Opazovanje poplav s podatki daljinskega zaznavanja

Abstract

Keywords

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Language:	Slovenian
Year of publishing:	2009
Source:	Ljubljana
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FGG - Faculty of Civil and Geodetic Engineering
Publisher:	[D. Vodišek]
UDC:	528.8:556.166(043.2)
COBISS:	4601185
Views:	1843
Downloads:	827
Average score:	0 (0 votes)
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Secondary language:	English
Secondary title:	Observing floods from remote sensing data
Secondary abstract:	Remote sensing techniques have been used to observe various phenomena on the Earth. With improved satellite system natural disasters can be better monitored. The Thesis deals with the usefulness of satellite images in the case of natural disasters and presents the procedure with which we obtaine, preprocess, classify and interpret satellite images of catastrophic flood in year 2007. The international charter Space and Major Disasters was activated in order to get satellite images to observe floods. The satellite images SPOT have been processed as follows: orthorectification, pan-sharpening of multispektral images and contrast enhancement. Maximum likelihood algorithm was used as the main classifier and the accuracy of results was further improved by normalized difference vegetation index, digital elevation model and hydrological data. From these flooded areas statistical analysis for damaged land use was made.
Secondary keywords:	graduation thesis;geodesy;remote sensing;natural disasters;Space and Major Disasters charter;SPOT;image analysis;normalized difference vegetation index;classification;land use;
File type:	application/pdf
Type (COBISS):	Undergraduate thesis
Thesis comment:	Univ. Ljubljana, Fakulteta za gradbeništvo in geodezijo
Pages:	XVI, 98 str., pril.
Type (ePrints):	thesis
Title (ePrints):	Surface: Observing floods from remote sensing data
Keywords (ePrints):	daljinsko zaznavanje;naravne nesreče;program Vesolje in velike nesreče;SPOT;analiza podob;normiran diferencialni vegetacijski indeks;klasifikacija;raba tal
Keywords (ePrints, secondary language):	remote sensing;natural disasters;Space and Major Disasters charter;SPOT;image analysis;normalized difference vegetation index;classification;land use
Abstract (ePrints):	Z daljinskim zaznavanjem opazujemo razne pojave na Zemlji, s satelitskimi sistemi z boljšo prostorsko ločljivostjo lahko spremljamo naravne nesreče bolj nazorno. V diplomski nalogi sem predstavila uporabnost satelitskih posnetkov v primeru naravnih nesreč. Opisan je postopek pridobitve, predobdelave, klasifikacije in interpretacije satelitskih podob ob katastrofalni poplavi leta 2007. Z aktivacijo mednarodnega programa Vesolje in velike nesreče so bili za opazovanje poplave pridobljeni satelitski posnetki, sledila je ortorektifikacija, ostrenje večspektralne podobe s pankromatsko ter izboljšanje kontrasta uporabljenih podob SPOT. Iz predobdelanih podob SPOT sem s klasifikacijskim algoritmom metode največje verjetnosti določila poplavljena območja. Natančnost klasifikacije je bila izboljšana z normiranim diferencialnim vegetacijskim indeksom, z digitalnim modelom višin in s slojem hidrografije. Iz poplavljenih območij sledi statistična analiza poškodovane rabe tal.
Abstract (ePrints, secondary language):	Remote sensing techniques have been used to observe various phenomena on the Earth. With improved satellite system natural disasters can be better monitored. The Thesis deals with the usefulness of satellite images in the case of natural disasters and presents the procedure with which we obtaine, preprocess, classify and interpret satellite images of catastrophic flood in year 2007. The international charter Space and Major Disasters was activated in order to get satellite images to observe floods. The satellite images SPOT have been processed as follows: orthorectification, pan-sharpening of multispektral images and contrast enhancement. Maximum likelihood algorithm was used as the main classifier and the accuracy of results was further improved by normalized difference vegetation index, digital elevation model and hydrological data. From these flooded areas statistical analysis for damaged land use was made.
Keywords (ePrints, secondary language):	remote sensing;natural disasters;Space and Major Disasters charter;SPOT;image analysis;normalized difference vegetation index;classification;land use
ID:	8310869