Image analysis with environmental applications
Kaukokartoitusmenetelmiä käytetään tarkkuusmaataloudessa ja metsien inventoinnissa. Pro gradu -tutkielma keskittyy parantamaan analysointiprosessia kasvillisuusmäärien arvioimiseksi esikäsitellyistä ilmakuvista ja digitaalisesta korkeusmallista. Tutkielmassa esitellään evolutiivinen optimointimenetelmä viljapellon biomassojen estimoimiseksi ja tutkitaan biomassaestimaattien tekoa eri menetelmin radiometrisesti korjatuista spektrikaistoista. Tutkielmassa pohditaan myös vaihtoehtoja puulajeittaisten tilavuuksien estimoimiseksi metsistä. Remote sensing methodologies are employed in the fields of precision agriculture and forest industry. This thesis focuses on enhancing analysation process for making vegetation volume estimates from pre-processed aerial images and Digital Surface Models. An evolutionary optimisation system for learning crop field biomasses is proposed and making estimates using radiometrically corrected spectral bands with different tools is studied. This thesis also considers methods for estimating forest stem volumes by tree species.
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GIS-data related route optimization, hierarchical clustering, location optimization, and kernel density methods are useful for promoting distributed bioenergy plant planning in rural areas
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