Abstract
Abstract. Land Surface Temperature (LST) is one of the important factors in monitoring urban climate. Observing the variations of LST can provide a better understanding of the Urban Heat Islands (UHI) phenomenon. The aim of this research is to assess the relationship between the spatial and temporal distribution of LST and water consumption in Zamboanga City for years 2016 and 2017. Data from the city’s water district were used to compute for the per capita water consumption (PCWC) of 49 barangays. Landsat 8 LST data with 30m spatial resolution were computed using inverse Plank function and other parameters such as vegetation proportion and surface emissivity to assess LST spatially while MODIS Terra data with 1km spatial resolution were used to assess LST temporally. Result showed that Landsat LST and PCWC have moderate correlations with p < 0.01: 0.59 and 0.55 for March and April 2016, respectively; 0.49 and 0.56 for March and April 2017, respectively. These indicated that warmer barangays consumed more water. The temporal correlation of the MODIS LST and the computed PCWC equated a −0.71, p < 0.01, correlation. This negative correlation indicated that when LST increases, PCWC decreases, which do not directly indicate that the city consumed less water but rather that the supply was less during warmer months. It was evident as water rationing was experienced during the first quarter of 2016 and intensified on April where the highest LST was recorded. Finally, LST was found of good use in assessing the relationship of temperature and water consumption.
Highlights
Surface temperature is a major role in assessing urban climatology (Voogt and Oke 2003)
This paper aims to assess the general relationship between the temporal and spatial distribution of Land Surface Temperature and water consumption in Zamboanga City for years 2016 and 2017
Landsat 8 Thermal Infrared Sensor (TIRS) data with 30m resolution was used to analyze Land surface temperature (LST) spatially. This TIRS data were converted from Digital Number (DN) to Top of Atmosphere (ToA) spectral radiance using the radiance scaling factors found in the metadata using the equation below: Lλ = MLQcal + AL
Summary
Surface temperature is a major role in assessing urban climatology (Voogt and Oke 2003). The lack of vegetation in these urban cities reduces its ability to shed excessive heat (T.R Oke 1987). Though most studies identify the same factors, UHI still varies locally depending on the city size, physiographic features and meteorological conditions (Martin et al, 2015; Tzavali et al, 2015). This reality has caused difficulties in systematizing the definition of a UHI. Land surface temperature (LST) is a major parameter used to examine urban heat islands in the surface level (Wang 2015) and understanding surface urban heat islands (SUHI) using LST can help understand and quantify UHI (Weng 2009)
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