Population living along the coast are at risk of losing land, households, and economic resources due to the hazards of coastal erosion. Scientific research has indicated that 70% of the planet's sandy coastal environment is being impacted by coastal erosion. Due to the different characteristics of the lands in the coastal zone versus other areas, it is important to understand how the hazard of shoreline erosion contributes to subsequent land use change in affected coastal regions. This study analyzes how the level of erosion, land loss, and developed land loss performs when added with the default land use change parameters such as existing developed land proximity, proximity to forested areas, population, transportation, etc. Sample points of 1020 from 10 years and 15 years of shoreline erosion data for the lower Meghna River estuary of Southeast Bangladesh have been obtained and from there, different erosion statistics have been developed. Developed land use data has been collected from ESA's World Settlement Footprint dataset and other datasets are also collected from secondary data sources. Logistic regression modeling shows that there are verified contributions of proximity to erosion and amount of land loss with the probability of developed land use conversion in the study area. Adding the variables of environmental hazards increases the prediction accuracy by 2-3% and overall, the models are at least 85% accurate. / Master of Science / Population living along the coast are at risk of losing land, households, and economic resources due to the hazards of coastal erosion. The coast of the Lower Meghna estuary in Bangladesh is a region experiencing chronic and severe shoreline erosion that causes the land to be lost to estuarine waters. This research quantifies the amount of land lost to erosion with a special focus on the amount of developed land that is lost. Developed land in this study is defined as a built-up area typically composed of buildings and roads. The research also evaluates the effects of lost land on the subsequent conversion of interior land from a non-developed to developed status. The main contribution is to quantitatively identify the association between the erosion-induced land loss to future land use conversion. Using statistical modeling and digital mapping methods, results show that loss of land is associated with the subsequent conversion of non-developed land to developed land use. In particular, conversion has a higher probability at sites that are located more distant from the eroding shoreline that also are proximal to shoreline sites with higher rates of erosion-induced land loss. These results are suggestive of a relocation process where previously lost developed land is reestablished at interior sites within five kilometers of the eroding shoreline.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第24221号 / 工博第5049号 / 新制||工||1788(附属図書館) / 京都大学大学院工学研究科都市環境工学専攻 / (主査)教授 清水 芳久, 教授 米田 稔, 准教授 松田 知成 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Forest degradation is a significant yet underestimated source of carbon emissions. Traditionally, monitoring forest degradation has been difficult due to a lack of sufficiently frequent satellite observations and reliable analysis methods. Recent advancements in satellite remote sensing provide new opportunities to monitor, attribute and analyze forest degradation. This dissertation develops methods to monitor and attribute forest degradation and analyzes the spatial-temporal patterns of forest degradation and associated carbon emissions. A new method, Continuous Change Detection and Classification - Spectral Mixture Analysis (CCDC-SMA), was developed on Google Earth Engine (GEE) to monitor abrupt and gradual forest degradation in temperate climate zones using Landsat time series. CCDC-SMA was applied to the Republic of Georgia from 1987-2019. Results show that forest degradation affected a much larger area than deforestation. In addition, CCDC-SMA was extended to monitor forest degradation in the tropics and applied in Laos. Attribution of the drivers of forest degradation was based on a combination of CCDC-SMA results, post-disturbance land cover classification and object-based image analysis. Shifting cultivation is the largest kind of forest disturbance in Laos, affecting 32.9% ± 1.9% of Laos during 1991-2020. The results show that shifting cultivation has been expanding and intensifying in Laos, especially in the last five years. Furthermore, the length of fallow periods has been continuously declining, which indicates that shifting cultivation is becoming increasingly unsustainable. Combining biomass estimates from the Global Ecosystem Dynamics Investigation (GEDI) and area estimates of shifting cultivation, the net carbon emissions from shifting cultivation during 1991-2020 in Laos are 1.28 ± 0.12 petagrams of CO2 equivalent (Pg CO2 eq). Tree canopy height and aboveground biomass density are strongly correlated with the years of regrowth since the latest year of slash-and-burn activities, which can be expressed using logarithmic models. It takes 131 years for the biomass to recover to pre-disturbed levels based on the logarithmic models. In addition to advancements in remote sensing of forest degradation, the results of this dissertation provide valuable information for policy related to forest management and reduction of carbon emissions.

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京都大学 / 新制・課程博士 / 博士(地球環境学) / 甲第24058号 / 地環博第221号 / 新制||地環||42(附属図書館) / 京都大学大学院地球環境学舎地球環境学専攻 / (主査)教授 柴田 昌三, 准教授 深町 加津枝, 教授 西前 出 / 学位規則第4条第1項該当 / Doctor of Global Environmental Studies / Kyoto University / DFAM