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Uporaba podatkov daljinskega zaznavanja za opazovanje onesnaženosti zraka : magistrsko delo
ID Uršič, Meta (Author), ID Oštir, Krištof (Mentor) More about this mentor... This link opens in a new window, ID Kanjir, Urša (Co-mentor)

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Abstract
Onesnaženje zraka je eden glavnih problemov, s katerim se danes sooča svet. Stopnjo onesnaženosti zraka se vse večkrat opisuje s t. i. trdnimi delci PM10 oziroma PM2.5. Koncentracije trdnih delcev se sicer stalno spremljajo v meritvenih postajah na Zemlji po celem svetu, vendar so lokacije meritev skoncentrirane v razvitih državah in večjih mestih. Alternativo merjenju atmosferskih parametrov iz Zemlje predstavljajo satelitske meritve. Eden izmed mnogih satelitov, ki so zmoženi kontinuirano opazovati atmosfero okrog celotne Zemlje, je tudi Terra s senzorjem MODIS. Med drugim zbira tudi podatke o optični gostoti aerosolov (AOD). V nalogi je preučena možnost uporabe AOD za opazovanje onesnaženosti zraka z delci PM10. Obravnavano je območje Slovenije in del severozahodne Italije. V nalogi je podrobneje predstavljena regresijska analiza med količinama AOD in koncentracijo PM10 merjeno na Zemlji. Naloga ovrednoti smiselnost uporabe enostavne linearne odvisnosti med tema količinama za oceno onesnaženosti zraka. Rezultati uporabljene kalibracije kažejo na šibko povezanost AOD in koncentracijo delcev PM10 merjeno na tleh. Izkaže se, da je uporaba enostavne linearne odvisnosti med AOD in koncentracijo PM10 na Zemlji za oceno onesnaženosti zraka smiselna za poletne mesece, ko je podatkov dovolj, ne pa tudi pozimi. Satelitski podatki so zato lahko odlična osnova določevanju onesnaženosti zraka, pri čemer je, posebej za zimske mesece, obvezno upoštevati tudi druge dejavnike, ki vplivajo na koncentracijo delcev PM10 v zraku.

Language:Slovenian
Keywords:MODIS, PM10, daljinsko zaznavanje, regresijska analiza, onesnaženje zraka, optična globina aerosolov, optična gostota aerosolov
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FGG - Faculty of Civil and Geodetic Engineering
Publisher:[M. Uršič]
Year:2018
PID:20.500.12556/RUL-102783 This link opens in a new window
UDC:528.8:614.71(497.4)(450)(043.3)
COBISS.SI-ID:8551521 This link opens in a new window
Publication date in RUL:08.09.2018
Views:2331
Downloads:444
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Secondary language

Language:English
Title:Using remote sensing data for measuring air pollution : master thesis
Abstract:
Air pollution is one of the main problems the world is facing nowadays. The air pollution level is measured by the amount of solid particles in the air: PM10 and PM2.5. Concentration of solid particles in air quality measurement stations all around the globe varies constantly. Locations of the measuring stations are concentrated usually in major cities and more developed countries. An alternative to measurement stations on Earth are satellite measurements from space. NASA’s Terra Satellite is one of the satellites that are capable of continuously observing the Earth's atmosphere with the so-called MODIS sensor. It also gathers information about the aerosol optical density (AOD). The thesis deals with the potential of using these quantities in order to observe the pollution of air with PM10 particles. It focuses on Slovenia and a part of NW Italy. The thesis introduces a regression analysis between AOD and concentration of PM10 as measured on Earth. It deals with the question whether and to what extent it is reasonable to use a simple linear dependence between these two quantities for the assessment of air pollution. The results of the applied calibration show that there is a weak correlation between AOD and the concentration of PM10 particles measured on the ground. It turns out that the use of a simple linear interdependence between AOD and the concentration of PM10 on Earth is relevant in the summer months where there is sufficient data available, but not in the winter. Hence, satellite data can serve as an excellent base for assessing air pollution, whereby it is necessary, especially in the winter months, to take into account other factors that influence the concentration of PM10 particles in the air.

Keywords:MODIS, PM10, remote sensing, regression analysis, air pollution, aerosol optical depth, aerosol optical thickness

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