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Uporaba časovne serije satelitskih posnetkov za ugotavljanje sušnega stresa na izbrani poljščini v Prekmurju
Vertačnik, Maruša (Author), Glavan, Matjaž (Mentor) More about this mentor... This link opens in a new window, Oštir, Krištof (Co-mentor)

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Abstract
Uporaba posnetkov daljinskega zaznavanja pri spremljanju suše predstavlja veliko prednost pri zaznavanju posledic suše na rastlinstvu, saj omogoča merjenja in opazovanja v časovnem nizu. Z visokoločljivimi satelitskimi posnetki satelita Sentinel-2 smo v letih 2016 in 2017 spremljali rast in razvoj izbrane poljščine koruze. Raziskovalno območje so bile kmetijske površine v okolici Murske Sobote. Zanimalo nas je, ali lahko z izračunom vegetacijskega indeksa NDVI opazimo spremembe v posevku koruze, ki je bila izpostavljena različnim biotskim in abiotskim stresom. Hkrati smo želeli ugotoviti, če se pri tem vizualno stanje posevka razlikuje od stanja ocenjenega s satelitskimi posnetki. V raziskavo smo vključili njive, posejane s koruzo, na težkih in lahkih tleh. Del njiv je bil namakan, del pa izpostavljen naravnim padavinskim razmeram. Rezultati so pokazali, da indeks NDVI odraža vodni stres vegetacije, ki se izrazi kot rumenenje in sušenje listov. V začetnih znakih pomanjkanja vode se stanje rastlin na terenu razlikuje od satelitskih posnetkov. Indeks NDVI je na namakanih tleh na vrhuncu rastne dobe statistično značilno večji kot na nenamakanih tleh. Namakanje ima torej vpliv na večanje indeksa, kar odraža vegetacijo v boljši kondiciji. Če primerjamo vpliv teksture tal na vrednosti indeksa, so težka tla sposobna dlje časa zadržati vodo. To vpliva na boljše stanje vegetacije v fazi pospešene rasti in razvoja listov. Ob koncu rastne dobe statistična analiza pokaže večji indeks za lahka namakana tla v primerjavi s težkimi, kar se je odrazilo tudi z meritvami pridelka.

Language:Slovenian
Keywords:daljinsko zaznavanje, Sentinel-2, NDVI, suša, koruza
Work type:Master's thesis/paper (mb22)
Tipology:2.09 - Master's Thesis
Organization:BF - Biotechnical Faculty
Year:2017
Publisher:[M. Vertačnik]
UDC:631.671:581.5:633.15:528.87(043.2)
COBISS.SI-ID:8896121 Link is opened in a new window
Views:590
Downloads:222
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Secondary language

Language:English
Title:Analysis of time series satellite images for detection of drought stress in selected crop in Prekmurje
Abstract:
The use of remote sensing images in the monitoring of drought is a great advantage in detecting the effects of drought on vegetation, since it enables measurement and observation in the time series. The growth and development of selected crop, maize, was monitored with the high-resolution satellite imagery Sentinel-2. Selected research area were agricultural lands in Murska Sobota between years 2016 and 2017. By calculating the NDVI vegetation index, we wanted to find out, whether we can observe the changes in maize crop that was exposed to various biotic and abiotic stress. At the same time, we wanted to determine if the visual condition of the crop differs from that of the estimated satellite imagery. The study includes fields covered with maize on both heavy and light soils. One part of the fields was irrigated, while the second part was exposed to natural precipitation. The results showed that the NDVI index has detected when vegetation is in water stress. In reality, this is expressed as yellowing and drying of leaves. In the initial signs of water scarcity, the condition of plants in the field is different from the satellite imagery. At the peak of the growing season the NDVI index on irrigated soils is statistically higher than on non-irrigated. Thus, the irrigation has an impact on increasing the index, which reflects vegetation in better condition. Compared to the impact of the soil texture on the index values, heavy soils can retain water for longer periods of time. This results in better vegetation during the accelerated growth and leaf development phase. At the end of the vegetation period, the statistical analysis shows larger index for light soils compared to the heavy ones, which coincides with the highest yields on irrigated light soils.

Keywords:remote sensing, Sentinel-2, NDVI, drought, maize

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