DSpace collection: 博碩士論文

應用無人機多光譜影像於藻礁之分析;Application of UAV-Based Multispectral Imagery for the Analysis of Algal Reefs

title: 應用無人機多光譜影像於藻礁之分析;Application of UAV-Based Multispectral Imagery for the Analysis of Algal Reefs abstract: 桃園藻礁為臺灣沿岸珍貴且具代表性的潮間帶生態地形，兼具地質、景觀與生態價值。然而，藻礁環境長期受到覆沙作用之影響，其礁體分布範圍與表層藻類生長狀態容易隨環境條件而變動。傳統藻礁監測方式多仰賴人工現地調查，調查工作常受限於潮汐時段與天候條件，亦難以同時掌握大範圍且具高空間解析度之變化特徵。為提升潮間帶藻礁監測之效率與空間解析度，本研究結合無人機（Unmanned Aerial Vehicle, UAV）與多光譜遙測技術，採用P4 Multispectral（P4M）無人機，於桃園大潭 G1 區域進行兩個時期之多光譜影像航拍與分析。研究流程包含影像蒐集、影像前處理、人工圈選藻礁之可視裸露分布範圍、植生指數計算與資料分析等階段，並利用 Pix4Dmapper 影像處理軟體進行幾何與相對輻射校正，建立具地理參考之多波段正射影像（GeoTIFF）。後續於 ArcGIS 地理資訊軟體中計算 NDVI、NDRE、SAVI、OSAVI、MSAVI、NDWI 與 EVI 指數，以比較藻礁與覆沙區域之光譜差異特性。研究結果顯示，多光譜影像能有效呈現藻礁與覆沙區域之光譜差異，其中紅邊（Red Edge）與近紅外（NIR）波段對藻礁表層反射特徵具較高敏感性；NDVI 與 NDRE 指數於藻礁分布分析中表現相對穩定，適合用於區域尺度之相對比較。本研究驗證 UAV 多光譜影像應用於潮間帶藻礁監測之可行性，並建立一套具實務可行性之分析流程，可作為未來藻礁長期監測與沿岸生態保育之技術應用參考。;The Taoyuan algal reefs are a valuable and representative intertidal geomorphic feature along the coast of Taiwan, possessing important geological, landscape, and ecological significance. However, the algal reef environment has long been affected by sand burial processes, causing the spatial distribution of reef bodies and the growth conditions of surface algae to vary with environmental conditions. Traditional monitoring of algal reefs relies mainly on field surveys, which are constrained by tidal conditions and weather, making it difficult to simultaneously capture large-area changes with high spatial resolution. To improve the efficiency and spatial resolution of intertidal algal reef monitoring, this study integrates unmanned aerial vehicle (UAV) technology with multispectral remote sensing. A P4 Multispectral (P4M) UAV was used to acquire multispectral imagery over the G1 area of Datan, Taoyuan, during two survey periods. The research workflow includes image acquisition, image preprocessing, manual delineation of visually exposed algal reef areas, vegetation index calculation, and data analysis. Geometric correction and relative radiometric correction were performed using Pix4Dmapper to generate georeferenced multispectral orthomosaic images (GeoTIFF). Subsequently, vegetation and water-related indices—including NDVI, NDRE, SAVI, OSAVI, MSAVI, NDWI, and EVI—were calculated in ArcGIS to compare the spectral characteristics of algal reef and sand-covered areas. The results indicate that multispectral imagery can effectively reveal spectral differences between algal reefs and sand-covered substrates. Among the spectral bands, the red-edge (Red Edge) and near-infrared (NIR) bands exhibit higher sensitivity to the surface reflectance characteristics of algal reefs. In addition, the NDVI and NDRE indices show relatively stable performance in analyzing the spatial distribution of algal reefs and are suitable for regional-scale comparative analysis. This study demonstrates the feasibility of applying UAV-based multispectral imagery for monitoring intertidal algal reef environments and establishes a practical analysis workflow. The proposed approach can serve as a technical reference for future long-term algal reef monitoring and coastal ecological conservation applications.

建立氣象和植物因子與不同深度土壤水分之間的多元線性迴歸模型;Establishing a Multiple Linear Regression Model Relating the Meteorological and Plant Factors to Soil Moisture at Various Depths

title: 建立氣象和植物因子與不同深度土壤水分之間的多元線性迴歸模型;Establishing a Multiple Linear Regression Model Relating the Meteorological and Plant Factors to Soil Moisture at Various Depths abstract: 在水稻生長過程中，土壤含水量的多寡扮演關鍵的角色，直接影響作物的生長和產量。本研究主要探討氣象因子（淨輻射、氣溫或潛勢能蒸發散量）及植物因子（作物係數）對水稻不同生長期於不同深度土壤水分日消耗量的影響。本研究以桃園市觀音一處農地2023年二期作水稻種植時段的觀測資料建立了多元線性迴歸模型，以探討植物和氣象因子對不同深度土壤水分的影響。由迴歸結果可觀察出水稻根系對20公分深度土壤水分日下降速率相較於其他深度有顯著影響，可有效反映水稻根系於此深度附近較為密集。而氣象因子的影響在30至40公分深度處趨於穩定，反映地表能量對土壤水分的影響於此深度附近較弱。將多元線性迴歸模型計算的熱擴散率與阻尼深度，與利用實際量測的土壤溫度資料所計算的數值進行比較，結果顯示，透過相位法所得的平均熱擴散係數為0.5956×10?6 m?/s，而振幅法的平均熱擴散係數為0.6023×10?6 m?/s，兩者數值接近。同時，根據氣象因子為氣溫、淨輻射與潛勢能蒸發散的隨深度衰減係數（?

融合地理加權回歸與多目標空間最佳化之作物區位配置研究;Integrating Geographically Weighted Regression with Multi-Objective Spatial Optimization for Crop Allocation

title: 融合地理加權回歸與多目標空間最佳化之作物區位配置研究;Integrating Geographically Weighted Regression with Multi-Objective Spatial Optimization for Crop Allocation abstract: 本研究旨在探討氣候變遷情境下，如何透過融合地理加權回歸（GWR）與非支配排序基因演算法（NSGA-II），建立一套具空間解釋力與決策導向性的多目標作物區位配置模式。研究範圍涵蓋臺灣西部13縣市，選取稻米、花生與甘藷為示範作物，於466個5公里解析度網格中評估四個目標：作物總產量、農家收益、適栽度與空間緊湊度，並設定產量不得低於2018–2022年國內平均值之限制條件。氣候資料來源為臺灣氣候變遷推估資訊與調適知識平台(Taiwan Climate Change Projection Information and Adaptation Knowledge Platform, TCCIP)提供之26項1960–2022年指標，經主成分分析（PCA）降維後擷取7個主成分，累積解釋變異量達82%。GWR模型結合主成分與作物生產力建構空間回歸模型，修正R^2提升達157.8至989.4%，AICc下降5.7–9.9%，並有效消除殘差空間自相關（Moran’s I趨近於0），顯示模型能準確捕捉氣候與生產力間的空間異質性。進一步以GWR預測結果作為NSGA-II輸入資料，於800個種群與600世代中進行多目標演化求解，結果顯示GWR-NSGA在超體積（HV）與解多樣性指標上優於不含GWR的基準模式（TC-NSGA），其中稻米配置比例穩定占據主導地位（約64–67%），花生占比則較初始值顯著提升（16%至約24%）。本研究證實氣候主成分與空間回歸模型能有效輔助作物區位規劃，所建立之整合模式具備良好解釋力與實務應用潛力，適合作為未來氣候調適與農業空間規劃之決策支援工具。未來建議進一步提升空間解析度、引入多尺度GWR與非氣候因子，以及優化演算法參數與比較其他演化法，以增進模型精度與穩定性。;This study proposes an integrated framework combining Geographically Weighted Regression (GWR) and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to optimize multi-objective crop allocation under climate change scenarios. The study area includes 13 counties in western Taiwan, with rice, peanuts, and sweet potatoes selected as target crops. A total of 466 feasible 5-km spatial grid units were established, and four objectives were evaluated: total crop production, farm profit, land suitability, and spatial compactness. Constraints were imposed to ensure each crop’s production met or exceeded the national average from 2018 to 2022. Climate data, including 26 variables from 1960–2022 provided by TCCIP, were reduced to seven principal components (PCs) using Principal Component Analysis (PCA), explaining 82% of the total variance. GWR models incorporating these PCs significantly improved model performance over ordinary least squares (OLS), with adjusted R² increasing by 157.8%–989.4%, AICc decreasing by 5.7%–9.9%, and residual Moran’s I approaching zero. The GWR-estimated crop productivity was then integrated into the NSGA-II optimization process (800 population size, 600 generations). Results show that the GWR-based NSGA-II model outperforms the baseline (TC-NSGA) in hypervolume (HV) and diversity metrics. Rice maintained a dominant allocation proportion (64–67%) across all optimal solutions, while the peanut share increased from 16% to approximately 24% post-optimization. The proposed method demonstrates strong spatial explanatory power and practical value in supporting climate-resilient crop planning. Future work should focus on finer-scale spatial data, incorporation of multi-scale GWR, inclusion of non-climatic factors, and algorithm benchmarking to further enhance model accuracy and robustness.

雨水貯集於臺灣各縣市水稻灌溉與民生用水之經濟可行性與兼具減洪效用之評估;Evaluating the County-level Economic Feasibility and Flood Mitigation Benefits of Rainwater Harvesting for Paddy Irrigation and Domestic Water Use in Taiwan

title: 雨水貯集於臺灣各縣市水稻灌溉與民生用水之經濟可行性與兼具減洪效用之評估;Evaluating the County-level Economic Feasibility and Flood Mitigation Benefits of Rainwater Harvesting for Paddy Irrigation and Domestic Water Use in Taiwan abstract: 近年來，臺灣受氣候變遷影響，極端氣象事件頻繁發生，其中乾旱造成的水資源短缺對農業尤其水稻灌溉構成嚴峻挑戰；而已有相當多應用說明雨水貯集系統具有提升水資源系統韌性並降低旱澇風險之功能。本研究旨在評估不同雨水貯集系統容量、集水與供水情境在臺灣各縣市水稻田區域之供水穩定性、經濟可行性與其兼具減洪效用三方面之整體效益，作為因應氣候變遷下缺水與淹水之策略。本研究採用「溢流後取水（Yield-After-Spillage, YAS）」模式，並以供水量、體積可靠度、滿足天數與時間可靠度四項指標，評估雨水貯集系統對農業灌溉與非期作期間民生用水之供水能力；同時結合未來氣候變遷情境（SSP2-4.5 與 SSP5-8.5）進行供水效益之推估，並以淨現值（Net Present Value, NPV）與投資回本期（Payback Period, PBP）分析經濟可行性。結果顯示，北部地區因全年降雨分布較均勻，於一期與二期稻作皆展現較高之供水可靠度；南部、中部與東部地區則於二期稻作期間供水效益較佳。於全年降雨皆用於民生之情境下，多數北部與東部地區即使僅配置10 m³之雨水桶，即可達到90%可靠度。未來降雨趨於極端化，將導致供給一期作之潛能下降，二期則可能提升；民生用水部分，未來純雨水桶情境供水都增加，而因降雨集中使多數屋頂集水情境產生溢流後供水量較基期減少，僅有少數北部縣市在600 m²配置較大雨水桶時供水量增加。經濟分析方面，於現況水價情境下，多數情境難以達成回本，當採用農業用水戶願付價格進行評估時，回本潛力提升。減洪方面，採用合理化公式模擬逕流量，以滯留體積比評估各重現期設計暴雨下系統滯洪能力。模擬結果顯示，多數縣市選擇適當容量後可完全滯留該集水面積下延時90分鐘之暴雨逕流，然而減洪所需容量與供水導向配置存在差距。本研究建議未來可強化制度誘因與區域化設計，以提升雨水貯集系統於農業水資源調適政策中的應用潛力與推廣成效。;In recent years, Taiwan has experienced increasingly frequent extreme weather events due to climate change, with droughts posing significant challenges to agricultural irrigation, especially for rice cropping. Rainwater harvesting (RWH) systems, as a nature-based solution (NbS), have gained attention for their potential to enhance water resilience and mitigate both drought and flood risks. This study evaluates the overall effectiveness of RWH systems across Taiwan’s rice paddy regions, focusing on water supply reliability, economic feasibility, and flood mitigation potential under future climate scenarios.The Yield-After-Spillage (YAS) model was applied, and four indicators—water supply, volume reliability, satisfaction in time, and time reliability—were used to assess the performance of RWH systems for both agricultural irrigation and domestic use during non-cropping seasons. Among domestic-use scenarios, only scenario 4, which assumes year-round rainfall usage, was selected for detailed analysis due to its consistent rainfall distribution. Various tank capacities, catchment sizes, and daily water demand rates were evaluated across counties under SSP2-4.5 and SSP5-8.5 climate pathways. Economic feasibility was assessed using Net Present Value (NPV) and Payback Period (PBP). Results show that northern Taiwan, benefiting from more evenly distributed rainfall, generally achieves higher supply reliability in both the first and second cropping , while central, southern, and eastern regions perform better during the second cropping. For domestic use under Scenario 4, most northern and eastern counties achieve over 90% volumetric reliability even with just a 10 m³. However, performance differences emerge between collection types: while pure RWH systems with small catchments tend to benefit from future, roof area catchments with larger areas often face overflow losses due to concentrated storms, resulting in reduced supply efficiency—especially with smaller tanks. Only a few northern counties showed improved supply under the 600 m² roof area catchment with larger tanks. Economic analysis reveals that under current water pricing, most systems are not financially viable; however, when using a willingness-to-pay for agricultural water, payback potential improves, especially in northern counties with stable rainfall and eastern counties with high irrigation demand. For flood mitigation, the Rational Method was used to estimate runoff, and detention effectiveness was assessed based on retention volume ratios under different return periods. Simulation results indicate that many counties can fully retain 90-minute design storm runoff with properly sized systems, though the capacity needed for flood control often exceeds that for water supply. In conclusion, rainfall amount alone does not guarantee effective water supply; system performance is governed by the timing, intensity, and spatial distribution of rainfall, as well as system capacity and demand matching. This study highlights the importance of integrating climate-adaptive design and region-specific strategies, suggesting that institutional incentives and spatial planning will be key to promoting RWH systems as viable tools in Taiwan’s agricultural water resource adaptation policies.