博碩士論文 110022601 詳細資訊




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姓名 安亞迪(Adi Ankafia)  查詢紙本館藏   畢業系所 遙測科技碩士學位學程
論文名稱 衛星遙測印度尼西亞邦加島 Namang 村Pelawan 紅菇 (Heimioporus sp.)的產量
(Remote Sensing of Pelawan Red Mushroom Yield (Heimioporus sp.) in Namang Village, Bangka Island, Indonesia)
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摘要(中) 摘要
Pelawan 紅蘑菇(Heimioporus sp.)是一種食用菌,作為外生菌根真菌存在於 Pelawan 樹 (Tristaniopsis merguensis) 的根系中,是生態系中相當重要的資源。邦加島為 印尼的主要產地之一,但尚未正確記錄當地蘑菇的潛在種質資源。本研究旨在提供有
關使用衛星遙測技術估算 Namang 村 Pelawan 紅蘑菇的產量。由於這種蘑菇與寄主的
檳榔樹共生,因此需要先進行地表物種分類以確認檳榔樹面積,還有植被指數,如檳 榔樹面積的 NDVI (Normalized Difference Vegetation Index),EVI (Enhanced Vegetation Index)和 SAVI (Soil Adjusted Vegetation Index),並藉由葉面積指數(Leaf Area Index, LAI)和植被指數之間的相關性,進行每年 Pelawan 紅蘑菇產量的估算。研究結果顯示,
基於 LAI-NDVI 和 LAI-EVI 相關性的估計產量與實際產量間差異的均方根誤差 (RMSE) 值在 2018 年和 2021 年分別為 0.12 和 0.11,表示產量估算模式具有相當的準確性和可
靠性,適合實際應用。
關鍵詞:土地利用、Pelawan 樹、Pelawan 紅蘑菇、遙測產量、LAI

i
摘要(英) Abstract
One of the potential germplasms that has not been properly recorded on Bangka Island is indigenous mushrooms, namely Pelawan red mushrooms (Heimioporus sp.) and their potential uses. Pelawan red mushroom is a type of edible fungus that is found in the root system of Pelawan trees (Tristaniopsis merguensis) as an ectomycorrhizal fungus. Research on Pelawan red mushrooms related to yield estimation has never been carried out. This research aimed to provide information related to yield estimation of Pelawan red mushrooms in Namang Village using a remote sensing approach. The observation was conducted 2 times in 2018 and 2021. Because this mushroom exists in symbiosis with Pelawan trees as the host tree, firstly, it is necessary to determine LULC to mark the Pelawan trees area, also vegetation index, including NDVI, EVI, and SAVI in the Pelawan trees area, so that the existing area can help in yield estimation of Pelawan red mushroom for each year. The yield estimation model approach used the correlation between Leaf Area Index (LAI) and the vegetation index. The evaluation demonstrated that Root Mean Squared Error (RMSE) values, which represent the difference between the actual yield and the estimated yield based on the LAI - NDVI and LAI - EVI correlations, were consistently 0.12 and 0.11 in both 2018 and 2021. This indicates the high accuracy and reliability of the estimated models, making them suitable for practical applications. Additionally, Mean Absolute Percentage Error (MAPE) values for the LAI - NDVI correlation were 28.25% in 2018 and 23.23% in 2021, while for the LAI - EVI correlation, the MAPE values were 27.33% in 2018 and 21.44% in 2021. These values further reinforce the notion that the estimation models fall within the range of reasonable estimation, affirming their validity and effectiveness.
Keywords: LULC, Pelawan Trees, Pelawan Red Mushroom Yield Estimation, LAI, Remote Sensing.

ii
關鍵字(中) ★ 土地利用
★ Pelawan 樹
★ Pelawan 紅蘑菇
★ 遙測產量
★ LAI
關鍵字(英) ★ LULC
★ Pelawan Trees
★ Pelawan Red Mushroom
★ Yield Estimation
★ LAI
★ Remote Sensing
論文目次 Table of Contents
摘要 ..................................................................................................................i Abstract .............................................................................................................ii Acknowledgment...............................................................................................iii Table of Contents ..............................................................................................iv List of Figures ...................................................................................................vi List of Tables ....................................................................................................viii CHAPTER I INTRODUCTION ........................................................................1
1.1. Background ................................................................................1 1.2. Research Problem and Objective.................................................5 1.2. Thesis Outline.............................................................................6
CHAPTER II LITERATURE REVIEW ............................................................7 2.1 Nomenclature and Local Name ....................................................7 2.1.1. Pelawan Tree (Tristaniopsis merguensis)...............................7 2.1.2. Pelawan Red Mushroom (Heimioporus sp.) ...........................9
2.2. Remote Sensing of Vegetation ....................................................11 2.3. Land Use and Land Cover (LULC) .............................................13 2.4. Maximum Likelihood Classification (MLC) ...............................14 2.5. Accuracy Assessment .................................................................15 2.6. Vegetation Index (VI).................................................................15
2.6.1. Normalized Difference Vegetation Index (NDVI)..................16 2.6.2. Enhanced Vegetation Index (EVI) .........................................16 2.6.3. Soil Adjusted Vegetation Index (SAVI).................................17
2.7. Leaf Area Index (LAI) ................................................................17 2.8. Landsat 8 OLI/TIRS Satellite Imagery ........................................19 2.9. Related Works ............................................................................20
CHAPTER III STUDY AREA AND METHODS .............................................22 3.1. Study Area..................................................................................22 3.2. Dataset........................................................................................26 3.3. Methods......................................................................................27
3.3.1. Landsat 8 OLI/TIRS Pre-Processing ......................................27 3.3.2. Determine Land Use and Land Cover (LULC) Type..............29 3.3.3. Supervised Image Classification ............................................29
iv
3.3.4. Map Accuracy Assessment ....................................................30
3.3.5. Vegetation Index (VI) Calculation .........................................32 3.4. Leaf Area Index (LAI) Calculation ............................................35 3.5. Yield Estimation Model .............................................................36 3.6. Evaluation of Yield Estimation Model ........................................37 3.7. Research Workflow ...................................................................40
CHAPTER IV RESULTS AND DISCUSSION.................................................41 4.1. Results and Discussion................................................................41 4.1.1. Land Use and Land Cover Classification ...............................41 4.1.2. Land Use and Land Cover Changes .......................................41 4.1.3. Accuracy Assessment of LULC .............................................43 4.1.4. NDVI Condition in the Study Area ........................................44 4.1.5. EVI Condition in the Study Area ...........................................46 4.1.6. SAVI Condition in the Study Area.........................................48 4.2. LAI of Pelawan Tree...................................................................52 4.3. Correlation Between Leaf Area Index and Vegetation Index.......54 4.4. Yield Estimation Model of Pelawan Red Mushroom...................55 4.5. Comparisons of Yield Estimation Models ...................................58 4.6. Correlation Between Actual Yield and Climatic Parameters........60 CHAPTER V CONCLUSIONS, LIMITATIONS, AND FUTURE WORKS.....63 5.1. Conclusions ................................................................................63 5.2. Limitations .................................................................................64 5.3. Future Works..............................................................................66 References .........................................................................................................69
v
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指導教授 林唐煌(Tang-Huang Lin) 審核日期 2023-8-8
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