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Last modified by Hyunji Cho on 2023/06/27 11:52
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Hyunji Cho 1.1 1 = 2.3.17 Land surface temperature =
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5 ====== **Social challenge/ impact linked to:** ======
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8 ====== **Co-creation phase linked to:** ======
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10 E) Co-monitoring
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13 ====== **Level of importance** ======
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15 **1** - High Importance / must have
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18 ====== **Description** ======
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20 Land surface temperature
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23 ====== **Scale as linked to D2.2 framework** ======
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27 * City
28 * Neighborhood
29 * Project Area
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32 ====== **Data source and input type** ======
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34 * Satellite image (e.g. The US Landsat5)
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37 ====== **Connection with SDGs** ======
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41 * Goal 11: Sustainable cities and communities
42 * Goal 13: Climate action
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45 ====== **Required Data** ======
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47 * thermal infrared (TIR) band (10.40–12.50 mm) of Landsat-5 Thematic Mapper (TM) images
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50 ====== **Expected Outputs** ======
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52 * Land surface temperature (Celsius)
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55 ====== **Calculation methods** ======
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57 * Zhou //et al//. (2021): We used LST data derived from the thermal infrared (TIR) band (10.40–12.50 mm) of Landsat-5 Thematic Mapper (TM) images with a spatial resolution of 120 m. We used a total of 34 TM images, most of which were acquired in the summer of 2010 (June, July or August) to coincide with the year the census data were collected. All the images were acquired on sunny, calm days with clear-sky conditions at approximately 10:30 a.m. local time. We first converted the digital number of the TM TIR band to the top-of-atmospheric (TOA) radiance. We then calculated the surface-leaving radiance from TOA radiance. This was carried out by removing the effects of the atmosphere in the thermal region. Finally, we calculated LST based on surface-leaving radiance using the Planck function. More details about the calculation of LST can be found in Zhou et al. (2014)
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60 ====== **Level of expertise required** ======
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62 * High
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65 ====== **Links and references** ======
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67 * Zhou, W., Huang, G., Pickett, S. T., Wang, J., Cadenasso, M. L., McPhearson, T., ... & Wang, J. (2021). Urban tree canopy has greater cooling effects in socially vulnerable communities in the US. One Earth, 4(12), 1764-1775.https:~/~/eca.knmi.nl/indicesextremes/indicesdictionary.php#8
68 * Zhou, W., Qian, Y., Li, X., Li, W., and Han, L. (2014). Relationships between land cover and the surface urban heat island. Seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures. Landsc. Ecol. 29, 153–167. https:~/~/doi.org/10.1007/s10980-013-9950-5.
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74 (% class="success" %)|(% style="width:68px" %)**Version**|(% style="width:179px" %)**Name**|(% style="width:112px" %)**Date**|(% style="width:636px" %)**Changes made**
75 (% class="active" %)|(% style="width:68px" %)**0.1**|(% style="width:179px" %)Hyunji Cho|(% style="width:112px" %)27/06/2023|(% style="width:636px" %)Factsheet created
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