Mogućnost procjene prinosa lucerne i djetelinsko-travnih smjesa korištenjem satelitskih snimaka Landsat 8 i 9

master's thesis

• Title (english): Evaluating the yield of alfalfa and clover-grass mixtures using Landsat 8 and 9 satellite imagery
• Author: Tin Batur
• Mentor: Hrvoje Kutnjak (mentor)
• Committee member: Hrvoje Kutnjak (predsjednik povjerenstva)
• Committee member: Boris Lazarević (član povjerenstva)
• Committee member: Aleksandra Perčin (član povjerenstva)
• Granter: University of Zagreb; Faculty of Agriculture; (Department of Field Crops, Forage and Grassland); Zagreb
• Defense date and country: 2023-09-29, Croatia
• Scientific / art field, discipline and subdiscipline: BIOTECHNICAL SCIENCES; Agronomy

Abstract

Precizna poljoprivreda se oslanja na moderne tehnologije poput GNSS-a i daljinskog motrenja za racionalnije upravljanje vrijednim resursima na poljoprivrednom gospodarstvu. Korištenjem podataka o refleksiji svjetlosti s lista dobivamo uvid u bujnost vegetacije i varijabilnost unutar usjeva. Informaciju o varijabilnosti možemo iskoristiti za prilagodbu agrotehničkih mjera u svrhu povećanja kvalitete i količine prinosa. Cilj ovog rada bio je utvrditi korelaciju vrijednosti vegetacijskih indeksa dobivenih analizom satelitskih snimaka Landsat 8 i 9 s gravimetrijski izmjerenim prinosom lucerne i djetelinsko-travnih smjesa. Kao pokazatelj reprezentativnosti regresije korišten je koeficijent determinacije između vrijednosti triju različitih vegetacijskih indeksa i količine prinosa suhe tvari i zelene mase u tri košnje usjeva. Rezultati su pokazali čvršće veze vegetacijskih indeksa s prinosom zelene mase nego s prinosom suhe tvari i time imaju mjesto kao obećavajuć alat u planiranju proizvodnje daljinskim motrenjem.

Abstract (english)

Precision agriculture relies on modern technologies such as GNSS and remote sensing to efficiently manage valuable farm resources. Using data on light reflected from leaves, we gain insights into the vegetation density and variability within the crop. Information about this variability can be used to adjust agrotechnical measures in order to increase yield quality and quantity. The aim of this study was to determine the correlation between the values of vegetation indices obtained through the analysis of Landsat 8 and 9 satellite images and gravimetrically measured yields of alfalfa and clover-grass mixtures. The coefficient of determination was used as an indicator of the regression representativeness between the values of three different vegetation indices and the yield of dry matter and fresh cut biomass in three crop harvests. The results showed stronger connections of vegetation indices with fresh cut biomass yield than with dry matter yield, indicating their potential as a promising tool in production planning through remote sensing.

• Keywords: precizna poljoprivreda; Landsat 8 i 9; prognoza prinosa; lucerna; DTS
• Keywords (english): precision agriculture; Landsat 8 and 9; yield prediction; Landsat; Alfalfa; CGM
• Language: croatian
• URN:NBN: urn:nbn:hr:204:123847
• Study programme: Title: Agroecology; Study programme type: university; Study level: graduate; Academic / professional title: magistar/ magistra inženjer/inženjerka agroekologije (magistar/ magistra inženjer/inženjerka agroekologije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2023-11-07 13:23:06