請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/55494完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 莊振義(Jehn-Yih Juang) | |
| dc.contributor.author | Wei-Jhe Chen | en |
| dc.contributor.author | 陳緯哲 | zh_TW |
| dc.date.accessioned | 2021-06-16T04:05:38Z | - |
| dc.date.available | 2020-08-21 | |
| dc.date.copyright | 2020-08-21 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-08-19 | |
| dc.identifier.citation | Akdağ, S. A., Ö, G., Yağci, E. (2013). Wind speed extrapolation methods and their effect on energy generation estimation. International Conference on Renewable Energy Research and Applications (ICRERA). Benoit, R. (1977). On the Integral of the Surface Layer Profile-Gradient Functions. Journal of Applied Meteorology, 16, 859-860. Blazejczyk, K., Epstein, Y., Jendritzky, G., Staiger, H., Tinz, B. (2012). Comparison of UTCI to selected thermal indices. Int J Biometeorology, 56(3), 515-535. doi:10.1007/s00484-011-0453-2 Blocken, B., Stathopoulos, T., van Beeck, J. P. A. J. (2016). Pedestrian-level wind conditions around buildings: Review of wind-tunnel and CFD techniques and their accuracy for wind comfort assessment. Building and Environment, 100, 50-81. doi:10.1016/j.buildenv.2016.02.004 Carlson, T. N., Arthur, S. T. (2000). The impact of land use land cover changes due to urbanization on surface microclimate and hydrology a satellite perspective. Global and Planetary Change, 25, 49–65. Chen, X.-L., Zhao, H.-M., Li, P.-X., Yin, Z.-Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment, 104(2), 133-146. doi:10.1016/j.rse.2005.11.016 Chen, C. Y. (2018). Urban Climate Map in Taiwan. 國立成功大學建築研究所博士論文. Chen, Y. C., Chen, C. Y., A, M., Liu, K. J., T.P., L. (2017). Modeling the urban thermal environment distributions in Taipei Basin using Local Climate Zone (LCZ). Urban Remote Sensing Event, 10.1109/JURSE.2017.7924531. Chen, Y. C., Lin, T. P., Lin, C. T. (2017). A simple approach for the development of urban climatic maps based on the urban characteristics in Tainan, Taiwan. International Journal of Biometeorology, 61(6), 1029-1041. doi:10.1007/s00484-016-1282-0 Chen, Y. C., Yao, C. K., Honjo, T., Lin, T. P. (2018). The application of a high-density street-level air temperature observation network (HiSAN): Dynamic variation characteristics of urban heat island in Tainan, Taiwan. Sci Total Environ, 626, 555-566. doi:10.1016/j.scitotenv.2018.01.059 Chen, Y.-C., Lo, T.-W., Shih, W.-Y., Lin, T.-P. (2019). Interpreting air temperature generated from urban climatic map by urban morphology in Taipei. Theoretical and Applied Climatology, 137, 2657–2662. doi:10.1007/s00704-018-02764-x Counihan, J. (1975). Adiabatic atmospheric boundary layers: A review and analysis of data from the period 1880–1972. Atmospheric Environment, 9, 871-905. de Dear, R. J., Akimoto, T., Arens, E. A., Brager, G., Candido, C., Cheong, K. W., . . . Zhu, Y. (2013). Progress in thermal comfort research over the last twenty years. Indoor Air, 23(6), 442-461. doi:10.1111/ina.12046 Department of Urban Planning, H. K. (2003). Hong Kong Planning Standards and Guidelines. Du, Y., Mak, C. M. (2018). Improving pedestrian level low wind velocity environment in high-density cities: A general framework and case study. Sustainable Cities and Society, 42, 314-324. doi:10.1016/j.scs.2018.08.001 Du, Y., Mak, C. M., Kwok, K., Tse, K.-T., Lee, T.-c., Ai, Z., . . . Niu, J. (2017). New criteria for assessing low wind environment at pedestrian level in Hong Kong. Building and Environment, 123, 23-36. doi:10.1016/j.buildenv.2017.06.036 Fanger, P. O. (1972). Thermal comfort: analysis and applications in environmental engineering. Mc. Graww Hill. Fröhlich, D., Gangwisch, M., Matzarakis, A. (2019). Effect of radiation and wind on thermal comfort in urban environments - Application of the RayMan and SkyHelios model. Urban Climate, 27, 1-7. doi:10.1016/j.uclim.2018.10.006 Gagge, A. P. (1986). A Standard Predictive Index of Human Response to the Thermal Environment. ASHRAE Trans.; (United States), 92(CONF-8606125-). Golder, D. (1972). Relations among stability parameters in the surface layer. Boundary- Layer Meteorology, 3, 47-58. Höppe, H. M. a. P. (1987). Thermal Comfort of Man in Different Urban Environments. Theoretical and Applied Climatology, 38, 7. H., M. A. R. R. a. M. (1999). Urban climatic map studies in Germany. 20. Hang, J., Li, Y., Sandberg, M., Buccolieri, R., Di Sabatino, S. (2012). The influence of building height variability on pollutant dispersion and pedestrian ventilation in idealized high-rise urban areas. Building and Environment, 56, 346-360. doi:10.1016/j.buildenv.2012.03.023 Hellmann, G. (1917). Über die Bewegung der Luft in den untersten Schichten der Atmosphäre: Königlich Preussischen Akademie der Wissenschaften. Hong, B., Lin, B. (2015). Numerical studies of the outdoor wind environment and thermal comfort at pedestrian level in housing blocks with different building layout patterns and trees arrangement. Renewable Energy, 73, 18-27. doi:10.1016/j.renene.2014.05.060 Höppe, P. (1999). The physiological equivalent temperature – a universal index for the biometeorological assessment of the thermal environment. ISB, 33. Hsu, Y. J. Chang, P. S. (2013). The primary analysis of apparent temperature in Taiwan. Conference on Weather Analysis and Forecasting. Huang, K. T., Yang, S. R., Matzarakis, A., Lin, T. P. (2018). Identifying outdoor thermal risk areas and evaluation of future thermal comfort concerning shading orientation in a traditional settlement. Sci Total Environ, 626, 567-580. doi:10.1016/j.scitotenv.2018.01.031 I.D., S., R., O. T. (2012). Local Climate Zones for Urban Temperature Studies. Bulletin of the American Meteorological Society, 93, 1879-1900. Irwin, J. S. (1979). A theoretical variation of the wind profile power-law exponent as a function of surface roughness and stability. Atmospheric Environment, 13, 191-194. K, B. (1994). New climatological- and -physiological model of the human heat balance outdoor (MENEX) and its applications in bioclimatological studies in different scales. Zeszyty IGiPZ PAN, 28, 27–58. Karra, S., Malki-Epshtein, L., Neophytou, M. K. A. (2017). Air flow and pollution in a real, heterogeneous urban street canyon: A field and laboratory study. Atmospheric Environment,, 165, 370-384. Kent, C. W., Grimmond, S., Gatey, D., Hirano, K. (2019). Urban morphology parameters from global digital elevation models: Implications for aerodynamic roughness and for wind-speed estimation. Remote Sensing of Environment, 221, 316-339. Ketterer, C., Gangwisch, M., Fröhlich, D., Matzarakis, A. (2017). Comparison of selected approaches for urban roughness determination based on voronoi cells. . International Journal of Biometeorology, 61, 189-198. Kjellstrom, T., Holmer, I., Lemke, B. (2009). Workplace heat stress, health and productivity - an increasing challenge for low and middle-income countries during climate change. Glob Health Action, 2. doi:10.3402/gha.v2i0.2047 Kondo, J., Yamazawa, H. (1986). Aerodynamic Roughness over an Inhomogeneous Ground Surface. Boundary-Layer Meteorology, 35(4), 331-348. doi:Doi 10.1007/Bf00118563 Lin, C.-Y., Chen, F., Huang, J. C., Chen, W. C., Liou, Y. A., Chen, W. N., Liu, S.-C. (2008). Urban heat island effect and its impact on boundary layer development and land–sea circulation over northern Taiwan. Atmospheric Environment, 42(22), 5635-5649. doi:10.1016/j.atmosenv.2008.03.015 Lin, F. Y., Huang, K. T., Lin, T. P., Hwang, R. L. (2019). Generating hourly local weather data with high spatially resolution and the applications in bioclimatic performance. Sci Total Environ, 653, 1262-1271. doi:10.1016/j.scitotenv.2018.10.433 Lin, T.-P., Matzarakis, A. (2011). Tourism climate information based on human thermal perception in Taiwan and Eastern China. Tourism Management, 32(3), 492-500. doi:10.1016/j.tourman.2010.03.017 Ma, X., Fukuda, H., Zhou, D., Gao, W., Wang, M. (2019). The study on outdoor pedestrian thermal comfort in blocks: A case study of the Dao He Old Block in hot-summer and cold-winter area of southern China. Solar Energy, 179, 210-225. doi:10.1016/j.solener.2018.12.001 Macdonalda, R. W., R.F., G., D.J., H. (1998). A comparison of results from scaled field and wind tunnel modelling of dispersion in arrays of obstacles. Atmospheric Environment, 32(22), 3845-3862. Manwell, J. F., McGowan, J. G., Rogers, A. L. (2003). Wind energy explained: Theory, design and application. Masters, G. M. (2013). Renewable and efficient electric power systems. Matzarakis, A., Amelung, B. (2008). Physiological Equivalent Temperature as Indicator for Impacts of Climate Change on Thermal Comfort of Humans. Seasonal Forecasts, Climatic Change and Human Health, 12. Matzarakis, A., Rutz, F., Mayer, H. (2010). Modelling radiation fluxes in simple and complex environments: basics of the RayMan model. Int J Biometeorology, 54(2), 131-139. doi:10.1007/s00484-009-0261-0 McPherson, E. G., Rowntree, R. A. (1993). Energy Conservation Potential of Urban Tree Planting. Arboriculture, 19(6). Mochida, A., Lun, I. Y. F. (2008). Prediction of wind environment and thermal comfort at pedestrian level in urban area. Journal of Wind Engineering and Industrial Aerodynamics, 96(10-11), 1498-1527. doi:10.1016/j.jweia.2008.02.033 Montero, G., Rodríguez, E., Oliver, A., Calvo, J., Escobar, J. M., Montenegro, R. (2018). Optimization technique for improving wind downscaling results by estimating roughness parameters. Journal of Wind Engineering and Industrial Aerodynamics, 174, 411-423. Ng, E., Yuan, C., Chen, L., Ren, C., Fung, J. C. (2011). Improving the wind environment in high-density cities by understanding urban morphology and surface roughness: a study in Hong Kong. Landscape and Urban Planning, 101, 59-74. Oke, T. R. E. (1987). Boundary layer climates (2nd ed.). Ozelkan, E., Chen, G., Ustundag, B. B. (2006). Spatial estimation of wind speed: a new integrative model using inverse distance weighting and power law. International Journal of Digital Earth, 9, 733-747. Panofsky, H. A., Blackadar, A. K., McVehil, G. E. (1960). The diabatic wind profile. Quarterly Journal of the Royal Meteorological Society, 86, 390-398. Seinfeld, J. H., Pandis, S. N. (2016). Atmospheric chemistry and physics: from air pollution to climate change. Seo, E. S., Choi, S. H. (2019). Classification of surface roughness using spatial autocorrelation in the economical wind resistant design of buildings. Spatial Information Research, 27, 267-274. Shi, X., Zhu, Y., Duan, J., Shao, R., Wang, J. (2015). Assessment of pedestrian wind environment in urban planning design. Landscape and Urban Planning, 140, 17-28. doi:10.1016/j.landurbplan.2015.03.013 Shrestha, D. P., Saepuloh, A., van der Meer, F. (2019). Land cover classification in the tropics, solving the problem of cloud covered areas using topographic parameters. International Journal of Applied Earth Observation and Geoinformation, 77, 84-93. Steadman, R. G. (1984). A universal expression of apparent temperature. J. Appl. Meteor, 23, 1674-1687. Tuner. (1969). Workbook of Atmospheric Diffusion Estimates. USEPA 999-AP-26. Wang, A.-Q., Lin, T.-P., Liang, W.-Y., C.-Y., K., Tseng, S.-L., Chen, Y.-C. (2018). Across Different Land Use Regions: The Analysis of Wind Corridors Establishment and Assessment of Urban Ventilation Environment. . 126. Xu, Y., Ren, C., Mad, P., Ho, J., Wang, W., Lau, K. K.-L., . . . Ng, E. (2017). Urban morphology detection and computation for urban climate research. Landscape and Urban Planning, 167, 212-224. Yuan, C. (2018). Urban Wind Environment Integrated Climate-Sensitive Planning and Design. SPRINGER BRIEFS IN ARCHITECTURAL DESIGN AND TECHNOLOGY, 10. Zare, S., Hasheminejad, N., Shirvan, H. E., Hemmatjo, R., Sarebanzadeh, K., Ahmadi, S. (2018). Comparing Universal Thermal Climate Index (UTCI) with selected thermal indices/environmental parameters during 12 months of the year. Weather and Climate Extremes, 19, 49-57. doi:10.1016/j.wace.2018.01.004 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/55494 | - |
| dc.description.abstract | 隨著都市發展、熱島效應日益增強，從少數官方測站取得的觀測資料並不足以能夠代表都市的微氣候。本研究利用臺南市區與鄰近17個氣象局測站的風速資料以及高密度地面氣溫測量網(HiSAN)的溫溼度資料來計算行人尺度(2公尺高)的氣象資訊與體感溫度。本研究基於都市的建成環境資料，在考量平均地表粗糙度，使用改良的空間內插方法推算至行人高度的風速。然而在都市中，不只植物與建物的比率以及高度會影響地表粗糙度，大氣穩定度亦然。故本研究先利用交叉驗證法(Leave One Out Cross Validation)評估各氣象因子與條件下最好的參數設定，再選定參數進行空間內插。而在弱綜觀與無降雨的情況下，發現氣象因子的時空分布反映出有些區域有較高的體感溫度。為了了解都市地表型態與微氣候關係，利用主成分分析(Principal Component Analysis)選出較適當的參數，其中建物覆蓋率(BCR)、綠地覆蓋率(GCR)、建物高度(BH)與天空可視率(SVF)，皆被選出來用於分群演算法。局部氣候分區與分群演算法被用來區分都市型態並結合氣象條件，進而理解各型態的環境特徵。兩種都市型態分類方法都可以區分出合適的種類。這些資訊可以加值應用於即時呈現網頁，WebGIS，並提供都市規劃與決策使用。 | zh_TW |
| dc.description.abstract | As urban heat island effect intensifies, weather data produced by a mainly official weather station are not proper to represent and reflect the microclimate situation in a city. This study selected 17 weather stations in Tainan, Taiwan, to estimate the wind velocity on pedestrian-level and utilized 102 automatic stations from high-density street-level air temperature observation network (HiSAN) to measure air temperature and relative humidity at 2.5 meters height. Based on these observed weather data and urban environmental information provided from the government. This study established a method of generating high-resolution pedestrian-level weather information for urban areas. The method took urban morphological parameters, such as surface roughness, into consideration to be the factor of evaluating wind velocity. By interpolation and extrapolation, each grid obtained microclimate weather data on a pedestrian-level scale. The Leave One Out Cross Validation (LOOCV) tested the root-mean-squared errors for the interpolated data. Thus, the best set of parameters, height, methods, nearest neighbor numbers, and atmospheric stability, have been selected for conducting the calculation. The spatial and temporal distribution reflects the patterns of the microclimate conditions under the weak synoptic and no precipitation conditions. Furthermore, the results reflected the hot spots in the city and provided for the urban planners to improve this problem. Several parameters were examined to choose by principal component analysis. The results indicated four parameters, building coverage ratio, green area coverage ratio, building heights, and sky view factor, which should be used to the cluster analysis. The Local Climate Zone (LCZ) and the cluster analysis were used to classify the urban morphology, combining the microclimatic conditions for comprehensively understanding the pattern in each class. Both approaches showed the relationship within the appropriate categories. In addition, all data were integrated into the apparent temperature and presented by a useful tool, WebGIS. The application could provide a simple way to visualize an instantly environmental situation for urban planning and decision making. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T04:05:38Z (GMT). No. of bitstreams: 1 U0001-2907202021214000.pdf: 7585087 bytes, checksum: a7180ba65728fa6543942d273bc74f10 (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | 摘要 i Abstract ii List of Figures vi List of Tables ix Chapter 1、 Motivation and Objective 1 1.1 Background 1 1.2 Research Objective 4 Chapter 2、 Literature review 5 2.1 Pedestrian-level wind field 5 2.2 Thermal environment and thermal comfort 12 2.3 Apparent Temperature 14 2.4 Urban morphology 15 Chapter 3、 Data and Methodology 17 3.1 Research flow chart 17 3.2 Study areas 18 3.3 Data 19 3.3.1 Digitalized building data 19 3.3.2 Vegetation data 20 3.3.3 Wind velocity data 21 3.3.4 Air temperature and relative humidity data 22 3.4 Generating local weather data with high spatially resolution 23 3.4.1 High-density street-level air temperature observation network (HiSAN) 24 3.4.2 Estimation of pedestrian-level wind velocity with respect to land surface roughness 26 3.5 Urban morphological classification 31 3.5.1 Urban Morphological Indices 31 3.5.2 Local climate zone 34 3.5.3 Cluster analysis 38 Chapter 4、 Results and Discussions 38 4.1 Leave one out cross validation of Interpolated data 38 4.2 Heat environments and wind fields at pedestrian-level 46 4.2.1 Seasonal case – JJAS in 2017 46 4.2.2 Monthly Case- September in 2017 56 4.2.3 Diurnal Case – September 25 2017 62 4.3 Pedestrian-level meteorological data under different urban morphology classification 71 4.3.1 Principle Component Analysis 71 4.3.2 Local Climate Zone 76 4.3.3 Cluster Analysis 87 Chapter 5、 Conclusions and Suggestions 98 5.1 Conclusions 98 5.2 Suggestions 100 5.2.1 Application of urban design and policy decision 100 5.2.2 Application of real-time information warning System 101 Reference 102 | |
| dc.language.iso | en | |
| dc.subject | 行人風場 | zh_TW |
| dc.subject | WebGIS | zh_TW |
| dc.subject | 高密度地面氣溫監測網 | zh_TW |
| dc.subject | 都市型態分類 | zh_TW |
| dc.subject | 體感溫度 | zh_TW |
| dc.subject | Urban morphological classification | en |
| dc.subject | WebGIS | en |
| dc.subject | Apparent temperature | en |
| dc.subject | Pedestrian-level wind | en |
| dc.subject | HiSAN | en |
| dc.title | 都市地表型態對行人尺度風場與熱環境之探討:以臺南市區為例 | zh_TW |
| dc.title | Investigating Pedestrian-level Wind Fields and Thermal Environments Under Different Urban Morphology in Tainan | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳正平(Jen-Ping Chen),林子平(Tzu-Ping Lin) | |
| dc.subject.keyword | 高密度地面氣溫監測網,行人風場,體感溫度,都市型態分類,WebGIS, | zh_TW |
| dc.subject.keyword | HiSAN,Pedestrian-level wind,Apparent temperature,Urban morphological classification,WebGIS, | en |
| dc.relation.page | 109 | |
| dc.identifier.doi | 10.6342/NTU202002062 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2020-08-19 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 氣候變遷與永續發展國際學位學程 | zh_TW |
| 顯示於系所單位： | 氣候變遷與永續發展國際學位學程(含碩士班、博士班) | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| U0001-2907202021214000.pdf 未授權公開取用 | 7.41 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。