Thurston County GIS Data 2007

UW access only. Questions about spatial data can be directed to uwlib-gis [at] uw [dot] edu, include the URI address below and any information you have.

Thurston County GIS Data 2004

UW access only. Questions about spatial data can be directed to uwlib-gis [at] uw [dot] edu, include the URI address below and any information you have.

Thurston County GIS Data 1999

UW access only. Questions about spatial data can be directed to uwlib-gis [at] uw [dot] edu, include the URI address below and any information you have.

Thurston County GIS Data 1998

UW access only. Questions about spatial data can be directed to uwlib-gis [at] uw [dot] edu, include the URI address below and any information you have.

Yakima County GIS Data 2007

UW access only. Questions about spatial data can be directed to uwlib-gis [at] uw [dot] edu, include the URI address below and any information you have.

Yakima County GIS Data 2010

UW access only. Questions about spatial data can be directed to uwlib-gis [at] uw [dot] edu, include the URI address below and any information you have.

Yakima County Assessor Data 2010

UW access only. Questions about spatial data can be directed to uwlib-gis [at] uw [dot] edu, include the URI address below and any information you have.

Map of part of the “Smith & Kerby” tract in the City of Brantford, County of Brant, Ontario, no date.

An abstract map of a part of the “Smith & Kerby tract” lying within the City of Brantford, County of Brant, Ontario. There is no date on the map. The map shows parts from McMurray’s Survey, Mrs. G.S. Wilkes Survey, and the Howell Survey.

Conservation strategy maps: a tool to facilitate biodiversity action planning illustrated using the heath fritillary butterfly

1. The UK Biodiversity Action Plan (UKBAP) identifies invertebrate species in danger of national extinction. For many of these species, targets for recovery specify the number of populations that should exist by a specific future date but offer no procedure to plan strategically to achieve the target for any species. 2. Here we describe techniques based upon geographic information systems (GIS) that produce conservation strategy maps (CSM) to assist with achieving recovery targets based on all available and relevant information. 3. The heath fritillary Mellicta athalia is a UKBAP species used here to illustrate the use of CSM. A phase 1 habitat survey was used to identify habitat polygons across the county of Kent, UK. These were systematically filtered using relevant habitat, botanical and autecological data to identify seven types of polygon, including those with extant colonies or in the vicinity of extant colonies, areas managed for conservation but without colonies, and polygons that had the appropriate habitat structure and may therefore be suitable for reintroduction. 4. Five clusters of polygons of interest were found across the study area. The CSM of two of them are illustrated here: the Blean Wood complex, which contains the existing colonies of heath fritillary in Kent, and the Orlestone Forest complex, which offers opportunities for reintroduction. 5. Synthesis and applications. Although the CSM concept is illustrated here for the UK, we suggest that CSM could be part of species conservation programmes throughout the world. CSM are dynamic and should be stored in electronic format, preferably on the world-wide web, so that they can be easily viewed and updated. CSM can be used to illustrate opportunities and to develop strategies with scientists and non-scientists, enabling the engagement of all communities in a conservation programme. CSM for different years can be presented to illustrate the progress of a plan or to provide continuous feedback on how a field scenario develops.

Conservation strategy maps: a tool to facilitate biodiversity action planning illustrated using the heath fritillary butterfly

1. The UK Biodiversity Action Plan (UKBAP) identifies invertebrate species in danger of national extinction. For many of these species, targets for recovery specify the number of populations that should exist by a specific future date but offer no procedure to plan strategically to achieve the target for any species. 2. Here we describe techniques based upon geographic information systems (GIS) that produce conservation strategy maps (CSM) to assist with achieving recovery targets based on all available and relevant information. 3. The heath fritillary Mellicta athalia is a UKBAP species used here to illustrate the use of CSM. A phase 1 habitat survey was used to identify habitat polygons across the county of Kent, UK. These were systematically filtered using relevant habitat, botanical and autecological data to identify seven types of polygon, including those with extant colonies or in the vicinity of extant colonies, areas managed for conservation but without colonies, and polygons that had the appropriate habitat structure and may therefore be suitable for reintroduction. 4. Five clusters of polygons of interest were found across the study area. The CSM of two of them are illustrated here: the Blean Wood complex, which contains the existing colonies of heath fritillary in Kent, and the Orlestone Forest complex, which offers opportunities for reintroduction. 5. Synthesis and applications. Although the CSM concept is illustrated here for the UK, we suggest that CSM could be part of species conservation programmes throughout the world. CSM are dynamic and should be stored in electronic format, preferably on the world-wide web, so that they can be easily viewed and updated. CSM can be used to illustrate opportunities and to develop strategies with scientists and non-scientists, enabling the engagement of all communities in a conservation programme. CSM for different years can be presented to illustrate the progress of a plan or to provide continuous feedback on how a field scenario develops.

A VEGETATION RECONSTRUCTION OF UNION COUNTY, PENNSYLVANIA DURING THE EARLY HISTORICAL PERIOD (1755-1855)

This thesis assesses relationships between vegetation and topography and the impact of human tree-cutting on the vegetation of Union County during the early historical era (1755-1855). I use early warrant maps and forestry maps from the Pennsylvania historical archives and a warrantee map from the Union County courthouse depicting the distribution of witness trees and non-tree surveyed markers (posts and stones) in early European settlement land surveys to reconstruct the vegetation and compare vegetation by broad scale (mountains and valleys) and local scale (topographic classes with mountains and valleys) topography. I calculated marker density based on 2 km x 2 km grid cells to assess tree-cutting impacts. Valleys were mostly forests dominated by white oak (Quercus alba) with abundant hickory (Carya spp.), pine (Pinus spp.), and black oak (Quercus velutina), while pine dominated what were mostly pine-oak forests in the mountains. Within the valleys, pine was strongly associated with hilltops, eastern hemlock (Tsuga canadensis) was abundant on north slopes, hickory was associated with south slopes, and riparian zones had high frequencies of ash (Fraxinus spp.) and hickory. In the mountains, white oak was infrequent on south slopes, chestnut (Castanea dentata) was more abundant on south slopes and ridgetops than north slopes and mountain coves, and white oak and maple (Acer spp.) were common in riparian zones. Marker density analysis suggests that trees were still common over most of the landscape by 1855. The findings suggest there were large differences in vegetation between valleys and mountains due in part to differences in elevation, and vegetation differed more by topographic classes in the valleys than in the mountains. Possible areas of tree-cutting were evenly distributed by topographic classes, suggesting Europeans settlers were clearing land and harvesting timber in most areas of Union County.

Socio-economic atlas of Kenya: Depicting the national population census by county and sub-location

The Socio-Economic Atlas of Kenya is the first of its kind to offer high-resolution spatial depictions and analyses of data collected in the 2009 Kenya Population and Housing Census . The combination of geographic and socio-eco - nomic data enables policymakers at all levels, development experts, and other interested readers to gain a spatial understanding of dynamics affecting Kenya. Where is the informal economic sector most prominent? Which areas have adequate water and sanitation? Where is population growth being slowed effectively? How do education levels vary throughout the country? And where are poverty rates lowest? Answers to questions such as these, grouped into seven broad themes, are visually illustrated on high-resolution maps. By supplying precise information at the sub-location level and summarizing it at the county level, the atlas facilitates better planning that accounts for local contexts and needs. It is a valuable decision-support tool for government institutions at different administrative levels, educational institutions, and others. Three organizations – two in Kenya and one in Switzerland – worked together to create the atlas: the Kenya National Bureau of Statistics (KNBS), the Nanyuki-based Centre for Training and Integrated Research in ASAL Development (CETRAD), and the Centre for Development and Environment (CDE) at the University of Bern. Close cooperation between KNBS, CETRAD, and CDE maximized synergies and knowledge exchange.

An examination of the relationship between maternal and neighborhood-level characteristics and intrauterine growth retardation in Harris County, Texas, 1999--2001

The persistence of low birth weight and intrauterine growth retardation (IUGR) in the United States has puzzled researchers for decades. Much of the work that has been conducted on adverse birth outcomes has focused on low birth weight in general and not on IUGR. Studies that have examined IUGR specifically thus far have focused primarily on individual-level maternal risk factors. These risk factors have only been able to explain a small portion of the variance in IUGR. Therefore, recent work has begun to focus on community-level risk factors in addition to the individual-level maternal characteristics. This study uses Social Ecology to examine the relationship of individual and community-level risk factors and IUGR. Logistic regression was used to establish an individual-level model based on 155, 856 births recorded in Harris County, TX during 1999-2001. IUGR was characterized using a fetal growth ratio method with race/ethnic and sex specific mean birth weights calculated from national vital records. The spatial distributions of 114,460 birth records spatially located within the City of Houston were examined using choropleth, probability and density maps. Census tracts with higher than expected rates of IUGR and high levels of neighborhood disadvantage were highlighted. Neighborhood disadvantage was constructed using socioeconomic variables from the 2000 U.S. Census. Factor analysis was used to create a unified single measure. Lastly, a random coefficients model was used to examine the relationship between varying levels of community disadvantage, given the set of individual-level risk factors for 152,997 birth records spatially located within Harris County, TX. Neighborhood disadvantage was measured using three different indices adapted from previous work. The findings show that pregnancy-induced hypertension, previous preterm infant, tobacco use and insufficient weight gain have the highest association with IUGR. Neighborhood disadvantage only slightly further increases the risk of IUGR (OR 1.12 to 1.23). Although community level disadvantage only helped to explain a small proportion of the variance of IUGR, it did have a significant impact. This finding suggests that community level risk factors should be included in future work with IUGR and that more work needs to be conducted. ^

Aedes aegypti, Aedes albopictus, and Dengue virus in Harris county: An estimate of risk

Recent outbreaks of dengue fever (DF) along the United States/Mexico border, coupled with the high number of reported cases in Mexico suggest that there is the possibility for DF emergence in Houston, Texas1,2. To determine the presence of DF, populations of Aedes aegypti and Aedes albopictus were identified and tested for dengue virus. Maps were created to identify "hot spots" (Figure 1) based on historical data on Ae. aegypti and Ae. albopictus, demographic information, and locations of human cases of dengue fever. BG Sentinel Traps®, in conjunction with BG Lure® attractant, octanol and dry ice, were used to collect mosquitoes, which were then tested for presence of dengue virus using ELISA techniques. All samples tested were negative for dengue virus (DV). Survival of DV ultimately comes down to whether or not it will be vectored by a mosquito to a susceptible human host. The presence of infected humans and contact with the mosquito vectors are two critical factors necessary in the establishment of DF. Historical records indicate the presence of Ae. aegypti and Ae. albopictus in Harris County, which would support localized dengue transmission if infected individuals are present.^ (1) Brunkard JM, Robles-Lopez JL, Ramirez J, Cifuentes E, Rothenberg SJ, Hunsperger EA, Moore CG, Brussolo RM, Villarreal NA, Haddad BM, 2007. Dengue fever seroprevalence and risk factors, Texas-Mexico border, 2004. Emerg Infect Dis 13: 1477-1483. (2) Ramos MM, Mohammed H, Zielinski-Gutierrez E, Hayden MH, Lopez JL, Fournier M, Trujillo AR, Burton R, Brunkard JM, Anaya-Lopez L, Banicki AA, Morales PK, Smith B, Munoz JL, Waterman SH, 2008. Epidemic dengue and dengue hemorrhagic fever at the Texas-Mexico Border: results of a household-based seroepidemiologic survey, December 2005. Am J Trop Med Hyg 78: 364-369.^

Burden of invasive pneumococcal disease in Harris County, Texas (2003--2010) and the implication for enhanced public health surveillance of isolates

Invasive pneumococcal disease (IPD) causes significant health burden in the US, is responsible for the majority of bacterial meningitis, and causes more deaths than any other vaccine preventable bacterial disease in the US. The estimated National IPD rate is 14.3 cases per 100,000 population with a case-fatality rate of 1.5 cases per 100,000 population. Although cases of IPD are routinely reported to the local health department in Harris County Texas, the incidence (IR) and case-fatality (CFR) rates have not been reported. Additionally, it is important to know which serotypes of S. pneumoniae are circulating in Harris County Texas and to determine if ‘replacement disease’ is occurring. ^ This study reported incidence and case-fatality rates from 2003 to 2009, and described the trends in IPD, including the IPD serotypes circulating in Harris County Texas during the study period, particularly in 2008 and 2010. Annual incidence rates were calculated and reported for 2003 to 2009, using complete surveillance-year data. ^ Geographic information system (GIS) software was used to create a series of maps of the data reported during the study period. Cluster and outlier analysis and hot spot analysis were conducted using both case counts by census tract and disease rate by census tract. ^ IPD age- and race-adjusted IR for Harris County Texas and their 95% confidence intervals (CIs) were 1.40 (95% CI 1.0, 1.8), 1.71 (95% CI 1.24, 2.17), 3.13 (95% CI 2.48, 3.78), 3.08 (95% CI 2.43, 3.74), 5.61 (95% CI 4.79, 6.43), 8.11 (95% CI 7.11, 9.1), and 7.65 (95% CI 6.69, 8.61) for the years 2003 to 2009, respectively (rates were age- and race-adjusted to each year's midyear US population estimates). A Poisson regression model demonstrated a statistically significant increasing trend of about 32 percent per year in the IPD rates over the course of the study period. IPD age- and race-adjusted case-fatality rates (CFR) for Harris County Texas were also calculated and reported. A Poisson regression model demonstrated a statistically significant increasing trend of about 26 percent per year in the IPD case-fatality rates from 2003 through 2009. A logistic regression model associated the risk of dying from IPD to alcohol abuse (OR 4.69, 95% CI 2.57, 8.56) and to meningitis (OR 2.42, 95% CI 1.46, 4.03). ^ The prevalence of non-vaccine serotypes (NVT) among IPD cases with serotyped isolates was 98.2 percent. In 2008, the year with the sample more geographically representative of all areas of Harris County Texas, the prevalence was 96 percent. Given these findings, it is reasonable to conclude that ‘replacement disease’ is occurring in Harris County Texas, meaning that, the majority of IPD is caused by serotypes not included in the PCV7 vaccine. Also in conclusion, IPD rates increased during the study period in Harris County Texas.^