Terrestrial photography as an alternative to satellite images to study snow cover evolution at hillslope scale

Rafael Pimentel; Javier Herrero; María José Polo

doi:10.1117/12.974419

23 October 2012 Terrestrial photography as an alternative to satellite images to study snow cover evolution at hillslope scale

Rafael Pimentel, Javier Herrero, María José Polo

Author Affiliations +

Proceedings Volume 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV; 85310Y (2012) https://doi.org/10.1117/12.974419
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

In Mediterranean regions, where the water shortage is a serious and recurrent problem, it is essential to know the behaviour and evolution of the snow. Satellite remote sensing is widely used to find out the evolution of the snow cover extension at medium-large scales. But these techniques pose some constraints if snow is heterogeneously distributed, as they do not correctly represent the physical processes that occur on a smaller scale than the satellite image. In such cases, terrestrial photographs, whose resolution can be more easily adapted to the required resolution for these study cases, are an economic and also efficient alternative. This work presents a methodology for the georeferencing and automatic detection of snow in terrestrial photography, as an alternative to the use of satellite images for the study of the snow cover evolution in small areas. This methodology has been evaluated during the snowmelt period in the spring of 2009 at a study site in Sierra Nevada Natural Park (Southern Spain). The resulting snow maps have been compared with the results available for that period obtained from the analyses of four Landsat images. The results show that the use of Landsat generally overestimated the extension of the snow cover in the study area.

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Rafael Pimentel, Javier Herrero, and María José Polo "Terrestrial photography as an alternative to satellite images to study snow cover evolution at hillslope scale", Proc. SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 85310Y (23 October 2012); https://doi.org/10.1117/12.974419

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