Dynamic Map Gives Harrison County Citizens Access to Elections Information

Esri logoCitizens of Harrison County, West Virginia, can easily determine their election districts and poll locations through an interactive map developed using free web templates from Esri. The county, which has just under 70,000 residents, also plans to use Esri templates to offer a real-time election results viewer.

“Harrison County is proving that it’s possible for small governments to bring their authoritative data online and engage citizens using a technology that they have learned simply works,” says Christopher Thomas, Esri director of government markets. “Applications like these are easily replicated and can help governments communicate with the public on everything from elections to service requests.”

Harrison County Clerk Susan Thomas requested an upgrade of the county’s outdated paper maps in preparation for the 2012 elections so her office could quickly and accurately confirm the eligibility of candidates for seats on the county commission and school board. “With the new 2010 census data available, there’s no better time to update our precinct map,” says Thomas.

In response, the county developed an online mapping application that leverages existing geospatial resources in Esri’s ArcGIS platform. This public application clearly defines the county’s district boundaries while bringing more transparency to the elections process. Besides providing citizens and staff with accurate district and poll information, the app is expected to boost efficiency by decreasing the number of poll location inquiries the county receives during elections and helping ensure that voters are registered in the correct precinct throughout the year. “It’s a win for everyone,” says Harrison County geographic information system (GIS) coordinator Mike Pizzino Jr. “This makes our work more accurate, which definitely helps the taxpayers.”

Harrison County’s elections app was built using ArcGIS and free web mapping APIs available on the ArcGIS for Local Government website at esri.com/arcgisforlocalgov. Also available are APIs involving code enforcement, emergency response, land use, and many other areas of local government operations.

{Source: Esri press release]

Assessing Resolution and Source Effects of Digital Elevation Models on Automated Floodplain Delineation: A Case Study from the Camp Creek Watershed, Missouri

Applied Geography

Applied Geography, Volume 34, May 2012

Richard Charrier and Yingkui Li

“Highlights

  • We examined resolution and source effects of DEMs on floodplain delineation.
  • High discrepancies exist between features delineated by LiDAR and USGS DEMs.
  • High resolution DEMs are more sensitive to minor features in watershed delineation.
  • LiDAR DEMs produce more resolution-dependent delineations.
  • USGS DEMs produce similar delineations regardless of DEM resolutions (5–30 m).

“Digital elevation models (DEMs) have been widely used in automated floodplain modeling to determine floodplain boundaries. However, the effects of DEM resolution and data source on floodplain delineation are not well quantified. This paper presents a case study to assess these effects from the Camp Creek Watershed, Missouri, using two sets of DEMs. One is the Light Detection and Ranging (LiDAR) DEMs re-sampled from 1-m to 3, 5, 10, 15, and 30-m resolutions. The other is 5, 10, and 30-m DEMs obtained from the U.S. Geological Survey (USGS). Floodplain boundaries are delineated using a combination of hydrological, hydraulic and floodplain delineation models under the Federal Emergency Management Agency’s (FEMA) guideline. Model outputs including stream network, watershed and floodplain boundaries are compared to 1-m LiDAR DEM outputs (as the reference) to assess the uncertainty. Results indicate that re-sampled 3 or 5-m LiDAR DEMs produce similar streams and floodplain boundaries within 10% difference of the reference. In contrast, coarser LiDAR DEMs (such as the 10-m resolution) are more appropriate for watershed boundary delineation because higher DEM resolutions are likely more sensitive to minor topographic changes and may introduce erroneous boundaries. For different data sources, uncertainties introduced by USGS DEMs are much higher than LiDAR DEMs with a distinct relationship between uncertainties and DEM resolutions. Uncertainties of LiDAR DEMs consistently increase with decreasing resolutions, whereas similar levels of uncertainty are observed for different USGS DEM resolutions. This difference is probably due to the inherited difference in their original data source resolutions to make these two types of DEMs.”

A Spatial Analysis of Infrastructures and Social Services in Rural Nigeria: Implications for Public Policy

GeoTropicoGeoTropico, 5 (1), Articulo 2: 25-3, 2011.

“There are observed inequalities in the distribution of socio-economic facilities in Nigeria. The paper examined the availability of some social infrastructural facilities in rural parts of Imo State. It equally examined the extent to which those facilities have promoted rural development in the State. Data were collected mainly from primary sources. A total number of 2,340 copies of questionnaire were administered in eighteen communities and all were retrieved for the analysis. Research findings revealed unevenness in the availability of potable water supply and telephone (analogue landline) facilities. However, the availability of electricity, educational and health facilities were largely indicated by respondents in the 18 study communities to be well spread across the State. The paper noted some rural development implications as the result of the Z-test of proportion statistics led to the rejection of the null hypothesis and the acceptance of the alternative, which is that, majority of rural areas in Imo State, have significant presence of social infrastructural facilities that enhance economic activities.”