spain 10m 10 meters 10 Spain IGN Spain

Varnamo 50cm 0.5 meter 0.5 Varnamo municipality, Sweden Värnamo Kommun Sweden

Canton of Basel-Landschaft 25cm 0.25 meter 0.25 Canton of Basel-Landschaft, Switzerland Geoinformation Kanton Basel-Landschaft Switzerland

Grand Geneva 50cm 0.5 meter 0.5 Grand Geneva metropolitan, France/Switzerland SITG Switzerland and France

Switzerland swissALTI3D 50cm 0.5 meter 0.5 Switzerland and Liechtenstein swisstopo Switzerland and Liechtenstein

Switzerland swissALTI3D 10m 10 meters 10 Switzerland and Liechtenstein swisstopo Switzerland and Liechtenstein

OS Terrain 50 50 meters 50 United Kingdom Ordnance Survey United Kingdom

3DEP 1m 1 meter 1 Partial areas of the conterminous United States, Puerto Rico USGS United States

NRCS 1m 1 meter 1 Partial areas of the conterminous United States NRCS USDA United States

FEMA LiDAR DTM 3 meters 3 Partial areas of the conterminous United States FEMA United States

NED 1/9 arc second 0.000030864197530866 degrees 3 Partial areas of the conterminous United States USGS United States

3DEP 5m 5 meters 5 Alaska, United States USGS United States

NED 1/3 arc second 0.000092592592593 degrees 10 conterminous United States, Hawaii, Alaska, Puerto Rico, and Territorial Islands of the United States USGS United States

NED 1 arc second 0.0002777777777779 degrees 31 conterminous United States, Hawaii, Alaska, Puerto Rico, Territorial Islands of the United States; Canada and Mexico USGS United States

NED 2 arc second 0.000555555555556 degrees 62 Alaska, United States USGS United States

Wales 2m 2 meters 2 70 % of Wales Natural Resources Wales Wales

WorldDEM4Ortho 0.00022222222 degrees 24 Global (excluding the countries of Azerbaijan, DR Congo and Ukraine) Airbus Defense and Space GmbH World

SRTM 1 arc second 0.0002777777777779 degrees 31 all land areas between 60 degrees north and 56 degrees south except Australia NASA World

EarthEnv-DEM90 0.00083333333333333 degrees 93 Global N Robinson,NCEAS World

SRTM v4.1 0.00083333333333333 degrees 93 all land areas between 60 degrees north and 56 degrees south except Australia CGIAR-CSI World

GMTED2010 7.5 arc second 0.00208333333333333 degrees 232 Global USGS World

GMTED2010 15 arc second 0.00416666666666666 degrees 464 Global USGS World

GMTED2010 30 arc second 0.0083333333333333 degrees 928 Global USGS World

Bathymetry

Canada west coast 10 meters 10 Canada west coast Natural Resources Canada Canada

Gulf of Mexico 40 feet 12 Northern Gulf of Mexico BOEM Gulf of Mexico

MH370 150 meters 150 MH370 flight search area (Phase 1) of Indian Ocean Geoscience Australia Indian Ocean

Switzerland swissBATHY3D 1 - 3 meters 1, 2, 3 Lakes of Switzerland swisstopo Switzerland

NCEI 1/9 arc second 0.000030864197530866 degrees 3 Puerto Rico, U.S Virgin Islands and partial areas of eastern and western United States coast NOAA NCEI United States

NCEI 1/3 arc second 0.000092592592593 degrees 10 Partial areas of eastern and western United States coast NOAA NCEI United States

CRM 1 arc second (Version 2) 0.0002777777777779 degrees 31 Southern California coast of United States NOAA United States

NCEI 1 arc second 0.0002777777777779 degrees 31 Partial areas of northeastern United States coast NOAA NCEI United States

CRM 3 arc second 0.00083333333333333 degrees 93 United States Coast NOAA United States

NCEI 3 arc second 0.00083333333333333 degrees 93 Partial areas of northeastern United States coast NOAA NCEI United States

USGS CoNED 1 - 3 meters 1, 2, 3 Partial coastal areas of eastern and western United States USGS United States

GEBCO 2021 ** 0.00416666666666666 degrees 464 Global GEBCO World

GEBCO 2014 0.0083333333333333 degrees 928 Global GEBCO World * Fundamental Geospatial Data provided by GSI with Approval Number JYOU-SHI No.1239 2016. ** GEBCO Compilation Group (2021) GEBCO 2021 Grid (doi:10.5285/c6612cbe-50b3-0cff-e053-6c86abc09f8f) *** Bathymetry datasets are part of TopoBathy and TopoBathy3D services only.Disclaimer: Data sources are not to be used for navigation/safety at sea and in air.