Open Data Network

An Effective And Efficient Transportation Network Indicator Summary

An Effective And Efficient Transportation Network Indicator Summary. To see details for each benchmark county, go to https://reports.data.montgomerycountymd.gov/dataset/An-Effective-And-Efficient-Transportation-Network-/qxyx-qs79

High Mountain Asia UCLA Daily Snow Reanalysis V001

Snowpack plays a significant role in the hydrologic cycle over High Mountain Asia (HMA). As a vital water resource, the distribution of snowpack volume also impacts the water availability for downstream populations. To assess the regional water balance, it is important to characterize the spatio-temporal distribution of water storage in the HMA snowpack. This HMA snow reanalysis data set contains daily estimates of posterior snow water equivalent (SWE), fractional snow covered area (fSCA), snow depth (SD), etc.

Nimbus-7 SMMR Derived Monthly Global Snow Cover and Snow Depth

The data set consists of monthly global snow cover and snow depth derived from Nimbus-7 SMMR data for 1978 through 1987. The SMMR data are interpolated for spatial and temporal gaps, and averaged for display in polar stereographic projection. Maps are based on six-day average brightness temperature data from the middle week of each month. Data are placed into 1/2 degree latitude by 1/2 degree longitude grid cells uniformly subdividing a polar stereographic map according to the geographic coordinates of the center of the radiometers' fields of view. Overlapping data from separate orbits in the same six-day period are averaged to give a single brightness temperature assumed to be at the cell's center. Oceans and bays are masked so that only microwave data for land areas are displayed. Comparisons of SMMR snow cover maps with previous maps produced by NOAA/NESDIS and US Air Force Global Weather Center indicate that the total snow covered area derived from SMMR is usually about ten percent less than that measured by the earlier products, because passive microwave sensors often can't detect shallow dry snow less than about 5 cm deep. Snow depths are comparable, showing SMMR results to be especially good for uniform snow covered areas such as the Canadian high plains and Russian steppes. Heavily forested and mountainous areas tend to mask the microwave snow signatures, and SMMR snow depth derivations are less reliable in those areas. Formerly distributed by NASA/GSFC/NSSDC and NASA Pilot Land Data System (PLDS), these data are now available via ftp from NSIDC.

Northern Hemisphere EASE-Grid 2.0 Weekly Snow Cover and Sea Ice Extent

The Northern Hemisphere EASE-Grid 2.0 Weekly Snow Cover and Sea Ice Extent Version 4 product combine snow cover and sea ice extent at weekly intervals from 23 October 1978 through 29 June 2014, and snow cover alone from 03 October 1966 through 29 June 2014. Snow cover extent for this data set is based on the NOAA/NCDC Climate Data Record (CDR) of Northern Hemisphere (NH) Snow Cover Extent (SCE) by D. Robinson (2012) and regridded to the EASE-Grid. The NOAA/NCDC CDR of Northern Hemisphere Snow Cover Extent data were derived from the manual interpretation of AVHRR, GOES, and other visible-band satellite data (Helfrich et al. 2007). Sea ice extent is regridded to EASE-Grid from Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data. Designed to facilitate study of Northern Hemisphere seasonal fluctuations of snow cover and sea ice extent, the data set also includes monthly climatologies describing average extent, probability of occurrence, and variance. Data are provided in flat, unsigned binary files and are available via FTP.

Northern Hemisphere Snow Cover Monthly Statistics at 1 Degree Resolution V001 (NHSNOWM) at GES DISC

This product is Snow Cover Statistics. The dataset was prepared by Dr. Peter Romanov at Cooperative Institute for Climate Studies(CICS) of the University of Maryland for Northern Eurasia Earth Science Partnership Initiative (NEESPI) program. The product includes the monthly snow statistics (frequency of occurrence) for Northern Hemisphere at 1x1 degree spatial resolution. The dataset covers the time period from January 2000 to November 2014. Monthly data were derived from daily snow cover charts produced at NOAA/NESDIS within Interactive Multisensor Ice Mapping System (IMS).

The Omnibus Surveys - Omnibus Monthly Survey 2002 May EXCEL Data

The Omnibus Surveys are a convenient way to get very quick input on transportation issues; to see who uses what, how they use it, and how users view it, and what they think about it; and to gauge public satisfaction with the transportation system and government programs.The series of surveys include: A monthly household survey of 1,000 households each month, which collects data on core questions about general travel experiences, satisfaction with the system, and some demographic data. Targeted surveys to address special transportation issues, as the U.S. Department of Transportation (DOT) operating administrations need them

Vital Signs: Commute Mode Choice (by Place of Residence) – Bay Area

VITAL SIGNS INDICATOR Commute Mode Choice (T1) FULL MEASURE NAME Commute mode share by residential location LAST UPDATED April 2020 DESCRIPTION Commute mode choice, also known as commute mode share, refers to the mode of transportation that a commuter uses to travel to work, such as driving alone, biking, carpooling or taking transit. The dataset includes metropolitan area, regional, county, city and census tract tables by place of residence. DATA SOURCE U.S. Census Bureau: Decennial Census (1960-2000) - via MTC/ABAG Bay Area Census http://www.bayareacensus.ca.gov/transportation/Means19802000.htm U.S. Census Bureau: American Community Survey Form B08301 (2006-2018; place of residence) www.api.census.gov CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) For the decennial Census datasets, the breakdown of auto commuters between drive alone and carpool is not available before 1980. "Other" includes bicycle, motorcycle, taxi, and other modes of transportation. For the American Community Survey datasets, 1-year rolling average data was used for metros, region, and county geographic levels, while 5-year rolling average data was used for cities and tracts. This is due to the fact that more localized data is not included in the 1-year dataset across all Bay Area cities. Regional mode shares are population-weighted averages of the nine counties’ modal shares. "Auto" includes drive alone and carpool for the simple data tables and is broken out in the detailed data tables accordingly, as it was not available before 1980. “Transit” includes public operators (Muni, BART, etc.) and employer-provided shuttles (e.g., Google shuttle buses). "Other" includes motorcycle, taxi, and other modes of transportation; bicycle mode share was broken out separately for the first time in the 2006 data and is shown in the detailed data tables. Census tract data is not available for tracts with insufficient numbers of residents or workers. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area in addition to the primary MSAs for the nine other major metropolitan areas.

The 1995 American Travel Survey (ATS) - Household Trip Characteristics

The 1995 American Travel Survey (ATS) was conducted by the Bureau of Transportation Statistics (BTS) to obtain information about the long-distance travel of persons living in the United States. The survey collected quarterly information related to the characteristics of persons, households, and trips of 100 miles or more for approximately 80,000 American households.The ATS data provide detailed information on state-to-state travel as well as travel to and from metropolitan areas by mode of transportation. Data are also available for subgroups defined in terms of characteristics related to travel, such as trip purpose, age, family type, income, and a variety of related characteristics. The data can be analyzed at the regional, state, metropolitan area, and county level.NOTE: In 2001, the National Household Travel Survey was carried out. This new survey is a combined Nationwide Personal Transportation Survey (NPTS) and ATS.

Federal Grants Fund Accounts

RICAPS On-road Transportation Emissions roll-up 2

Data by city showing transportation contribution to greenhouse gas emissions in the County. This data is part of the Regionally Integrated Climate Action Planning Suite (RICAPS) program. The majority of cities used the “in-boundary” methodology that relies on data from the Highway Performance Monitoring System. The inventories for South San Francisco and Unincorporated County use the “origin-destination” methodology from that relies on data from Metropolitan Transportation Commission (MTC). So, directly comparing vehicle miles traveled (VMT) across all cities is not statistically possible. Each city in San Mateo County has the opportunity to develop its own Climate Action Plan (CAP) using tools developed by C/CAG in conjunction with DNV KEMA https://www.dnvgl.com/ and Hara. http://www.verisae.com/default.aspx. This project was funded by grants from the Bay Area Air Quality Management District (BAAQMD) and Pacific Gas and Electric Company (PG&E). Climate Action Plans developed from these tools will meet BAAQMD's California Environmental Quality Act (CEQA) guidelines for a Qualified Greenhouse Gas Reduction Strategy. For more information, please see the RICAPS site: http://www.smcenergywatch.com/progress_report.html