Monitoring surface dryness using geostationary thermal observations

Rabin, Robert M.; Temimi, Marouane; Stepinski, Jan; Bothwell, Phillip D.

doi:10.1080/2150704x.2013.862601

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…Among these parameters, Land Surface Temperature (LST) is an essential environmental variable, which is a direct driving force of turbulent heat fluxes and long-wave radiation exchanges (Maurer, Wood, Adam, Lettenmaier, & Nijssen, 2002;Nishida, Nemani, Running, & Glassy, 2003). LST is a key variable in formulating energy and water budgets at local through global scales (Anderson et al, 2008;Karnieli et al, 2010;Kustas & Anderson, 2009;Li et al, 2013;Zhang et al, 2008), and it has been widely used during the last decades in a variety of environmental processes including vegetation dynamic (Kogan, 2001), drought (Karnieli et al, 2010;Rabin, Temimi, Stepinski, & Bothwell, 2014), forest fires (Vlassova, Pérez-Cabello, Mimbrero, Llovería, & García-Martín, 2014), urban expansion (Meng & Dou, 2016;Voogt & Oke, 2003) and climate change (Hansen, Ruedy, Sato, & Lo, 2010;Kalma, McVicar, & McCabe, 2008;Weng, 2009;Zhang et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Average annual and seasonal Land Surface Temperature, Spanish Peninsular

et al. 2018

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The first long-term Land Surface Temperature (LST) maps for the Peninsular Spain at annual and seasonal time scales for 1981-2015 is presented in this work. A robust protocol for correcting and calibrating NOAA-AVHRR images and computing LST datasets at the spatial resolution of 1.1 km has been used. Simultaneously, maximum air temperature (Tmax) maps at the same spatial resolution have been produced using data from meteorological stations. The comparison between the two datasets resulted in statistically significant spatial correlations at annual and seasonal scales. Finally, the Normalized Difference Vegetation Index (NDVI) data were also compared with the obtained LST datasets and the results showed significant negative correlations between the two variables, especially in summer.

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