Combining spatial and temporal data to create a fine-resolution daily urban air temperature product from remote sensing land surface temperature (LST) data

Bird, David Neil; Banzhaf, Ellen; Knopp, Julius; Wu, Wanben; Jones, Laurence ORCID: https://orcid.org/0000-0002-4379-9006. 2022 Combining spatial and temporal data to create a fine-resolution daily urban air temperature product from remote sensing land surface temperature (LST) data [in special issue: Cool cities: towards sustainable and healthy urban environments] Atmosphere, 13 (7), 1152. 18, pp. https://doi.org/10.3390/atmos13071152

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Official URL: http://dx.doi.org/10.3390/atmos13071152

Abstract/Summary

Remotely sensed land surface temperature (LST) is often used as a proxy for air temperature in urban heat island studies, particularly to illustrate relative temperature differences between locations. Two sensors are used predominantly in the literature, Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS). However, each has shortcomings that currently limit its utility for many urban applications. Landsat has high spatial resolution but low temporal resolution, and may miss hot days, while MODIS has high temporal resolution but low spatial resolution, which is inadequate to represent the fine grain heterogeneity in cities. In this paper, we overcome this inadequacy by combining high spatial frequency Environmental Services (ES), Landsat-driven Normalized Difference Vegetation Index (NDVI), and MODIS low spatial frequency background LST at different spatial frequency bands (spatial spectral composition). The method is able to provide fine scale LST four times daily on any day of the year. Using data from Paris in 2019 we show that (1) daytime cooling by vegetation reaches a maximum of 30 °C, above which there is no further increase in cooling. In addition, (2) the cooling is relatively local and does not extend further than 200 m beyond the boundary of the NBS. This model can be used to quantify the benefits of NBS in providing cooling in cities.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.3390/atmos13071152
UKCEH and CEH Sections/Science Areas:	Soils and Land Use (Science Area 2017-)
ISSN:	2073-4433
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	nature based solutions (NBS), environmental services (ES), land surface temperature (LST), Landsat, MODIS, Normalized Difference Vegetation Index (NDVI), DisTrad, spatial spectral composition
NORA Subject Terms:	Earth Sciences
Date made live:	28 Dec 2022 14:36 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/533764

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.3390/atmos13071152

UKCEH and CEH Sections/Science Areas:

Soils and Land Use (Science Area 2017-)

ISSN:

2073-4433

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

nature based solutions (NBS), environmental services (ES), land surface temperature (LST), Landsat, MODIS, Normalized Difference Vegetation Index (NDVI), DisTrad, spatial spectral composition

NORA Subject Terms:

Earth Sciences

Date made live:

28 Dec 2022 14:36 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/533764