The land area of Redding, CA was 60 in 2018. The land area of Nampa, ID was 31 in 2018.
Land Area
Water Area
Land area is a measurement providing the size, in square miles, of the land portions of geographic entities for which the Census Bureau tabulates and disseminates data. Area is calculated from the specific boundary recorded for each entity in the Census Bureau's geographic database. Land area is based on current information in the TIGER® data base, calculated for use with Census 2010.
Water Area figures include inland, coastal, Great Lakes, and territorial sea water. Inland water consists of any lake, reservoir, pond, or similar body of water that is recorded in the Census Bureau's geographic database. It also includes any river, creek, canal, stream, or similar feature that is recorded in that database as a two- dimensional feature (rather than as a single line). The portions of the oceans and related large embayments (such as Chesapeake Bay and Puget Sound), the Gulf of Mexico, and the Caribbean Sea that belong to the United States and its territories are classified as coastal and territorial waters; the Great Lakes are treated as a separate water entity. Rivers and bays that empty into these bodies of water are treated as inland water from the point beyond which they are narrower than 1 nautical mile across. Identification of land and inland, coastal, territorial, and Great Lakes waters is for data presentation purposes only and does not necessarily reflect their legal definitions.
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Geographic and Area Datasets Involving Redding, CA or Nampa, ID
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Next Generation Simulation (NGSIM) Vehicle Trajectories and Supporting Data
datahub.transportation.gov | Last Updated 2024-05-20T18:02:47.000ZClick “Export” on the right to download the vehicle trajectory data. The associated metadata and additional data can be downloaded below under "Attachments". Researchers for the Next Generation Simulation (NGSIM) program collected detailed vehicle trajectory data on southbound US 101 and Lankershim Boulevard in Los Angeles, CA, eastbound I-80 in Emeryville, CA and Peachtree Street in Atlanta, Georgia. Data was collected through a network of synchronized digital video cameras. NGVIDEO, a customized software application developed for the NGSIM program, transcribed the vehicle trajectory data from the video. This vehicle trajectory data provided the precise location of each vehicle within the study area every one-tenth of a second, resulting in detailed lane positions and locations relative to other vehicles. Click the "Show More" button below to find additional contextual data and metadata for this dataset. For site-specific NGSIM video file datasets, please see the following: - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf
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Average Water Network Capacity by Hexagon Area
data.edmonton.ca | Last Updated 2023-09-19T21:55:50.000ZThis dataset provides the average water network capacity (2023) within 200m x 200m hexagons, in Litres/second, for the City of Edmonton. The following colours describe the capacity of the city block area water system under computer-simulated conditions using EPCOR-owned hydrants: Red: 0-50 L/s Yellow: 50-100 L/s Light Green: 100-150 L/s Dark Green: 150-200 L/s Teal: 200-250 L/s Blue: 250-300 L/s Purple: 300 L/s and up No Data: No EPCOR-owned hydrants in Area Important Considerations: * EPCOR provides this data for information purposes only. EPCOR makes no guarantee, representation or warranty, express or implied, including that the data is true, accurate, complete, fit for a specific purpose or non-infringing, and no responsibility of any kind is accepted by EPCOR or EPCOR representatives for the completeness or accuracy of the data. EPCOR and its affiliates and their respective officers, directors, employees and other representatives shall not be liable to any person or entity as a result of the use or other handling of the data. * The hexagon grid utilized to present the average water network capacity data has been updated by EPCOR. As such, this version of the dataset should not be directly compared to previous versions of this dataset. * The average water network capacity is intended to be understood in a relative manner: e.g. a blue area is anticipated to provide higher flows on average than a green area. * Any city block area that indicates 0-50 L/s water network capacity has been evaluated by Edmonton Fire Rescue Services (EFRS). EFRS does not associate any significant risk with these areas and can adapt a response to a fire event in these areas given the small geographical area and buildings affected. * The results presented in this data were determined using computer modelling software that represented the distribution and transmission water network current in EWS's digital records as of February 16, 2023. Modifications to the water system after this date may change the water network capacity at any given time or place. * The results presented in this data represent the overall average water network capacity in an area during computer-simulated conditions at EPCOR-owned hydrants. Other factors may change the water network capacity at any given time or place. *The results presented in this data are not representative of lot-level available fire flow as outlined in the Volume 4 Design and Construction Standards. * The average water network capacity ranges are only indicative of average system capacity and not indicative of EPCOR-owned hydrant spacing. A development may still require infrastructure upgrades to meet minimum hydrant spacing requirements. * This map is not a substitute for directed engineering inquiries regarding infrastructure improvements to support development. Please contact EPCOR Water at wtrdc@epcor.com to determine fire protection requirements for development.
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Average Monthly Residential Water Consumption by City Block Area 2017
data.edmonton.ca | Last Updated 2019-07-17T17:08:47.000ZThis dataset provides the average (annual, winter, summer) residential metered water consumption (2017) within 400 m x 400m hexagons (approximately two city blocks) provided in m3/month for the City of Edmonton. Average monthly residential winter water consumption is the average consumption of the following months: January, February, March, April, October, November and December. Average monthly residential summer water consumption is the average consumption of the following months: May, June, July, August and September. Only those hexagons that contain at least ten accounts are illustrated to ensure customer privacy. Residential consumption refers to water used primarily for domestic purposes, where no more than four separate dwelling units are metered by a single water meter. Thematic mapping is based on the following ranges: 0-10 m3/month – orange 10-20 m3/month – green 20-30 m3/month – purple 30-35 m3/month – blue 35-60 m3/month – red 60 m3/month and up – maroon Note: For 2017, there were no areas where the consumption was 60 m3/month and up - thus, the maroon colour would not appear in the legend.
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Average Monthly Residential Water Consumption by City Block Area (Multi-Year)
data.edmonton.ca | Last Updated 2020-10-29T15:04:43.000ZThis dataset provides the average (annual, winter, summer) residential metered water consumption (by year) within 400 m x 400m hexagons (approximately two city blocks) provided in m3/month for the City of Edmonton. Average monthly residential winter water consumption is the average consumption of the following months: January, February, March, April, October, November and December. Average monthly residential summer water consumption is the average consumption of the following months: May, June, July, August and September. Only those hexagons that contain at least ten accounts are illustrated to ensure customer privacy. Residential consumption refers to water used primarily for domestic purposes, where no more than four separate dwelling units are metered by a single water meter. Thematic mapping is based on the following ranges: 0-10 m3/month – orange 10-20 m3/month – green 20-30 m3/month – purple 30-35 m3/month – blue 35-60 m3/month – red 60 m3/month and up – maroon
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Average Monthly Residential Water Consumption by Neighbourhood 2017
data.edmonton.ca | Last Updated 2019-07-17T17:08:16.000ZThis dataset provides the average (annual, winter, summer) residential metered water consumption (2017) within residential neighbourhoods provided in m3/month for the City of Edmonton. Average monthly residential winter water consumption is the average consumption of the following months: January, February, March, April, October, November and December. Average monthly residential summer water consumption is the average consumption of the following months: May, June, July, August and September. Only those residential neighbourhoods with at least ten accounts are illustrated to ensure customer privacy. Residential consumption refers to water used primarily for domestic purposes, where no more than four separate dwelling units are metered by a single water meter. Thematic mapping is based on the following ranges: 0-10 m3/month – orange 10-20 m3/month – green 20-30 m3/month – purple 30-35 m3/month – blue 35-60 m3/month – red 60 m3/month and up – maroon Note: For 2017, there were no areas where the consumption was 60 m3/month and up - thus, the maroon colour would not appear in the legend.
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Average Monthly Residential Water Consumption by City Block Area 2016
data.edmonton.ca | Last Updated 2019-07-17T16:58:13.000ZThis dataset provides the average (annual, winter, summer) residential metered water consumption (2016) within 400 m x 400m hexagons (approximately two city blocks) provided in m3/month for the City of Edmonton. Average monthly residential winter water consumption is the average consumption of the following months: January, February, March, April, October, November and December. Average monthly residential summer water consumption is the average consumption of the following months: May, June, July, August and September. Only those hexagons that contain at least ten accounts are illustrated to ensure customer privacy. Residential consumption refers to water used primarily for domestic purposes, where no more than four separate dwelling units are metered by a single water meter. Thematic mapping is based on the following ranges: 0-10 m3/month – orange 10-20 m3/month – green 20-30 m3/month – purple 30-35 m3/month – blue 35-60 m3/month – red 60 m3/month and up – maroon
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Land Use_data
opendata.utah.gov | Last Updated 2024-04-10T19:40:16.000ZThis dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the Northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the Southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe’s Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe’s Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS.
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Vital Signs: Fatalities From Crashes – by crash
data.bayareametro.gov | Last Updated 2018-07-06T18:04:12.000ZVITAL SIGNS INDICATOR Injuries From Crashes (EN4-6) FULL MEASURE NAME Fatalities from crashes (traffic collisions) LAST UPDATED October 2017 DESCRIPTION Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries sustained as part of this metric. This total fatalities dataset includes fatality counts for the region and counties, as well as individual collision data and metropolitan area data. DATA SOURCE National Highway Safety Administration: Fatality Analysis Reporting System CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the National Highway Safety Administration's Fatalities Analysis Reporting System. 2016 data comes from the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc). Fatalities were normalized over historic population data from the US Census and California Department of Finance and vehicle miles traveled (VMT) data from the Federal Highway Administration. For more regarding reporting procedures and injury classification see the California Highway Patrol Manual (http://www.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).
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Baseline Study of Food for Peace Title II Development Food Assistance Program in Niger-- Household Sanitation and Maternal Health
datahub.usaid.gov | Last Updated 2024-07-12T09:55:20.000ZThis dataset captures data about the mothers in the households surveyed as part of the Baseline Study of Food for Peace Title II Development Food Assistance Program in the Maradi and Zinder regions in Niger as well as the water and sanitation resources available to the household. It has 200 columns and 7,337 rows. In fiscal year 2012, USAID's Office of Food for Peace (FFP) awarded funding to private voluntary organizations (PVOs) to design and implement a multi-year Title II development food assistance program in Niger. The main purpose of the Title II program is to improve long-term food security of chronically food insecure population in the target regions. FFP contracted a firm, ICF International to conduct a baseline study in targeted areas of the country prior to the start of the new program. The purpose of the study was to assess the current status of key indicators, have a better understanding of prevailing conditions and perceptions of the population in the implementation areas, and serve as a point of comparison for future final evaluations. Results would also be used to further refine program targeting and, where possible, to understand the relationship between variables to inform program design. The study was conducted in 2013, while FFP expects to conduct final evaluations as close as possible to the end of the program five years later.
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Vital Signs: Fatalities From Crashes – By Case (2022) DRAFT
data.bayareametro.gov | Last Updated 2022-12-11T07:45:10.000ZVITAL SIGNS INDICATOR Fatalities From Crashes (EN4-6) FULL MEASURE NAME Fatalities from crashes (traffic collisions) LAST UPDATED May 2022 DESCRIPTION Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries sustained as part of this metric. This total fatalities dataset includes fatality counts for the region and counties, as well as individual collision data and metropolitan area data. DATA SOURCE National Highway Safety Administration: Fatality Analysis Reporting System CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc). For more regarding reporting procedures and injury classification, see the California Highway Patrol Manual (https://one.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).