Final report on the use of the satellite data and data fusion techniques, based on the historical data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F18%3AN0000154" target="_blank" >RIV/00020699:_____/18:N0000154 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Final report on the use of the satellite data and data fusion techniques, based on the historical data

Popis výsledku v původním jazyce

In the scope of the SAMIRA project, an important task is a development of data fusion methods combining in situ measurements, satellite observations and chemical transport modelling (CTM) outputs. These three sources are mutually complimentary – in situ measurements provide accurate actual levels of concentrations, satellite data provide reasonably continuous observations of spatial patterns and modelling outputs provide spatially continuous coverage of given area. None of these datasets on its own is ideal for mapping purposes due to either substantial data gaps, insufficient spatial resolution, or large uncertainties. For the combination of different data sources, a range of various methods can be used to create spatial concentration fields. Such methods are often referred to as 'data assimilation' and 'data fusion'. Data fusion is a subset of data assimilation methods in a wider sense. One of the often used data fusion methods is residual kriging. In the SAMIRA project, the residual kriging applied separately for the rural and urban background areas with the subsequent merging of these maps layers by population density is used, i.e. the regression – interpolation – merging mapping. It combines in-situ measurements, chemistry transport model results, and Earth Observation (satellite). In this final report, NO2, SO2, PM10, and PM2.5 data for 2014 are examined, at two spatial domains. In a use of the satellite data, the major obstacle is a frequent occurrence of spatial gaps. Trying to overcome this obstacle, gapfilling has been selected and applied.

Název v anglickém jazyce

Final report on the use of the satellite data and data fusion techniques, based on the historical data

Popis výsledku anglicky

In the scope of the SAMIRA project, an important task is a development of data fusion methods combining in situ measurements, satellite observations and chemical transport modelling (CTM) outputs. These three sources are mutually complimentary – in situ measurements provide accurate actual levels of concentrations, satellite data provide reasonably continuous observations of spatial patterns and modelling outputs provide spatially continuous coverage of given area. None of these datasets on its own is ideal for mapping purposes due to either substantial data gaps, insufficient spatial resolution, or large uncertainties. For the combination of different data sources, a range of various methods can be used to create spatial concentration fields. Such methods are often referred to as 'data assimilation' and 'data fusion'. Data fusion is a subset of data assimilation methods in a wider sense. One of the often used data fusion methods is residual kriging. In the SAMIRA project, the residual kriging applied separately for the rural and urban background areas with the subsequent merging of these maps layers by population density is used, i.e. the regression – interpolation – merging mapping. It combines in-situ measurements, chemistry transport model results, and Earth Observation (satellite). In this final report, NO2, SO2, PM10, and PM2.5 data for 2014 are examined, at two spatial domains. In a use of the satellite data, the major obstacle is a frequent occurrence of spatial gaps. Trying to overcome this obstacle, gapfilling has been selected and applied.

Druh

O - Ostatní výsledky

CEP obor

—

OECD FORD obor

10509 - Meteorology and atmospheric sciences

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů