Vulnerability to Natural Hazards: A Study of Wildfire-Burned Subdivisions in the Wildland-Urban Interface Using Ikonos Imagery and GIS Data
Dissertation by: Uddhab Bhandary
Completed: December 2007
Wildfire threats to homes are increasing in the wildland-urban interfaces of the Western United States. However, little research has been done in community planning issues related to wildfire risk mitigation and systematic evaluation of risk factors based on fire experiences. The objective of this research is to move this process forward by studying a wildfire-burned site integrating high-resolution remote sensing data and GIS data. This research conceptualizes that the wildfire vulnerability of a house is a characteristic of its built environment which is inextricably linked to the natural environment, socioeconomic conditions and planning policies. Accordingly, selected independent variable are: vegetation density, defensible space, road width, road type, parcel size, adjacency of a parcel to public land, morphology, proximity of a house to a fire station, land value, elevation, slope, and aspect. The dependent variable is the probability of a house burning whose response is dichotomous – 1 for burned houses and 0 for unburned houses. Data are processed from IKONOS imageries taken before and after fire, parcel data, and Digital Elevation Models (DEMs) and analyzed in logistic regression. Seven variables are significant in univariate analysis, out of which vegetation density, defensible space, proximity of a house to a fire station and slope are significant in the regression model. Model performance is tested by Receiver Operating Curve (ROC) where Area under Curve (AUC) is 0.91.
Research findings are congruent with widespread wildfire mitigation practices on:
(1) vegetation management; (2) defensible space requirements; and (3) slope. Univariate analysis results emphasizes the need for further study on the relationship between the probability of a house burning and (1) proximity of a house to a fire station; (2) adjacency of parcel to public land; (3) morphology; and (4) road width. This research also recommends the inclusion of roofing material, house density and boundary walls in the future studies. Findings of this research add our understating on how the probability of a house burning changes when a unit-change is made in independent variables. The method applied in this research demonstrates a process of integrating high-resolution remote sensing and GIS data for planners and policy makers to focus in the evaluation of wildfire risk and to develop mitigation measures.
Collaboration and the Bureau of Land Management: Differential Adoption of Community-Based Approaches to Public Lands Planning in the West
Dissertation by: Tamara J. Laninga
Community-based collaboration is the U.S. Bureau of Land Management’s (BLM) preferred approach to land use planning. While some BLM field offices have successfully adopted collaborative planning, others have struggled with its implementation or not yet tried collaborating at all. This dissertation examines institutional, contingency, community capacity, leadership, and group relations theories, and the New West thesis to consider factors that motivate and inhibit BLM field offices from adopting a collaborative planning approach. A two-staged, multiple method research strategy was designed to examine the differential adoption of collaboration.
Stage 1 consisted of a survey sent to BLM field staff in all 146 field offices to provide a comprehensive picture of where collaboration is being used. Field offices responding to the survey (n=89) served as the sample frame from which four case studies were drawn for Stage 2 of the study.
In this stage, BLM staff and stakeholders were interviewed in field offices selected for their adoption or non-adoption of collaboration and their location in the New or Old West. The survey data supports the New West thesis, showing that adoption of collaboration is more likely in field offices located in counties experiencing population growth, with diversified economies and high levels of community capacity (human capital). This finding, however, does not explain all the variation in the use of collaboration, since some field offices in the Old West are adopting collaboration and some field offices in the New West are not adopting this planning process.
The case study data clarifies this discrepancy and provides support for the community capacity and leadership theories. The case studies showed that field offices are likely to adopt collaboration, regardless of being in the New or Old West, where there is a visionary leader working in communities with high community capacity (social capital). The ability of BLM field offices to adopt community-based collaboration seems especially hindered by overbearing procedural and legal requirements, ineffective leadership, and low social capital.
Remote Sensing Application for Environmental Management
Dissertation by: Chengmin Hsu
Expected Completion: May 2009
This dissertation is a synthesized report depicting applications of the various geo-spatial technologies and models for the purpose of environmental management. The applied technologies include Geographic Information Systems, Remote Sensing, Statistical Analysis, and Multi-Criteria Evaluation. The Earth is a dynamic and intricate system. The creation of some environmental models requires execution of complex sets of mathematical functions that represent physical processes such as groundwater movement or the water cycle. Many of these natural phenomena cannot be expressed by logical or numerical equations. Parametric methods are difficult to use in these complex and non-linear situations where attributes are not normally distributed. Therefore, this dissertation involves the application of the Integrated Decision Tree and the numerical model, which are used in order to develop a model for the forecasting of the social route change and the understanding of its impacts on watershed hydrology.
The important chapters of this dissertation are listed below:
- Colorado environmental geo-database
- Multi-criteria wetland mapping using an integrated pixel-based and object-based classification approach
- The creation of trail inventory using an object-based hierarchic classification algorithm
- Forecasting the ATV trail increase in open space by an integrated numerical and decision tree model
- Watershed Soil Moisture Modeling
- A multimodel ensemble forecast framework—application to spring seasonal flows in the San Pedro River Basin