Physical and Environmental Geography Commons^™

Assessing Flood Resilience In West Virginia Communities: Integrating Physical, Institutional, Socioeconomic, And Environmental Dimensions, Anahita Mahmoudi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Flooding is one of the most frequent and damaging natural hazards in the United States, with impacts expected to intensify under changing climate conditions. In regions such as West Virginia, complex terrain, development patterns along river corridors, and socioeconomic disparities contribute to elevated flood risk. Traditional approaches to flood risk assessment often focus on single dimensions of vulnerability or rely on binary floodplain maps, which do not fully capture the spatial variability and multidimensional nature of flood resilience.

This dissertation develops an integrated, community-scale framework for assessing flood resilience in West Virginia by combining physical, environmental, institutional, and socioeconomic dimensions …

Climate Change In Gilgit-Baltistan: Satellite-Based Land Use/Land Cover Change Detection, Socio-Economic Dimensions, And Adaptation Strategies, Ali Muhammad

Graduate Theses/Dissertations

Climate change is increasingly transforming the cryosphere, hydrology, and human landscape of Gilgit-Baltistan, a highly climate-sensitive mountain region in northern Pakistan. This thesis investigates these transformations through satellite-based land use/land cover (LULC) change detection in four representative tehsils of Gilgit-Baltistan—Ali Abad, Gilgit, Nagar, and Sikander Abad—selected to span a gradient of human pressure and cryospheric exposure within the region. Using summer, cloud-free (< 10%) imagery from USGS Landsat 7 (2000) and Landsat 8 (2025), it conducts a multi-temporal comparison of environmental and socio-spatial change. After atmospheric correction and band compositing, the imagery is classified in ArcGIS Pro into six classes—Water, Barren land, Vegetation, Snow, Glacier, and Built-up—using a Support Vector Machine (SVM) classifier, with Maximum Likelihood Classification and Random Forest also tested but found less suitable for the final workflow. The analysis detects a pronounced reduction in mapped glacier-class area alongside a comparatively stable snow class, together with built-up expansion, while examining how temperature, precipitation, tourism, and population dynamics relate to observed LULC transitions. The results reveal a pattern of cryospheric decline and urban growth, with implications for water availability, ecological stability, hazard exposure, and settlement pressure. By integrating geospatial change detection with climatic and socio-economic interpretation, the thesis moves beyond mapping to explain interacting environmental and human drivers of landscape transformation and provides a reproducible remote-sensing baseline for monitoring land-surface change in heterogeneous mountainous terrain. It recommends integrated water-resource management, climate-resilient land-use planning, watershed and glacier monitoring, and sustainable tourism governance, supporting evidence-based decision-making by the Government of Gilgit-Baltistan and organizations working on climate adaptation, disaster risk reduction, and sustainable regional development.

An Ex-Post Analysis Framework For Assessing The Effectiveness And Driving Factors Of Green Building Certification Adoption: A Case Study Of Singapore, Hao Gu, Xiaoyu Jin, Fu Xiao, Maomao Hu, Clayton Miller

Research Collection College of Integrative Studies

Cities worldwide are adopting green building certification policies to meet sustainability and decarbonization targets in the building sector. However, the effectiveness of green certifications remains contested due to the difficulty of decomposing multiple influencing factors on building energy consumption. This study proposes an econometrics-based ex-post analysis framework to assess the effectiveness of green building certification policies in energy savings and identify driving factors by decomposing multiple influential factors. The proposed framework incorporates time-fixed effect models to examine factors driving the adoption of green building certifications, and causality analysis to quantify the effectiveness. Applying the framework to analyze a panel dataset …