Influence of post-soviet land reform on the patterns of land use dynamics in Gauja National Park, Latvia

This dissertation analyzes landuse and landcover dynamics in Gauja National Park (GNP), Latvia from the late Soviet period (1985) through 2002. Landcover change in the Park is assessed through analyses of remotely sensed imagery in conjunction with ancillary Geographic Information Systems (GIS) data layers. Changes in landcover composition and patterns are measured using post-classification change analyses of Landsat Thematic Mapper satellite images, and by computing landscape pattern metrics, respectively. These landscape changes are examined with respect to GNP stakeholder group interests, as determined through qualitative interviews with key informants. Statistical regression models are developed to determine effects on the landscape of spatially explicit variables representing social, biophysical, geographic, and political drivers of landcover change in GNP. Finally, a landowner survey conducted by the GNP Administration was geocoded and statistically analyzed using crosstabs with respect to geographically explicit variables to understand important factors affecting landowner attitudes to GNP landuse policies. Results from the key informant interviews show that community leaders representing GNP residents are interested in broadening landuse rights and compensation for owners of use-restricted lands. Environmental NGOs, Western government organizations, and supra-national organizations promote their interests in preserving biodiversity in GNP, while Latvian landscape scientists express interest in preserving Latvia’s cultural landscape and promoting rural development within the Park. Landcover change analyses showed an increase in forest cutting immediately after Latvia’s independence (in 1991), and, following, a consistent overall growth in forested lands, particularly in the more protected zones of the Park. A decrease in the amount of fields and meadows was evident since Latvian independence, resulting in a deterioration of Latvia’s cultural landscape. Regression analyses showed the most important predictor variables of the type of landcover change, on a per pixel basis, were the management zones of the Park, the distance from large water bodies, the distance to the nearest road, the municipality, and the slope of the land. In addition, crosstab analyses showed that landowners in zones with more landuse restrictions were more likely to be supportive of GNP landuse policies than were landowners in zones with fewer landuse restrictions

Locating suitable habitats for West Nile Virus-infected mosquitoes through association of environmental characteristics with infected mosquito locations: a case study in Shelby County, Tennessee

<p>Abstract</p> <p>Background</p> <p>Since its first detection in 2001, West Nile Virus (WNV) poses a significant health risk for residents of Shelby County in Tennessee. This situation forced public health officials to adopt efficient methods for monitoring disease spread and predicting future outbreaks. Analyses that use environmental variables to find suitable habitats for WNV-infected mosquitoes have the potential to support these efforts. Using the Mahalanobis Distance statistic, we identified areas of Shelby County that are ecologically most suitable for sustaining WNV, based on similarity of environmental characteristics to areas where WNV was found. The environmental characteristics in this study were based on Geographic Information Systems (GIS) data, such as elevation, slope, land use, vegetation density, temperature, and precipitation.</p> <p>Results</p> <p>Our analyses produced maps of likely habitats of WNV-infected mosquitoes for each week of August 2004, revealing the areas that are ecologically most suitable for sustaining WNV within the core of the Memphis urban area. By comparing neighbourhood social characteristics to the environmental factors that contribute to WNV infection, potential social drivers of WNV transmission were revealed in Shelby County. Results show that human population characteristics and housing conditions such as a high percentage of black population, low income, high rental occupation, old structures, and vacant housing are associated with the focal area of WNV identified for each week of the study period.</p> <p>Conclusion</p> <p>We demonstrated that use of the Mahalanobis Distance statistic as a similarity index to assess environmental characteristics is a potential raster-based approach to identify areas ecologically most suitable for sustaining the virus. This approach was also useful to monitor changes over time for likely locations of infected mosquito habitats. This technique is very helpful for authorities when making decisions related to an integrated mosquito management plan and targeted health education outreach.</p

Influence of post -Soviet land reform on the patterns of land use dynamics in Gauja National Park, Latvia

This dissertation analyzes landuse and landcover dynamics in Gauja National Park (GNP), Latvia from the late Soviet period (1985) through 2002. Landcover change in the Park is assessed through analyses of remotely sensed imagery in conjunction with ancillary Geographic Information Systems (GIS) data layers. Changes in landcover composition and patterns are measured using post-classification change analyses of Landsat Thematic Mapper satellite images, and by computing landscape pattern metrics, respectively. These landscape changes are examined with respect to GNP stakeholder group interests, as determined through qualitative interviews with key informants. Statistical regression models are developed to determine effects on the landscape of spatially explicit variables representing social, biophysical, geographic, and political drivers of landcover change in GNP. Finally, a landowner survey conducted by the GNP Administration was geocoded and statistically analyzed using crosstabs with respect to geographically explicit variables to understand important factors affecting landowner attitudes to GNP landuse policies. Results from the key informant interviews show that community leaders representing GNP residents are interested in broadening landuse rights and compensation for owners of use-restricted lands. Environmental NGOs, Western government organizations, and supra-national organizations promote their interests in preserving biodiversity in GNP, while Latvian landscape scientists express interest in preserving Latvia’s cultural landscape and promoting rural development within the Park. Landcover change analyses showed an increase in forest cutting immediately after Latvia’s independence (in 1991), and, following, a consistent overall growth in forested lands, particularly in the more protected zones of the Park. A decrease in the amount of fields and meadows was evident since Latvian independence, resulting in a deterioration of Latvia’s cultural landscape. Regression analyses showed the most important predictor variables of the type of landcover change, on a per pixel basis, were the management zones of the Park, the distance from large water bodies, the distance to the nearest road, the municipality, and the slope of the land. In addition, crosstab analyses showed that landowners in zones with more landuse restrictions were more likely to be supportive of GNP landuse policies than were landowners in zones with fewer landuse restrictions

Exploring the spatio-temporal dynamics of reservoir hosts, vectors, and human hosts of west Nile virus: A review of the recent literature

Over the last two decades West Nile Virus (WNV) has been responsible for significant disease outbreaks in humans and animals in many parts of the World. Its extremely rapid global diffusion argues for a better understanding of its geographic extent. The purpose of this inquiry was to explore spatio-temporal patterns of WNV using geospatial technologies to study populations of the reservoir hosts, vectors, and human hosts, in addition to the spatio-temporal interactions among these populations. Review of the recent literature on spatial WNV disease risk modeling led to the conclusion that numerous environmental factors might be critical for its dissemination. New Geographic Information Systems (GIS)-based studies are monitoring occurrence at the macro-level, and helping pinpoint areas of occurrence at the micro-level, where geographically-targeted, species-specific control measures are sometimes taken and more sophisticated methods of surveillance have been used. © 2013 by the authors; licensee MDPI, Basel, Switzerland

Remote sensing assessment of salinization impacts in the tarim basin: The delta oasis of the ugan and kuqa rivers

Extracting information about saline soils from remote sensing data can be useful, particularly given the environmental significance and changing nature of these soils in arid environments. One interesting case study is the delta oasis of the Ugan and Kuqa rivers in China\u27s Xinjiang region, which was studied using a landsat enhanced thematic mapper plus (ETM+) image collected in August 2001. In recent years, decision tree classifiers have been used successfully for land cover classification from remote sensing data. Principal component analysis (PCA) is a popular data reduction technique used to help build a decision tree; it reduces complexity and can help improve the classification precision of a decision tree. A decision tree approach was used to determine the key variables to be used for classification and ultimately extract salinized soil from other cover and soil types within the study area. The third principal component (PC3) is an effective variable in the decision tree classification for salinized soil information extraction. The PC3 was the best band to identify areas of severely salinized soil; the blue spectral band from the ETM+ sensor (TM1) was the best band to identify salinized soil with the salt-tolerant vegetation of tamarisk (Tamarix chinensis Lour); and areas comprising mixed water bodies and vegetation can be identified using the spectral indices Modified Normalized Difference Water Index (MNDWI) and Normalized Difference Vegetation Index (NDVI). Based upon this analysis, a decision tree classifier was applied to classify land cover types with different levels of soil saline. The overall accuracy of the classification was 94.80%, which suggests that the decision tree model was a simple and effective method with relatively high precision. © 2010 Springer Science+Business Media B.V

Locating suitable habitats for West Nile Virus-infected mosquitoes through association of environmental characteristics with infected mosquito locations: a case study in Shelby County, Tennessee-1

Ater than or equal to 0.9 (P-value ≥ 0.9).<p><b>Copyright information:</b></p><p>Taken from "Locating suitable habitats for West Nile Virus-infected mosquitoes through association of environmental characteristics with infected mosquito locations: a case study in Shelby County, Tennessee"</p><p>http://www.ij-healthgeographics.com/content/7/1/12</p><p>International Journal of Health Geographics 2008;7():12-12.</p><p>Published online 29 Mar 2008</p><p>PMCID:PMC2322965.</p><p></p

Locating suitable habitats for West Nile Virus-infected mosquitoes through association of environmental characteristics with infected mosquito locations: a case study in Shelby County, Tennessee-0

<p><b>Copyright information:</b></p><p>Taken from "Locating suitable habitats for West Nile Virus-infected mosquitoes through association of environmental characteristics with infected mosquito locations: a case study in Shelby County, Tennessee"</p><p>http://www.ij-healthgeographics.com/content/7/1/12</p><p>International Journal of Health Geographics 2008;7():12-12.</p><p>Published online 29 Mar 2008</p><p>PMCID:PMC2322965.</p><p></p