The aim of this PhD thesis was an objective assessment of application of VNIR spectroscopy for predicting properties of forest soils. For each soil property were found the most appropriate combination of statistical methods for pre-processing (continuum removal, 1. derivation, 2. derivation) and processing (PLSR, PCR, SVM) of certain spectral bands. As generally successful shows a combination of methods 1. derivation and support vector machine throughout the VNIR spectral range (400-2500 nm). In some cases, however, they proved to other models. Among the best predictable features include pH, content of oxidizable carbon, aluminum, iron, silicon, or calcium (at higher concentrations). Not very high success rate prediction was found in indicators that take low values (sodium, manganese, aluminum or ferrous complexes). The results show that VNIR spectroscopy method is applicable for predicting properties of forest soils. It can not completely replace traditional analysis, but it can very well complement, especially in practice. For example, when the soil mapping can help thicken network data and refine the information better than other methods of spatial estimation. It is applicable in cases where it is required large amounts of data in a short timeframe and at minimal cost. It is suitable for monitoring trends over time, or for a quick survey of an area.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:259622 |
| Date | January 2015 |
| Creators | Kratina, Josef |
| Contributors | Borůvka, Luboš, Lucie, Lucie |
| Publisher | Česká zemědělská univerzita v Praze |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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