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HYPOS aerial hyperspectral campaign
Hanuš, Jan ; Homolová, Lucie ; Janoutová, Růžena
The ESA project HYPOS (Hyper-Spectral Analysis and Heterogeneous Surface Modeling) was solved by CzechGlobe together with three French partners (Magellium, CESBIO, IRSTEA) between 2016 and 2018. The task of the project was to create algorithms for estimating vegetation parameters from hyperspectral data and to define the most suitable spectral bands for estimation of parameters from multispectral data.
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Application of imaging spectroscopy in monitoring of vegetation stress caused by soil pollutants in the Sokolov lignite basin
Mišurec, Jan ; Kupková, Lucie (advisor) ; Pavelka, Karel (referee) ; Homolová, Lucie (referee)
Forests can be considered as one of the most important Earth's ecosystems not only because of oxygen production and carbon sequestration via photosynthesis, but also as a source of many natural resources (such as wood) and as a habitat of many specific plants and animals. Monitoring of forest health status is thus crucial activity for keeping all production and ecosystem functions of forests. The main aim of the thesis is development of an alternative approach for forest health status based on airborne hyperspectral data (HyMap) analysis supported by field sampling. The proposed approach tries to use similar vegetation parameters which are used in case of the current methods of forest health status assessment based on field inspections. It is believed that importance of such new methods will significantly increase in the time when the planned satellite hyperspectral missions (e.g. EnMap) will move into operational phase. The developed forest health monitoring approach is practically demonstrated on mature Norway spruce (Picea abies L. Karst) forests of the Sokolov lignite basin which were affected by long-term coal mining and heavy industry and therefore high variability of forest health status was assumed in this case. Two leaf level radiative transfer models were used for simulating spectral...
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Description and metabolites of pharmaceutical and toxicological important plants I.
Homolová, Lucie ; Opletal, Lubomír (advisor) ; Macáková, Kateřina (referee)
VIII. ABSTRACT HOMOLOVÁ Lucie, Description and metabolites of pharmaceutically and toxicologically important plants, Thesis, Charles University in Prague, Faculty of Pharmacy in Hradec Králové, Department of Pharmaceutical Botany and Ecology, Hradec Králové 2008, 90 pp. In this thesis 31 pharmaceutically and toxicologically important or interesting plants are described. The work is focused especially on metabolites and use of these plants - therapeutical, folk and tradicional medicine, in some cases also in food-processing industry. Prahmacopoeial and non-pharmacopoeial monographs and dosage are also listed. For this thesis plants which are used in folk medicine even though the contents of substances does not conform to it were chosen. Other recorded plants were primarily used for some particular reasons but now some other important substances are extracted from them. Also plants that are toxic and can not be recommended for treating diseases but are still used in folk medicine are described. In the end the actual utilization and benefits of each plant are evaluated. Key words:
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Potential of the sentinel-2 red edge spectral bands for estimation of eco-physiological plant parameters
Malenovský, Zbyněk ; Homolová, Lucie ; Janoutová, Růžena ; Landier, L. ; Gastelluetchegorry, J-P. ; Bertholt, B. ; Huck, A.
In this study we investigated importance of the spaceborne instrument Sentinel-2 red edge spectral bands and reconstructed red edge position (REP) for retrieval of the three eco-physiological plant parameters, leaf and canopy chlorophyll content and leaf area index (LAI), in case of maize agricultural fields and beech and spruce forest stands. Sentinel-2 spectral bands and REP of the investigated vegetation canopies were simulated in the Discrete Anisotropic Radiative Transfer (DART) model. Their potential for estimation of the plant parameters was assessed through training support vector regressions (SVR) and examining their P-vector matrices indicatingsignificance of each input. The trained SVR were then applied on Sentinel-2 simulated images and the acquired\nestimates were cross-compared with results from high spatial resolution airborne retrievals. Results showed that contribution of REP was significant for canopy chlorophyll content, but less significant for leaf chlorophyll content and insignificant for leaf area index estimations. However, the red edge spectral bands contributed strongly to the retrievals of all parameters, especially canopy and leaf chlorophyll content. Application of SVR on Sentinel-2 simulated images demonstrated, in general, an overestimation of leaf chlorophyll content and an underestimation of LAI when compared to the reciprocal airborne estimates. In the follow-up investigation, we will apply the trained SVR algorithms on real Sentinel-2 multispectral images acquired during vegetation seasons 2015 and 2016.
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Potentials of the VNIR airborne hyperspectral system AISA Eagle
Hanuš, Jan ; Malenovský, Zbyněk ; Homolová, Lucie ; Kaplan, Věroslav ; Cudlín, Pavel ; Lukeš, Petr
Airborne hyperspectral remote sensing (imaging spectroscopy) sensors acquire images of several (from tens to hundreds) narrow spectral bands in visible, near and short infrared wavelengths. Use of hyperspectral remote sensing (RS) data in scientific and even commercial applications is quite broad, starting from agriculture, forestry, and natural vegetation (precision farming, assessment of general plant status, biomass estimation, species composition mapping), through geology (mapping of minerals, land degradation assessment), up to limnology (water quality evaluation), and other domains. Since 2004 the Institute of Systems Biology and Ecology (ISBE) (Academy of Sciences of the Czech Republic) has been operating the VNIR airborne hyperspectral sensor AISA Eagle. The workgroup for remote sensing of vegetation at ISBE is currently capable to facilitate the complete flight/ground hyperspectral campaign including the standard image data pre-processing.
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