Forschungs- & Entwicklungsinformationsdienst der Gemeinschaft - CORDIS


ENVISNOW Berichtzusammenfassung

Project ID: EVG1-CT-2001-00052
Gefördert unter: FP5-EESD
Land: Norway

Multi-sensor time-series snow cover algorithms

Frequent mapping of snow parameters, like snow cover area (SCA), is important for applications in hydrology and climatology. The objective is to analyse on a daily basis a time series of optical and Synthetic Aperture Radar (SAR) data together producing sensor-independent products. A multi-sensor SCA product has been defined. A prototype production line has been developed to automatically perform data retrieval, pre-processing, parameter retrieval and product generation.

The approach is to analyse each satellite image individually and then first to combine them into a day product. How each image contributes to the day product is controlled by a pixel-by-pixel confidence value that is computed for each image analysed. The confidence algorithm may take into account information about the local observation angle/IFOV size, probability of clouds, prior information about snow state, etc. The time series of day products are then combined into a multi-sensor/multi-temporal product.

The combination of products is done on a pixel-by-pixel basis and controlled by each individual product/pixel’s confidence and a decay function of time. The “multi product” is then to represent the most likely status of the SCA.

Reported by

Norut IT
P.O. 6434 Forskningsparken
9294 Tromsø
Folgen Sie uns auf: RSS Facebook Twitter YouTube Verwaltet vom Amt für Veröffentlichungen der EU Nach oben