have been aggregated into tables containing, in columns, the time of acquisition of each scene and in rows the ID and values of pixels, their elevation, extracted The snow is an essential component of the radiation balance of the planet due to its high reflectivity combined with the high surface coverage. The remote sensing allows, by exploiting snow physical features, to measure its coverage. MODIS sensor is currently used for the measurement of snow cover: the observations generate daily snow cover maps with a resolution of 500 meters. In our experiments, we used 506 scenes (2000 - 2010) to analyze the snow cover dynamics in the Verbano - Cusio – Ossola Province: the data have been reclassified in order to optimize the information content to the needs of the project. The reclassification has the objective to provide a quantification of pixels characterized by snow cover and to evaluate the surface in term of time: reclassified raster from digital elevation model, resampled at the same resolution of MODIS scenes, has also been included in a separate column. The procedure was implemented in Visual Basic environment, where every step of the sequence has been automated, allowing the processing of the whole dataset. At the end of the procedure summary tables were generated, subdivided into individual years of observation, table data have been then processed, exploiting the potential of the R language, by generating graphic representations and maps of snow cover concerning the study area. The data obtained from these calculations were validated by comparison with data obtained from snow sensor located in the Province, in particular by comparing the snowpack melt-out date evaluated according to the 2 approaches - MODIS and snow sensors.

Copertura nevosa nella provincia del Verbano-Cusio-Ossola: analisi automatizzata di una serie storica MODIS

GODONE, DANILO FRANCESCO;FILIPPA, Gianluca;TERZAGO, SILVIA;FREPPAZ, Michele;FRATIANNI, SIMONA;GARNERO, Gabriele;
2012

Abstract

have been aggregated into tables containing, in columns, the time of acquisition of each scene and in rows the ID and values of pixels, their elevation, extracted The snow is an essential component of the radiation balance of the planet due to its high reflectivity combined with the high surface coverage. The remote sensing allows, by exploiting snow physical features, to measure its coverage. MODIS sensor is currently used for the measurement of snow cover: the observations generate daily snow cover maps with a resolution of 500 meters. In our experiments, we used 506 scenes (2000 - 2010) to analyze the snow cover dynamics in the Verbano - Cusio – Ossola Province: the data have been reclassified in order to optimize the information content to the needs of the project. The reclassification has the objective to provide a quantification of pixels characterized by snow cover and to evaluate the surface in term of time: reclassified raster from digital elevation model, resampled at the same resolution of MODIS scenes, has also been included in a separate column. The procedure was implemented in Visual Basic environment, where every step of the sequence has been automated, allowing the processing of the whole dataset. At the end of the procedure summary tables were generated, subdivided into individual years of observation, table data have been then processed, exploiting the potential of the R language, by generating graphic representations and maps of snow cover concerning the study area. The data obtained from these calculations were validated by comparison with data obtained from snow sensor located in the Province, in particular by comparing the snowpack melt-out date evaluated according to the 2 approaches - MODIS and snow sensors.
16° Conferenza Nazionale ASITA
Vicenza
6-9 novembre 2012
Atti 16° Conferenza Nazionale SITA
ASITA: Federazione delle Associazioni Scientifiche per le Informazioni Territoriali e Ambientali.
761
766
9788890313271
http://www.ASITA.it
Copertura nevosa; MODIS; Verbano Cusio Ossola
Godone D.; Filippa G.; Terzago S.; Freppaz M.; Fratianni S.; Garnero G.; Rivella E.; Saladin A.; Barbero S.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/128937
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