將生物物理參數整合進行城市熱島效應分析：1997-2022年間，基於衛星數據的曼齊尼 馬察帕（斯威士蘭）時空觀測。

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柯倫(Mdluli Kolunga Nkosinathi) 查詢紙本館藏

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遙測科技碩士學位學程

論文名稱

將生物物理參數整合進行城市熱島效應分析：1997-2022年間，基於衛星數據的曼齊尼馬察帕（斯威士蘭）時空觀測。
(Analyzing Urban Heat Island Effect with Integration of Biophysical Parameters: A Spatial-Temporal Observation from Satellite Data in Manzini-Matsapha, Eswatini, 1997-2022)

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摘要(中)

這項研究結合了遙感數據和方法來分析馬薩帕-曼齊尼的城市化進程，斯威士蘭中部地區（以前稱為斯威士蘭）多年來經歷了巨大的城市化進程，社會經濟指標和自然特徵的變化得到了證實。本研究旨在利用遙感技術調查 Manzini-Matsapha 地區從 1997 年到 2022 年的城市化趨勢和相關環境影響，研究分析了地表溫度 (LST)、歸一化植被指數 (NDVI)、歸一化植被指數 (NDVI)、差異建成指數 (NDBI)、土地利用土地覆蓋 (LULC) 和城市熱島，以了解環境變化和城市擴張之間的相互作用。該研究利用 LULC、LST 和社會經濟數據來形成關於城市化影響的具體而全面的觀點。該研究分析了社會經濟變量，以衡量城市化趨勢，繪製 LULC 地圖以分解其對 LST 的影響，為選定的研究時期繪製 LST 地圖，並將其與兩個生物物理參數 (即 NDVI 和 NDBI) 相關聯。除此之外，該研究還利用植被調整植被指數 (VANUI)，使用 LST 閾值和夜間燈光對 UHI 區域進行分類。該方法利用 1997-1998、2006-2007、2014-2015 和 2021-2022 這四個時間段的衛星圖像進行多時相分析。數據處理包括圖像預處理、NDVI 和 NDBI 的推導、LST 計算和使用其他學者建立的算法進行 LULC 分類。結果顯示，城市區域覆蓋範圍呈增加趨勢，像素間高 LST 差異相應增加，這也表明城市熱島區域有所增加。該研究表明，植被覆蓋率下降、建成區和高地表溫度像素之間存在明顯的關係。這一結果強調了納入綠色空間以減輕城市熱島影響的必要性。該研究面臨一些限制，例如衛星和社會經濟數據的空間分辨率不同以及時間範圍變化很大。鑑於這些，該研究確實為曼齊尼-馬薩法城市化對環境的影響提供了極其有價值的見解。總之，該研究揭示了遙感在監測城市化及其相關環境影響方面發揮的重要作用。通過利用這種動態，可以制定適當的策略來盡量減少這種不利影響。

摘要(英)

This study incorporates remote sensing data and methods to analyze urbanization in Matsapha-Manzini, this central region of Eswatini (formerly known as Swaziland) has undergone tremendous urbanization over the years with a proven growth in socio economic indicators and changes in physical characteristics. This research aims to investigate urbanization trends and the associated environmental impacts in the Manzini-Matsapha area dating back to 1997 until 2022 by employing remote sensing techniques, the research analyzes the land surface temperature (LST), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), land use land cover (LULC) and urban heat islands in a bid to understand the interplay between environmental changes and urban expansion. The research leverages LULC, LST and socio-economic data to develop a concrete and comprehensive view of urbanization impacts. The study analyzed the socio-economic variables to gauge the trend of urbanization, develop LULC maps to break down their influence on LST, develop LST maps for the chosen study periods and correlate them to the two biophysical parameters, namely NDVI and NDBI. Above that, the study classified UHI zones using an LST threshold and night time lights by making use of the vegetated adjusted vegetation index (VANUI). The method made use of a multi-temporal analysis using satellite imagery at four time periods, 1997-1998, 2006-2007, 2014-2015 and 2021-2022. The processing of the data included image preprocessing, derivation of NDVI and NDBI, calculation of LST and LULC classification using established algorithms from other scholars. The result depicted an increasing trend in urban area coverage with a corresponding rise in high LST difference amongst pixels, which also showed a rise in UHI zones. The study showed a clear relationship amongst reduced vegetation coverage, built-up areas and high LST pixels. This result emphasizes on the need for incorporation of green spaces to mitigate UHI effects. The study faced some limitations such as the varying spatial resolutions and largely varying temporal scope of the satellite and socio-economic data. In light to these, the study does provide extremely valuable insights into the environmental impacts of urbanization in Manzini-Matsapha. In conclusion, the study brings forth the vital role that remote sensing plays in monitoring urbanization and the associated environmental impacts. By utilizing such dynamics, appropriate strategies can be developed as to how to minimize such adverse effects.

關鍵字(中)

★ 城市熱島
★ 城市化
★ 地表溫度
★ 社會經濟數據
★ 可見紅外成像輻射計套件 (VIIRS) 夜間燈光
★ Manzini-Matsapha

關鍵字(英)

★ Urban heat islands
★ Urbanization
★ land surface temperature
★ socio-economic data
★ Visible Infrared Imaging Radiometer Suite (VIIRS) Night Time Lights
★ Manzini-Matsapha

論文目次

摘要 I
Abstract III
Acknowledgments V
List Of Figures IX
List of Table X
Abbreviations XI
Chapter 1: Introduction 1
1.1 Urbanization and Environmental issues 1
1.2 Remote sensing and urbanization 2
1.3 Research questions 3
1.4 Aims and Objectives 4
1.5 Scope and limitations of the study 5
1.6 Main contribution of the study 5
1.7 Conceptual framework 6
1.8 Roadmap of the study 6
Chapter 2: Literature review 8
2.1 Urbanization And Urban heat islands 8
2.1.1. Socio-economic Aspects 9
2.2 Description of study area 10
2.2.1. Urbanization in Matsapha-Manzini 10
2.2.2. Matsapha-Manzini 10
2.2.3. Climate 11
2.3 An approach to studying urbanization 12
2.4 Landsat usage in UHI 13
2.5 Remote sensing orbits, systems, wavelengths and resolutions 14
2.6 Resolution: Spatial, temporal, radiometric and spectral 14
2.7 Satellite Orbit and altitude 15
2.8 Landsat 5 Thematic Mapper (TM) 16
2.9 Landsat 8 operational Land Imager 16
2.10 Visible Infrared Imaging Radiometer Suite (VIIRS) Night Time Lights 16
2.11 Vegetation Adjusted Night Urban Index (VANUI) 18
Chapter 3: Materials and Methodology 19
3.1. Tools and methods used 19
3.1.1. Tools used for data processing and analysis 21
3.2. Indicators of urbanization (UHI) 22
3.3. Processing of Landsat imagery 22
3.3.1. Image preprocessing 22
3.4. Development of Land Use Land Cover (LULC) maps 24
3.4.1. Accuracy assessment of LULC and LST Maps 26
3.5. Deriving the Normalized difference Vegetation Index (NDVI) 26
3.6. Deriving the Normalized difference Built-up Index (NDBI) 27
3.7. Calculation of Land Surface Temperatures (LST) 27
3.6.1. Top of Atmospheric Radiance 28
3.6.2. Brightness Temperature 29
3.6.4. Proportion of vegetation (Pv) 30
3.6.5. Land Surface Emissivity (E) 30
3.6.6. Land surface temperature 30
3.8. Classification of Urban Heat Island (UHI) zones 31
Chapter 4: Results and Discussion 33
4.1. Socio-economic indicators of Urbanization 33
4.1.1. Population Growth 33
4.1.2. Net Migration 34
4.1.3. Energy Demand 34
4.2. Remote Sensing derived Variables 36
4.2.1. Land Use Land Cover 36
4.2.2. Derived NDVI and NDBI 39
4.2.3. Land surface temperature 41
4.2.3.1. Assessment of Satellite derived LST against Ground True Values 42
4.2.4. Correlation of LST with NDVI and NDBI 44
46
4.2.5. Association of LST and LULC 46
4.3. UHI Intensity 47
Chapter 5: Conclusion and Discussion 53
5.1. Conclusion of presented results 53
5.2. Future work 55
References 57

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指導教授

林唐煌(Tang-Huang Lin)

審核日期

2024-7-26

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