Air pollution detection using MODIS data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F11%3A33119528" target="_blank" >RIV/61989592:15310/11:33119528 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1117/12.898107" target="_blank" >http://dx.doi.org/10.1117/12.898107</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1117/12.898107" target="_blank" >10.1117/12.898107</a>
Alternative languages
Result language
angličtina
Original language name
Air pollution detection using MODIS data
Original language description
The quality of the environment has a great impact on public health while air quality is a major factor that is especially relevant for respiratory diseases. PM10 (particulate matter below 10 mý) particles are among the most dangerous pollutants, which enter the lower respiratory tract and cause serious health problems. Obtaining reliable air pollution data is limited to a number of ground measuring stations and their spatial location. We used an alternative approach and created statistical models that employed remotely sensed imageries. To establish empirical relationships, we used multi-temporal (2006-2009) MODIS aerosol optical thickness data (product MOD04, Level 2) and the PM10 ground mass concentrations. The north-western part of the Czech Republic (namely the Karlovarský and the Ustecký regions) was chosen as a test site, as all the different types of cultural landscape (forest-economical, agricultural, mining, and urban) can be found within one MODIS scene. This study was focuse
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
DE - Earth magnetism, geodesy, geography
OECD FORD branch
—
Result continuities
Project
<a href="/en/project/GA205%2F09%2F1079" target="_blank" >GA205/09/1079: Methods of Artificial Inteligence in GIS</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings - Earth Resources and Environmental Remote Sensing/GIS Applications II
ISBN
978-0-8194-8808-4
ISSN
0277-786X
e-ISSN
—
Number of pages
15
Pages from-to
1-14
Publisher name
SPIE
Place of publication
Bellingham, USA
Event location
Praha
Event date
Sep 20, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—