Quantitative Analysis of Greening for Sustainable City
DOI:
https://doi.org/10.64862/Keywords:
LST, ET, Landsat TM5, LiDAR, Energy Balance ModelingAbstract
This study quantitatively analyses the spatial relationship between land surface cover and urban surface temperature distribution among different land use classes in metropolitan Melbourne. This relationship was explored through a detailed estimate of fractional land cover at 30 m grid resolution using LiDAR data along with land surface temperature (LST) and modeled heat fluxes using Landsat TM5 data. In this study spatially distributed energy fluxes specifically ET, in an urban area were modeled based on an energy balance approach incorporating the surface roughness parameters derived from the LiDAR Data. This study shows a strong and significant linear relationship between LST and the percentage of different types of land cover. The relationship is positive for built-up areas and negative for vegetated areas. Such relationship quantitively depicts that with increasing total vegetation cover the LST decreases; in contrast LST increases linearly with increased imperviousness.
References
Allen, R. G., Tasumi, M., Morse, A., Trezza, R., Wright, J. L., Bastiaanssen, W., Kramber, W., Lorite, I., and Robison, C. W. (2007). Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) applications. Journal of Irrigation and Drainage Engineering, 133 (4), 395–406. https://doi.org/10.1061/(ASCE)0733-9437(2007)133:4(395)
Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., and Holtslag, A. A. M. (1998). A remote sensing surface energy balance algorithm for land (SEBAL): 1. Formulation. Journal of Hydrology, 212–213, 198–212. https://doi.org/10.1016/S0022-1694(98)00253-4
Burian, S. J., Stetson, S. W., Han, W., Ching, J., and Byun, D. (2004). High-resolution dataset of urban canopy parameters for Houston, Texas.
Coutts, A. M., Tapper, N. J., Beringer, J., Loughnan, M., and Demuzere, M. (2013). Watering our cities: The capacity for water sensitive urban design to support urban cooling and improve human thermal comfort in the Australian context. Progress in Physical Geography, 37 (1), 2–28. https://doi.org/10.1177/0309133312461032
Grimmond, S. (2007). Urbanization and global environmental change: Local effects of urban warming. Geographical Journal, 173(1), 83–88. https://doi.org/10.1111/j.1475-4959.2007.232_3.x
Grimmond, C. S. B., and Oke, T. R. (1999). Evapotranspiration rates in urban areas. In Impacts of Urban Growth on Surface Water and Groundwater Quality (IAHS Publication No. 259, pp. 235–244). International Association of Hydrological Sciences.
Liu, S., Hu, G., Lu, L., and Mao, D. (2007). Estimation of regional evapotranspiration by TM/ETM data over heterogeneous surfaces. Photogrammetric Engineering and Remote Sensing, 73(10), 1169–1178. https://doi.org/10.14358/PERS.73.10.1169
Liu, W., Hong, Y., Khan, S. I., Huang, M., Vieux, B., Caliskan, S., and Grout, T. (2010). Actual evapotranspiration estimation for different land use and land cover in urban regions using Landsat 5 data. Journal of Applied Remote Sensing, 4, 041873. https://doi.org/10.1117/1.3525566
Markham, B. L., and Barker, J. L. (1986). Landsat MSS and TM post-calibration dynamic ranges, exoatmospheric reflectances and at-satellite temperatures. Earth Observation Satellite Company.
Oke, T. R. (1988). The urban energy balance. Progress in Physical Geography, 12(4), 471–508. https://doi.org/10.1177/030913338801200401
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Nepal Society of Engineering Geology (NSEG)
This work is licensed under a Creative Commons Attribution 4.0 International License.
