Theses and Dissertations from UMD
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Item Monitoring Aboveground Biomass in Forest Conservation and Restoration Areas Using GEDI and Optical Data Fusion(2024) Liang, Mengyu; Duncanson, Laura I; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Forests play a critical role in the global carbon cycle by sequestering carbon in the form of aboveground biomass. Area-based conservation measures, such as protected areas (PAs), are a cornerstone conservation strategy for preserving some of the world's most at-risk forest ecosystems. Beyond PAs, tree planting and forest restoration have been lauded as solutions to combat climate change and criticized as ways for polluters to offset carbon emissions. Consistent monitoring and quantification of forest restoration can impact decisions on future restoration activities. In this dissertation, I utilized a fusion of remote sensing assets and a combination of remote sensing with impact assessment techniques, to obtain objective baseline information for reconstructing past forest biomass conditions, and for monitoring and quantifying the patterns and success of forest regrowth in areas that underwent different forest management interventions. This overarching research goal is approached in three studies corresponding to chapters 2-4. In chapter 2, PAs’ effectiveness in storing biomass carbon and preserving forest structure is assessed on a regional scale using Global Ecosystem Dynamics Investigation (GEDI) lidar data in combination with a counterfactual analysis using statistical matching. This chapter provides an assessment of the reference condition of the biomass carbon storage capacity by one of the most stringent forest management means. The study finds that analyzed PAs in Tanzania possess 24.4% higher biomass densities than their unprotected counterparts and highlights that community-governed PAs are the most effective category of PAs at preserving forest structure and aboveground biomass density (AGBD). In chapter 3, empirical models are developed to link current (2019-2020) AGBD estimates from the GEDI with Landsat (2007-2019) at a regional scale. This will allow both current wall-to-wall biomass mapping and estimation of biomass dynamics across time. We demonstrate the utility of the method by applying it to quantify the AGBD dynamics associated with forest degradation for charcoal production. In chapter 4, the same modeling framework laid out in chapter 3 will be used to derive AGBD trajectories for 27 forest restoration sites across three biomes in East Africa. To assess the effectiveness of and compare Assisted Natural Regeneration (ANR) and Active Restoration (AR) in enhancing forest AGBD growth compared to natural regeneration (NR), we used staggered difference-in-difference (staggered DiD) to analyze the average annual AGBD change. We controlled for pre-intervention AGBD change rate between AR/ANR and NR and estimated the effectiveness with explicit consideration of intervention duration. This study finds that AR and ANR outperform NR during long-term restoration. Using the most suitable restoration interventions in each biome and timeframe, 4% suitable areas could enhance 2.40 ± 0.78 Gt (billion metric tons) forest carbon uptake over 30 years, equivalent to 3.6 years of African-wide emissions. Overall, this dissertation develops remote sensing methodological frameworks for using GEDI data and its fusion with Landsat time series to quantify and monitor forest AGBD. Moreover, by combining remote sensing-derived AGBD dynamics with impact assessment techniques, such as statistical matching and staggered DiD, the dissertation further assesses and compares different conservation and restoration means’ effectiveness in increasing AGBD and carbon uptake in forests. The dissertation therefore advances the applications of state-of-the-art remote sensing data and techniques for sustainably managing forests towards climate mitigation targets.Item ESSAYS ON ENERGY EFFICIENCY AND FOREST CONSERVATION(2015) Maher, Joseph Andrew; Just, Richard; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation is composed of three essays in environmental economics related to residential energy efficiency and forest conservation. My first paper assesses the effectiveness of energy-efficient technologies in the setting of a utility rebate program. To date, the energy savings from energy-efficiency building retrofits are assessed using ex-ante engineering models. My analysis provides the first evaluation of engineering models that uses residential billing data, combined with data on observable characteristics of each residence, to assess the accuracy of engineering predictions across nine retrofit technologies used in Gainesville, Florida. My second essay presents the first causal evidence that trees have a major impact on consumer demand—with large shade trees reducing household electricity use by more than 20 percent. This work contributes to the existing literature on the energy saving potential of urban forests by implementing a quasi-experimental design to identify a causal link between tree shade and energy use. Results suggest that the energy savings from tree shade are an order of magnitude greater than other energy-efficiency policy measures, providing new evidence that tree ordinances may serve as effective demand-side management policies. My third essay assesses the effectiveness of forest conservation policies in reducing carbon emissions from deforestation. To date, the effectiveness of protected areas has been assessed using cross-sectional methods. In this essay, new quasi-experimental models using panel data on annual deforestation are used to reveal new insights into the importance of government oversight of protected areas with findings that counter economists’ prior notions of the avoided deforestation of new parks. I extend the analysis to estimate avoided carbon emissions, a key policy metric that varies considerably from deforestation trends.