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Contenuto archiviato il 2024-05-14

Satellite Remote Sensing for Lake Monitoring

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Summary: The introduction of remote sensing material into the daily procedures of water quality surveillance in Sweden has been going very slowly, although material and research results have been available for two decades. We believe, however, that we now have such a good co-operation with Stockholm Water Company that this may lead to a more frequent use of the remote sensing data.
Summary: The project has generated knowledge from imaging spectrometers that could be useful for the future environmental monitoring of the larger lakes of Europe by means of satellite remote sensing. To some extent we have been using the same wavelengths as the shortly launched satellite ENVISAT by ESA and its sensor MERIS. This has enabled us to come to a first simple algorithm for monitoring of water quality variables from space. Within the last few months of the SALMON project and in the near future, we expect to further improve the algorithm for MERIS
Summary: The developed technique assimilates in situ limnological observations and remote sensing data (space/airborne imaging spectrometer data) in order to increase the spatial representativity of the current monitoring system that is based on discrete water quality sampling. The feasibility of the remote sensing aided water quality observation system can be implemented as an integrated part of the current water quality monitoring system of the Finnish environment administration. Applicable near-future space-borne sensors to be used in operative lake water quality assessment system include the MERIS-instrument onboard the ESA Envisat satellite.t
Summary: One of the most critical factors affecting radiometric remote sensing is the effect of the atmosphere on the propagating energy. In most cases, the atmosphere is perceived as a hostile entity whose adverse impacts must be neutralized or eliminated before remotely sensed data can be properly analyzed. Then, a specific shell was developed permitting an automatic correction of remote sensing data-sets in order to remove noise from atmospheric effects, either from airborne or satellite. To the goal, specific options are included where different models can be applied. The software produced runs under most common operating systems and it is implemented on IDL programming environment, the software produced runs in all computer type (Unix based, Windows PC, Macintosh) at the condition to have a run-time IDL license.

Risultati sfruttabili

One main goal of the SALMON project is the definition of Earth observation (EO) data needs for monitoring the European lakes, with the primary concern being water quality. The project was a unique opportunity for limnologists and remote sensing (RS) specialists to work together, with the aim to fill end-users' needs. In fact results of the project will benefit regional and local authorities responsible for lake monitoring, management, and water supply. An effective management of waters requires information on the spatial distribution and temporal variation of water quality. RS is in many cases the only effective technique for monitoring these differences in water quality, although the information is less accurate than traditional laboratory analyses. Joint campaigns with limnological and optical sampling simultaneous to RS overpasses, both spaceborne and airborne, have been accomplished in three ecoregions: Sub-alpine, Boreal, Sub-arctic. To make all project data-sets comparable and sharable, instrument intercalibration was accomplished and common protocols defined (for limnology, optical observations, RS). Estimation of the inherent and apparent optical properties of waters provided a mechanistic explanation for the bio-physical content variations, to be used to improve RS algorithms and related models to predict limnological parameters starting from radiative information. Several algorithms for retrieving different parameters were found and evaluated, depending on the trophic state, the season and other environmental conditions. Results also include radiometric and atmospheric correction modelling for RS data. Statistical analyses of synchronous multi-instrument (imaging spectrometer and microwave sensors) overpasses, showed that radar data can be of great support in the correction of optical data and that specific narrow spectral bands are of greater utility to detect some basic limnological parameters.

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