diplomska naloga
Aleksander Šašo (Avtor), Mojca Kosmatin Fras (Mentor), Dušan Kogoj (Član komisije za zagovor), Alma Zavodnik Lamovšek (Član komisije za zagovor), Urška Kanjir (Komentor)

Povzetek

Spremljanje stanja vegetacije na osnovi podatkov daljinskega zaznavanja

Ključne besede

geodezija;GIG;diplomska dela;daljinsko zaznavanje;biofizikalne spremenljivke;vegetacija;MERIS;

Podatki

Jezik: Slovenski jezik
Leto izida:
Izvor: Ljubljana
Tipologija: 2.11 - Diplomsko delo
Organizacija: UL FGG - Fakulteta za gradbeništvo in geodezijo
Založnik: [A. Šašo]
UDK: 528.7(043.2)
COBISS: 6368097 Povezava se bo odprla v novem oknu
Št. ogledov: 2022
Št. prenosov: 543
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Angleški jezik
Sekundarni naslov: Monitoring of vegetation condition from remote sensing data
Sekundarni povzetek: In the graduation thesis different biophysical variables that can be derived from remotely sensed data are presented. The algorithms for their calculations, that have been tested on the medium resolution remotely sensed MERIS data, are given. Based on the linear regression the interdependence of individual biophysical variables has been determined. The visual comparison between our results and digital orthophoto as well as biophysical products, available on the Internet, has been made. We have found out that all biophysical variables are mutually dependent. All the algorithms, needed for calculation of biophysical variables, except the MERIS Terrestrial Chlorophyll Index (MTCI), were suitable for the purpose. At the algorithm MTCI in case when clouds and sea surfaces are present more significant mistakes may occur. Further on, we have realized that the medium resolution remotely sensed data are suitable for monitoring the condition of vegetation in larger areas.
Sekundarne ključne besede: graduation thesis;geodesy;GIG;remote sensing;biophysical variables;vegetation;MERIS;
Vrsta datoteke: application/pdf
Vrsta dela (COBISS): Diplomsko delo/naloga
Komentar na gradivo: Univ. v Ljubljani, Fak. za gradbeništvo in geodezijo
Strani: XII, 33 str., 11 pril.
Vrsta dela (ePrints): thesis
Naslov (ePrints): Monitoring of vegetation condition from remote sensing data
Ključne besede (ePrints): daljinsko zaznavanje;biofizikalne spremenljivke;vegetacija;MERIS
Ključne besede (ePrints, sekundarni jezik): remote sensing;biophysical variables;vegetation;MERIS
Povzetek (ePrints): V diplomski nalogi so predstavljene različne biofizikalne spremenljivke, ki jih lahko pridobimo s pomočjo posnetkov daljinskega zaznavanja. Podani so algoritmi za njihov izračun, kateri so bili preizkušeni na srednje ločljivih daljinsko zaznanih podatkih MERIS. Na osnovi linearne regresije smo ugotavljali medsebojno odvisnost posameznih biofizikalnih spremenljivk. Narejena je bila vizualna primerjava rezultatov z državnim letalskih ortofotom in izdelki, ki so nam na voljo na spletu. Ugotovili smo, da so vse biofizikalne spremenljivke med seboj odvisne. Vsi algoritmi za izračun biofizikalnih spremenljivk, razen MERIS kopenski indeks klorofila (MTCI, angl. MERIS Terrestrial Chlorophyll Index), so ustrezali namenu. Pri algoritmu MTCI v primeru prisotnosti oblakov in morskih površin prihaja do večjih napak. Ugotovili smo, da so srednje ločljivi podatki daljinskega zaznavanja primerni za spremljanje stanja vegetacije večjih območij.
Povzetek (ePrints, sekundarni jezik): In the graduation thesis different biophysical variables that can be derived from remotely sensed data are presented. The algorithms for their calculations, that have been tested on the medium resolution remotely sensed MERIS data, are given. Based on the linear regression the interdependence of individual biophysical variables has been determined. The visual comparison between our results and digital orthophoto as well as biophysical products, available on the Internet, has been made. We have found out that all biophysical variables are mutually dependent. All the algorithms, needed for calculation of biophysical variables, except the MERIS Terrestrial Chlorophyll Index (MTCI), were suitable for the purpose. At the algorithm MTCI in case when clouds and sea surfaces are present more significant mistakes may occur. Further on, we have realized that the medium resolution remotely sensed data are suitable for monitoring the condition of vegetation in larger areas.
Ključne besede (ePrints, sekundarni jezik): remote sensing;biophysical variables;vegetation;MERIS
ID: 8312875