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100			_aVecchio, A Lo _951059
245			_aMODIS Image-derived ice surface temperature assessment in the Southern Patagonian Icefield/
260			_bSage, _c2019.
300			_aVol 43, issue 6, 2019 : (754-776 p.).
520			_aIce surface temperature (IST) is one of the most relevant parameters when it comes to estimating the effects of climate change on glaciers. This study aims to estimate the IST for the Southern Patagonian Icefield (SPI) during the 2001–2016 period and, in so doing, to contribute to the assessment of the MOD11A1 product in this area. We evaluated IST performance by comparing it with that of automatic weather stations (AWSs). In addition, the glaciological significance of the results is presented through 1) IST trends, 2) annual IST anomalies, 3) IST behavior at different altitudes and orientations and 4) a comparison with Santa Cruz River flow records. The correlation coefficients obtained between the IST and AWSs ranged between 0.66 and 0.85. In addition, we report on the mean absolute differences between them, ranging between 0.6 ± 3.6°C and 9.4 ± 1.9°C. In this sense, we observed the lowest differences at the AWSs that were located in a homogeneous environment. Stated in glaciological terms: 1) only 1% of the pixels had a statically significant IST trend (p-value ≤ 0.05): between 0.01 and 0.05°C/month; 2) we found that most of the IST anomalies ranged between –1 and 1°C throughout the period of this study; 3) the results suggest that the altimetric gradient was the most influential variable of the IST, mostly in north-oriented glaciers; and 4) the SPI IST showed an annual periodicity, which, in turn, shows a high correlation with the Santa Cruz River flow (R = 0.86). This study is the first in estimating the SPI’s IST and contributes to enhance our knowledge of glacier dynamics and, therefore, the management of the water resource. Despite this, some MOD11 filtering is required in regions with high cloud cover frequency.
650			_aMOD11A1, _951060
650			_a ice surface temperature analysis, _951061
650			_aMOD11 correction, _951062
650			_aspatial distribution, _951063
650			_aremote sensing _950690
700			_aLannutti, E _951064
700			_a Lenzano, MGR _951065
700			_aMikkan, _951066
700			_aVacaflor, P _951067
700			_a Lenzano, L _951068
773	0		_012665 _916502 _dLondon: Sage Publication Ltd, 2019. _tProgress in Physical Geography: Earth and Environment/ _x03091333
856			_uhttps://doi.org/10.1177/0309133319851022
942			_2ddc _cART
999			_c12714 _d12714