As of March 2025, there were a reported 5,426 data centers in the United States, the most of any country worldwide. A further 529 were located in Germany, while 523 were located in the United Kingdom. What is a data center? A data center is a network of computing and storage resources that enables the delivery of shared software applications and data. These facilities can house large amounts of critical and important data, and therefore are vital to the daily functions of companies and consumers alike. As a result, whether it is a cloud, colocation, or managed service, data center real estate will have increasing importance worldwide. Hyperscale data centers In the past, data centers were highly controlled physical infrastructures, but the cloud has since changed that model. A cloud data service is a remote version of a data center – located somewhere away from a company's physical premises. Cloud IT infrastructure spending has grown and is forecast to rise further in the coming years. The evolution of technology, along with the rapid growth in demand for data across the globe, is largely driven by the leading hyperscale data center providers.

Worldwide spending on data center systems is projected to reach over, *** billion U.S. dollars in 2025, marking a significant ** percent increase from 2024. This growth reflects the ongoing digital transformation across industries and the increasing demand for advanced computing capabilities. The surge in data center investments is closely tied to the rapid expansion of artificial intelligence technologies, particularly with the wake of generative AI. AI chips fuel market growth The rise in data center spending aligns with the booming AI chip market, which is expected to reach ** billion U.S. dollars by 2025. Nvidia has emerged as a leader in this space, with its data center revenue skyrocketing due to the crucial role its GPUs play in training and running large language models like ChatGPT. The global GPU market, valued at ** billion U.S. dollars in 2024, is a key driver of this growth, powering advancements in machine learning and deep learning applications. Semiconductor industry adapts to AI demands The broader semiconductor industry is also evolving to meet the demands of AI technologies. With global semiconductor revenues surpassing *** billion U.S. dollars in 2023, the market is expected to approach *** billion U.S. dollars in 2024. AI chips are becoming increasingly prevalent in servers, data centers and storage infrastructures. This trend is reflected in the data centers and storage semiconductor market, which is projected to grow from ** billion U.S. dollars in 2023 to *** billion U.S. dollars by 2025, driven by the development of image sensors and edge AI processors.

This data package includes an ArcMap geodatabase for the Chihuahuan Desert Rangeland Research Center (CDRRC) pastures 1, 4, 14, and 15: one polygon feature class, one point feature class, associated attribute tables and metadata. The spatial data, CDRRC1_4_14_15_StateMap_v1.gdb.zip, represents the ecological sites and states on Pastures 1, 4, 14 and 15 on the Chihuahuan Desert Rangeland Research Center, and includes field traverse data. CDRRC1_4_14_15_StateMapMetadata.pdf and TraversePointsMetadata.pdf contain the geospatial metadata provided by ArcMap. CDRRC1_4_14_15_StateMap_v1.csv is the attribute table associated with the state map’s polygon feature class, and TraversePoints.xlsx is the attribute table associated with the traverse points feature class and includes a sheet containing detailed attribute metadata.

The Data Center Opportunity Zone Overlay District was created for the purpose of promoting development of data centers within areas of the County where there is existing infrastructure that could adequately support the proposed use. This District continues the County's efforts to attract and advance high-tech industrial development while limiting negative impacts to communities. (Ord. No. 16-21, Attch., 5-17-16)

The size of the Malaysia Data Center market was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 10.00% during the forecast period.Data centers can be explained as basically buildings that house computer systems and networking equipment to store, process, and distribute data. The data center acts as the backbone of the digital age, and smooth access to and operation of information and services by business organizations and individuals make it highly relevant to the involved businesses. Malaysia's data center market is experiencing tremendous growth, with growing digitalization, initiatives of the government, and favorable investment climate serving as drivers.Data centers are very common and highly employed in almost all industries. Data centers help store confidential information, including financial data, while at the same time making it possible to conduct transactions on the spot in the financial industry. The healthcare organizations use data centers as they help store patients' records and subsequently analyze them for research purposes to better care for patients. In an e-commerce business, it relies on a data center because orders are managed and processed through inventory management and online shopping. Besides, data centers provide the power for cloud computing services; this way businesses can gain access to computing resources on demand, thus keeping their infrastructure costs down and improving ease of use.Malaysia has strategically poised as a hub of a regional data center that is strengthened by its well-developed telecom infrastructure as well as the policies of the government. Initiatives taken up for promoting digital economy and foreign investments helped further boost the growth in the data center market. Increasing the demand for data storage, processing, and connectivity from the Malaysian end further assures its position on the world's digital map. Recent developments include: October 2022: Zenlayer entered into a joint venture with Megaport to strengthen and expand its presence globally. The partnership is aimed at providing enhanced services such as improved network connectivity, real time provisioning, and on demand private connectivity for its clients around the globe.September 2022: NTT Ltd announced the commencement of the construction of its sixth data centre in Cyberjaya. NTT plans to initially invest over USD 50 million in the sixth data centre, which is also known as Cyberjaya 6 (CBJ6). Further, CBJ6 and CBJ5 will have a total facility load of 22MW, spanning a combined 200,000 sq ft.April 2022: Malaysian data center firm Open DC aanounced that they are partnering with the Malaysian government to build a data center in the north of the country. The company aim to improve the Internet development at the northern border, to emulate the existing neighboring Internet Exchange (IX) via the Malaysia-Singapore border.. Key drivers for this market are: Increasing Awareness of Energy Consumption Control. Potential restraints include: High Risk Associated with Data. Notable trends are: OTHER KEY INDUSTRY TRENDS COVERED IN THE REPORT.

The Growth Centers data on the Future Land Use Map were developed for the Division of Planning, RI Statewide Planning Program as part of an update to a state land use plan. These data are included in the Plan as Figure 121-02-(01), Future Land Use Map. The growth centers were an end product of a GIS overlay analysis of land suitability and scenario planning for future growth. Initially the factors for centers included 9 urban communities; Providence, East Providence, Pawtucket, Cranston, Central Falls, Warwick, West Warwick, Newport and Woonsocket as potential urban centers as opposed to identifying specific neighborhoods in those municipalities. Historical downtowns and traditional mixed-use central business cores in urban fringe / suburban communities were included as potential town centers, as well as, some of the historical village downtowns and some traditional mixed-use cores in rural communities. All communities in the State either include one or more existing or potential centers or are within the Urban Services Boundary on the map. The growth centers shown in these data were selected by the Statewide Planning staff, the Technical Committee and the State Planning Council through a series of discussions at public meetings, and comments received at public hearings and workshops in the final adoption of Land Use 2025 in 2006. Centers depicted on the Future Land Use 2025 map are illustrative of potential new centers that may be established. It is not a intended as a comprehensive inventory of existing centers. Other centers may be illustrated and or proposed in municipal comprehensive plans. Full descriptions of the methodology for the GIS analysis and scenario planning can be found within the Technical Appendix D to Land Use 2025, Geographic Analysis for Land Available and Suitable for Development for Land Use 2025. Land Use 2025: State Land Use Policies and Plan was published by the RI Statewide Planning Program on April 13, 2006. The Plan directs the state and communities to concentrate growth inside the Urban Services Boundary (USB) and within potential growth centers in rural areas. It establishes different development approaches for urban and rural areas. This Map has several purposes and applications: It is intended to be used as a policy guide for directing growth to areas most capable of supporting current and future developed uses and to direct growth away from areas less suited for development. Secondly, the Map is a guide to assist the state and communities in making land use policies. It is important to note the Map is a generalized portrayal of state land use policy. It is not a statewide zoning map. Zoning matters and individual land use decisions are the prerogative of local governments. Growth Centers are envisioned to be areas that will encourage development that is both contiguous to existing development with low fiscal and environmental impacts. They are intended to be compact developed areas (existing or new) containing a defined central core that accommodate community needs for residential and economic functions. Centers are intended to provide optimum use of land and services, and offer a choice of diverse housing stock, economic functions, and cultural and governmental uses. Density will vary greatly between centers subject to site constraints; however, it is intended that they will share the common characteristic of compact development that capitalizes on existing infrastructure. Centers should reflect traditional New England development patterns with a human scale of blocks, streets, open spaces that offer walkability and access to transit where available. In suburban areas, centers should be distinguished from surrounding sprawling development by a closer proximity between residential and non-residential uses. In rural areas, centers should be surrounded by natural areas, farmland, or open space, and may have a mixed-use and or commercial area in the core for neighborhood-scale goods and services. The land use element is the over arching element in Rhode Island's State Guide Plan. The Plan articulates goals, objectives and strategies to guide the current and future land use planning of municipalities and state agencies. The purpose of the plan is to guide future land use and to present policies under which state and municipal plans and land use activities will be reviewed for consistency with the State Guide Plan. The Map is a graphical representation of recommendations for future growth patterns in the State. The Map contains a USB that shows where areas with public services supporting urban development presently exist, or are likely to be provided, through 2025. Also included on the map are growth centers which are potential areas for development and redevelopment outside of the USB. These data will be updated when plan is updated or upon an amendment approved by the State Planning Council.

This file contains vector digital data for vegetation groupings in New Mexico at a 1:1,000,000 scale. The source software was ARC/INFO 5.0.1 and the conversion software was ARC/INFO 7.0.3.

The Career Centers data set houses the Division’s information for customers on all of the Career Centers across the state.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

Using these data, the COVID-19 community level was classified as low, medium, or high.

COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.

For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

Archived Data Notes:

This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.

May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.

June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.

July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.

July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.

July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.

July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.

July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.

August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.

August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.

August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.

August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.

August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.

September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.

September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,

The "Planimetric Map Digital Data File (scale is 1:25,000, 1:50,000 and 1:100,000)" of this center was listed as class A data in the "Second Meeting of the 105th Executive Yuan Open Data Consultation Group" and was revised and issued by the Ministry of the Interior on July 26, 105th, under the Taiwan-Nei-Di-Zi No. 1051306149 Order to amend and promulgate the "Charging Standards for Land Surveying and Mapping Results Data". The attached Annex 2 to Paragraph 2 of the aforementioned standards opened the data for free download and use. Please note that the Planimetric Map Digital Data File does not include contour line layers.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

Culminating more than four years of processing data, NASA and the National Geospatial-Intelligence Agency (NGA) have completed Earth's most extensive global topographic map. The mission is a collaboration among NASA, NGA, and the German and Italian space agencies. For 11 days in February 2000, the space shuttle Endeavour conducted the Shuttle Radar Topography Mission (SRTM) using C-Band and X-Band interferometric synthetic aperture radars to acquire topographic data over 80% of the Earth's land mass, creating the first-ever near-global data set of land elevations. This data was used to produce topographic maps (digital elevation maps) 30 times as precise as the best global maps used today. The SRTM system gathered data at the rate of 40,000 per minute over land. They reveal for the first time large, detailed swaths of Earth's topography previously obscured by persistent cloudiness. The data will benefit scientists, engineers, government agencies and the public with an ever-growing array of uses. The SRTM radar system mapped Earth from 56 degrees south to 60 degrees north of the equator. The resolution of the publicly available data is three arc-seconds (1/1,200th of a degree of latitude and longitude, about 295 feet, at Earth's equator). The final data release covers Australia and New Zealand in unprecedented uniform detail. It also covers more than 1,000 islands comprising much of Polynesia and Melanesia in the South Pacific, as well as islands in the South Indian and Atlantic oceans. SRTM data are being used for applications ranging from land use planning to "virtual" Earth exploration. Currently, the mission's homepage "http://www.jpl.nasa.gov/srtm" provides direct access to recently obtained earth images. The Shuttle Radar Topography Mission C-band data for North America and South America are available to the public. A list of complete public data set is available at "http://www2.jpl.nasa.gov/srtm/dataprod.htm" The data specifications are within the following parameters: 30-meter X 30-meter spatial sampling with 16 meter absolute vertical height accuracy, 10-meter relative vertical height accuracy, and 20-meter absolute horizontal circular accuracy. From the JPL Mission Products Summary, "http://www.jpl.nasa.gov/srtm/dataprelimdescriptions.html". The primary products of the SRTM mission are the digital elevation maps of most of the Earth's surface. Visualized images of these maps are available for viewing online. Below you will find descriptions of the types of images that are being generated:

• Radar Image
• Radar Image with Color as Height
• Radar Image with Color Wrapped Fringes
  -Shaded Relief
• Perspective View with B/W Radar Image Overlaid
• Perspective View with Radar Image Overlaid, Color as Height
• Perspective View of Shaded Relief
• Perspective View with Landsat or other Image Overlaid
• Contour Map - B/W with Contour Lines
• Stereo Pair
• Anaglypgh

The SRTM radar contained two types of antenna panels, C-band and X-band. The near-global topographic maps of Earth called Digital Elevation Models (DEMs) are made from the C-band radar data. These data were processed at the Jet Propulsion Laboratory and are being distributed through the United States Geological Survey's EROS Data Center. Data from the X-band radar are used to create slightly higher resolution DEMs but without the global coverage of the C-band radar. The SRTM X-band radar data are being processed and distributed by the German Aerospace Center, DLR.

The "Economic Development Version Topographic Map Digital Data File (scale of 1:25,000, 1:50,000 and 1:100,000)" of this center has been classified as category A data at the "2nd meeting of the open consultation group for 105 Executive Yuan data" and has been amended and released by the Ministry of the Interior on July 26, 105, in the directive Tai-Nei-Di No. 1051306149, "National Surveying and Mapping Results Data Charging Standard" Article 2, Annex 2 to Open Data for free download and use. Note: The topographic map digital data file of the economic development version does not include contour layers.

No Publication Abstract is Available

The Lands pdf represent the location and project number of NMDOT Construction projects.

This dataset contains all Known Mineral Deposit Areas in the state of New Mexico. It is in a vector digital structure digitized from a 1:500,000 scale map of the state of New Mexico. The source software used was ARC/INFO 5.0 and the conversion software was ARC/INFO 7.0.3. For questions regarding data and full documentation contact: Bureau of Mines, Intermountain Field Operations Center, PO Box 25086, Bldg 20, Federal Center, Denver, CO, 80225. File siz is 0.7 Mb, compressed.

These ESI data were collected, mapped, and digitized to provide environmental data for oil spill planning and response. The Clean Water Act with amendments by the Oil Pollution Act of 1990 requires response plans for immediate and effective protection of sensitive resources. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. ESI MAPS SHOULD NOT BE USED FOR NAVIGATIONAL PURPOSES. Source data used in the development of these regional atlases range from 1900 to 2005 with much of the data dated from the 1980s, 1990s, to 2005. Source data dates are extensively documented in the included metadata and include the following DE_NJ_PA, data range 1969-1995, compiled 1995, HudsonRiver data range 1942-2005, compiled 2005, Massachusetts data range 1978-1998, compiled 1998, New Hampshire data range 1948-2003, compiled 2003, and RI_CT_NY_NJ data range 1900-2001, compiled 1999.

This atlas update adds data formats to those originally released to accommodate new technologies of digital mapping. The underlying data have not been updated since the atlas publication dates shown. Each ESI atlas listed is provided in a variety of GIS formats, including a personal Geodatabase for use with the ESRI ArcGIS product line. An .mxd file, created in ArcMap 9.3 is also included. This mapping document provides links to all of the data tables and symbolization of the layers using the standardized ESI colors and hatch patterns. Layer files are also supplied. These, together with the associated geodatabase, can be used in other mapping projects to define the symbology and links established in the original ESI .mxd file.

PDF files of the map pages are also included. These PDFS now have the seasonality pages attached to the appropriate map document. This should make it easier to print and distribute individual maps and insure that the supporting information is always included. The GIS data are also provided in ARC Export .e00 format, as shape files with an ArcView 3.x project and in MOSS format. Database files are included in text and .e00 format. Each area directory contains a readme file which shows the area of coverage and gives a bit more description of the various file formats included.

description: The City Planning Facilities Database (FacDB) aggregates information about 35,000+ public and private facilities and program sites that are owned, operated, funded, licensed or certified by a City, State, or Federal agency in the City of New York. It captures facilities that generally help to shape quality of life in the city s neighborhoods, including schools, day cares, parks, libraries, public safety services, youth programs, community centers, health clinics, workforce development programs, transitional housing, and solid waste and transportation infrastructure sites. To facilitate analysis and mapping, the data is available in coma-separated values (CSV) file format, ESRI Shapefile, and GeoJSon. The data is also complemented with a new interactive web map that enables users to easily filter the data for their needs. Users are strongly encouraged to read the database documentation, particularly with regard to analytical limitations.; abstract: The City Planning Facilities Database (FacDB) aggregates information about 35,000+ public and private facilities and program sites that are owned, operated, funded, licensed or certified by a City, State, or Federal agency in the City of New York. It captures facilities that generally help to shape quality of life in the city s neighborhoods, including schools, day cares, parks, libraries, public safety services, youth programs, community centers, health clinics, workforce development programs, transitional housing, and solid waste and transportation infrastructure sites. To facilitate analysis and mapping, the data is available in coma-separated values (CSV) file format, ESRI Shapefile, and GeoJSon. The data is also complemented with a new interactive web map that enables users to easily filter the data for their needs. Users are strongly encouraged to read the database documentation, particularly with regard to analytical limitations.

The Lands pdf represent the location and project number of NMDOT Construction projects.

NM EPSCoR RII3 is designed to enhance research competitiveness through investment in three strategic areas: (1) critical Research Infrastructure, (2) Cyberinfrastructure, and (3) Human Infrastructure. These investments will help establish NM as a laboratory for climate change research, and as a model for science‐based public policy. The multi‐disciplinary, multi‐scale effort is envisioned to transform climate change science and policymaking in NM by providing the tools required for quantitative, science‐driven discussion of difficult water policy options facing the State in the 21st Century.