6 resultados para Madison County

em Digital Archives@Colby


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China Lake is located in Kennebec County, Maine. Since 1983 the lake has suffered from yearly algal blooms as a result of the addition of excess nutrients. The nutrient load was amplified by erosion within the watershed. Erosion varies widely depending on a number of factors, including the slope of the land, the type of soil, and the way the land is being used. Certain land use types have a high potential to add nutrients to the environment, while others may help absorb excess nutrients and prevent erosion and runoff into the lake. A comprehensive examination of the China Lake watershed was completed using GIS to calculate the erosion potential for the entire area, taking into account past and present land use patterns. This information will help the towns around the lake to make informed decisions about future development and land management.

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http://digitalcommons.colby.edu/atlasofmaine2005/1016/thumbnail.jpg

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http://digitalcommons.colby.edu/atlasofmaine2005/1025/thumbnail.jpg

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This document lists keywords for searching the collection of Kennebec County Interviews. Keywords are arranged in classic, hierarchical index style.

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The U.S. Department of Housing and Urban Development defines affordable housing as a household paying no more than 30 percent of its annual income on housing. That is, families who pay more than 30 percent of their income on housing are considered cost burdened and may have difficulty affording necessities such as food, clothing, healthcare, and transportation. This project focused on Kennebec County, Maine. Between 1990 and 2000, market demand for housing increased at a faster rate than did the supply of housing. Despite the addition of 6,719 homes, the average home price increased faster than average household income. This raises the question of just how many households in Kennebec County are facing unaffordable housing. Using shapefiles and data provided by the US Census Bureau, a map was created with ArcGIS to illustrate the percentage of households, down to the Census Block level of detail, that are paying more than 30 percent of their income to housing. By looking at this information I was able to get a better picture of the housing situation and where in the county households are having the hardest time meeting their needs. The results indicate that households in the more urbanized sections of the county are more likely than rurally located households to be facing unaffordable housing. Namely, Waterville and Augusta held the highest percentage of households paying more than 30 percent of their income for housing.

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Fire is a major management issue in the southwestern United States. Three spatial models of fire risk for Coconino County, Northern Arizona. These models were generated using thematic data layers depicting vegetation, elevation, wind speed and direction, and precipitation for January (winter), June (summer), and July (start of monsoon season). ArcGIS 9.0 was used to weight attributes in raster layers to reflect their influence on fire risk and to interpolate raster data layers from point data. Final models were generated using the raster calculator in the Spatial Analyst extension of ArcGIS 9.0. Ultimately, the unique combinations of variables resulted in three different models illustrating the change in fire risk during the year.