Enviromentální aplikace obrazové spektroskopie

The main purpose of this thesis is to use Image Spectroscopy as a tool to monitor the environmental conditions in a region affected by anthropogenic activities via estimating both geochemical and biochemical parameters on a regional scale. The research has been carried on the Sokolov lignite mine, NW Bohemia, a region affected by long-term extensive mining. The thesis is divided into two thematic parts. First part is devoted to applications of Image Spectroscopy into Acid Mine Drainage mapping and its related issues (chapters 2 and 3). In chapter 2 the equivalent mineral end-members were successfully derived from the ASTER image data (Advanced Space-borne Thermal Emission and Reflection Radiometer satellite data). In the chapter 3 the pH was estimated on the basis of mineral and image spectroscopy. The Multi Range Spectral Feature Fitting (MRSFF) technique was utilized for mineral mapping and the multiple regression model using the fit images, the results of MRSFF, as inputs was constructed to estimate the surface pH and statistical significant accuracy was attained. In the second thematic part (chapters 4-6) Image Spectroscopy is applied into monitoring of vegetation stress. A new statistical method was developed to assess the physiological status of macroscopically undamaged foliage of Norway...Předložená disertační práce se věnuje aplikaci metod obrazové spektroskopie jako moderního nástroje pro environmentální monitoring, přičemž se zaměřuje na modelování vybraných geochemických a biochemických parametrů Disertační práce je členěna do dvou tematických celků. První z nich (kapitoly 2 a 3) je věnován aplikaci minerální a obrazové spektroskopie pro vymezení plošného výskytu povrchové acidifikace (anglický termín: AMD - Acid Mine Drainage) a modelování povrchového pH. Druhá tematická část (kapitoly 4, 5 a 6) se věnuje zhodnocení fyziologického stavu smrkových porostů. V kapitole 2 jsou s využitím satelitních dat ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer satellite data) plošně vymezeny kyselé zvětralinové povrchy (pH<4), jež charakterizuje výskyt jarositu a lignitu (hnědé uhlí). Kapitola 3 se věnuje vytvoření modelu pro odhad povrchového pH odkrytých substrátů s využitím leteckých hyperspektrálních dat HyMap (07/2009). Tato studie je jednou z prvních, jež aplikuje metody obrazové spektroskopie pro kvantitativní modelování pH v prostředí povrchových dolů vyznačující se vysokou heterogenitou. V druhé tematické části je obrazová spektroskopie aplikována do oblasti monitoringu zdravotního stavu lesních smrkových porostů, které se vyskytují v bezprostředním okolí...Department of Applied Geoinformatics and CartographyKatedra aplikované geoinformatiky a kartografieFaculty of SciencePřírodovědecká fakult

Arc-like magmatism in syn- to post-collisional setting: The Ediacaran Angra Fria Magmatic Complex (NW Namibia) and its cross-Atlantic correlatives in the south Brazilian Florianópolis Batholith

Ediacaran syn-tectonic plutonic rocks (amphibole gabbros, quartz diorites/tonalites to biotite- and muscovite-bearing granites) of the Angra Fria Magmatic Complex (Kaoko Belt, north-western Namibia) belong to two compositionally similar, magnesian, transitional tholeiitic–calc-alkaline suites, the Older (∼625–620 Ma) and the Younger (∼585–575 Ma). Both have counterparts in the broadly contemporaneous Florianópolis Batholith (southern Brazil), from which they were separated during the Cretaceous opening of the southern Atlantic. In the Angra Fria Magmatic Complex, the only unequivocal mantle contributions are identified in mingling zones of the Younger Suite and hybrid mafic–intermediate dykes of uncertain age. Previously published Hf-in-zircon isotopic data, together with new whole-rock geochemical and Sr–Nd isotopic signatures, underline an important role of crustal anatexis of a material with late Palaeoproterozoic to early Mesoproterozoic mean crustal residence (1.9–1.5 Ga). This interval resembles some of the published Nd model ages for Tonian ‘Adamastor Rift’-related felsic magmatic rocks in the Namibian Coastal and Uruguayan Punta del Este terranes. In detail, the Older Suite probably originated mainly by fluid-present melting of metabasalts and metatonalites, followed by (near) closed-system fractional crystallization (with or without accumulation) of amphibole ± plagioclase. For the Younger Suite, the principal process was the dehydration melting of relatively felsic lower crustal protoliths (metagreywackes or intermediate–acid orthogneisses >> metapelites), leaving garnet in the residue. Based on the geological context, the conspicuous enrichment of hydrous-fluid-mobile large ion lithophile over the conservative high field strength elements is not interpreted through a classic model of oceanic plate subduction, devolatilization, and fluxed-melting of the overriding mantle wedge. Instead, it is thought to reflect high-grade metamorphism of deeply buried continental crust and attendant water-fluxed melting of the overlying crustal lithologies, connected with inversion of the Tonian ‘Adamastor Rift’

Landslide databases in the Geological Surveys of Europe

Acceso electrónico sólo desde el IGMELandslides are one of the most widespread geohazards in Europe, producing significant social and economic impacts. Rapid population growth in urban areas throughout many countries in Europe and extreme climatic scenarios can considerably increase landslide risk in the near future. Variability exists between European countries in both the statutory treatment of landslide risk and the use of official assessment guidelines. This suggests that a European Landslides Directive that provides a common legal framework for dealing with landslides is necessary. With this long-term goal in mind, this work analyzes the landslide databases from the Geological Surveys of Europe focusing on their interoperability and completeness. The same landslide classification could be used for the 849,543 landslide records from the Geological Surveys, from which 36% are slides, 10% are falls, 20% are flows, 11% are complex slides, and 24% either remain unclassified or correspond to another typology. Most of them are mapped with the same symbol at a scale of 1:25,000 or greater, providing the necessary information to elaborate European-scale susceptibility maps for each landslide type. A landslide density map was produced for the available records from the Geological Surveys (LANDEN map) showing, for the first time, 210,544 km2 landslide-prone areas and 23,681 administrative areas where the Geological Surveys from Europe have recorded landslides. The comparison of this map with the European landslide susceptibility map (ELSUS 1000 v1) is successful for most of the territory (69.7%) showing certain variability between countries. This comparison also permitted the identification of 0.98 Mkm2 (28.9%) of landslide-susceptible areas without records from the Geological Surveys, which have been used to evaluate the landslide database completeness. The estimated completeness of the landslide databases (LDBs) from the Geological Surveys is 17%, varying between 1 and 55%. This variability is due to the different landslide strategies adopted by each country. In some of them, landslide mapping is systematic; others only record damaging landslides, whereas in others, landslide maps are only available for certain regions or local areas. Moreover, in most of the countries, LDBs from the Geological Surveys co-exist with others owned by a variety of public institutions producing LDBs at variable scales and formats. Hence, a greater coordination effort should be made by all the institutions working in landslide mapping to increase data integration and harmonization.Earth Observation and Geohazards Expert Group (EOEG), EuroGeoSurveys, the Geological Surveys of Europe, BélgicaGeohazards InSAR Laboratory and Modeling Group, Instituto Geológico y Minero de España, EspañaRisk and Prevention Division, Bureau de Recherches Géologiques et Minières, FranciaEngineering Geology Department, Institute of Geology and Mineral Exploration, GreciaGeoHazard team, Geological Institute of Romania, RumaníaGeological Survey of Slovenia, EsloveniaCroatian Geological Survey, CroaciaItalian Institute for Environmental Protection and Research, Geological Survey of Italy, ItaliaSwiss Federal Office for the Environment, SuizaGeological Survey of Austria, AustriaPolish Geological Institute, National Research Institute, PoloniaGeological Survey of Ireland, IrlandaCzech Geological Survey, República ChecaFederal Institute for Geosciences and Natural Resources, AlemaniaGeological Survey of Norway, NoruegaCyprus Geological Survey, ChipreGeological Survey of Sweden, SueciaInstitut Cartogràfic i Geològic de Catalunya, EspañaBritish Geological Survey, Reino UnidoGeological Survey of Slovakia, EslovaquiaGeological Survey of Lithuania, LituaniaFederalni zavod za geologiju, Bosnia y HerzegovinaGeological Survey of Estonia, EstoniaLaboratório Nacional de Energia e Geologia, PortugalGeological Survey of Hungary, HungríaNorwegian Water and energy Directorate of Norway, Norueg

Applying Spectral Unmixing to Determine Surface Water Parameters in a Mining Environment

Compared to natural waters, mine waters represent an extreme water type that is frequently heavily polluted. Although they have been traditionally monitored by in situ measurements of point samples taken at regular intervals, the emergence of a new generation of multispectral and hyperspectral (HS) sensors means that image spectroscopy has the potential to become a modern method for monitoring polluted surface waters. This paper describes an approach employing linear Spectral Unmixing (LSU) for analysis of hyperspectral image data to map the relative abundances of mine water components (dissolved Fe—Fediss, dissolved organic carbon—DOC, undissolved particles). The ground truth data (8 monitored ponds) were used to validate the results of spectral mapping. The same approach applied to HS data was tested using the image data resampled to WorldView2 (WV2) spectral resolution. A key aspect of the image data processing was to define the proper pure image end members for the fundamental water types. The highest correlations detected between the studied water parameters and the fractional images using the HyMap and the resampled WV2 data, respectively, were: dissolved Fe (R2 = 0.74 and R2vw2 = 0.6), undissolved particles (R2 = 0.57 and R2vw2 = 0.49) and DOC (R2 = 0.42 and R2vw2 < 0.40). These fractional images were further classified to create semi-quantitative maps. In conclusion, the classification still benefited from the higher spectral resolution of the HyMap data; however the WV2 reflectance data can be suitable for mapping specific inherent optical properties (SIOPs), which significantly differ from one another from an optical point of view (e.g., mineral suspension, dissolved Fe and phytoplankton), but it seems difficult to differentiate among diverse suspension particles, especially when the waters have more complex properties (e.g., mineral particles, DOC together with tripton or other particles, etc.)

Hyperspectral Remote Sensing for Environmental Mapping and Monitoring

The main purpose of this thesis is to use Image Spectroscopy as a tool to monitor the environmental conditions in a region affected by anthropogenic activities via estimating both geochemical and biochemical parameters on a regional scale. The research has been carried on the Sokolov lignite mine, NW Bohemia, a region affected by long-term extensive mining. The thesis is divided into two thematic parts. First part is devoted to applications of Image Spectroscopy into Acid Mine Drainage mapping and its related issues (chapters 2 and 3). In chapter 2 the equivalent mineral end-members were successfully derived from the ASTER image data (Advanced Space-borne Thermal Emission and Reflection Radiometer satellite data). In the chapter 3 the pH was estimated on the basis of mineral and image spectroscopy. The Multi Range Spectral Feature Fitting (MRSFF) technique was utilized for mineral mapping and the multiple regression model using the fit images, the results of MRSFF, as inputs was constructed to estimate the surface pH and statistical significant accuracy was attained. In the second thematic part (chapters 4-6) Image Spectroscopy is applied into monitoring of vegetation stress. A new statistical method was developed to assess the physiological status of macroscopically undamaged foliage of Norway..

Integration of Absorption Feature Information from Visible to Longwave Infrared Spectral Ranges for Mineral Mapping

Merging hyperspectral data from optical and thermal ranges allows a wider variety of minerals to be mapped and thus allows lithology to be mapped in a more complex way. In contrast, in most of the studies that have taken advantage of the data from the visible (VIS), near-infrared (NIR), shortwave infrared (SWIR) and longwave infrared (LWIR) spectral ranges, these different spectral ranges were analysed and interpreted separately. This limits the complexity of the final interpretation. In this study a presentation is made of how multiple absorption features, which are directly linked to the mineral composition and are present throughout the VIS, NIR, SWIR and LWIR ranges, can be automatically derived and, moreover, how these new datasets can be successfully used for mineral/lithology mapping. The biggest advantage of this approach is that it overcomes the issue of prior definition of endmembers, which is a requested routine employed in all widely used spectral mapping techniques. In this study, two different airborne image datasets were analysed, HyMap (VIS/NIR/SWIR image data) and Airborne Hyperspectral Scanner (AHS, LWIR image data). Both datasets were acquired over the Sokolov lignite open-cast mines in the Czech Republic. It is further demonstrated that even in this case, when the absorption feature information derived from multispectral LWIR data is integrated with the absorption feature information derived from hyperspectral VIS/NIR/SWIR data, an important improvement in terms of more complex mineral mapping is achieved

Testing a Modified PCA-Based Sharpening Approach for Image Fusion

Image data sharpening is a challenging field of remote sensing science, which has become more relevant as high spatial-resolution satellites and superspectral sensors have emerged. Although the spectral property is crucial for mineral mapping, spatial resolution is also important as it allows targeted minerals/rocks to be identified/interpreted in a spatial context. Therefore, improving the spatial context, while keeping the spectral property provided by the superspectral sensor, would bring great benefits for geological/mineralogical mapping especially in arid environments. In this paper, a new concept was tested using superspectral data (ASTER) and high spatial-resolution panchromatic data (WorldView-2) for image fusion. A modified Principal Component Analysis (PCA)-based sharpening method, which implements a histogram matching workflow that takes into account the real distribution of values, was employed to test whether the substitution of Principal Components (PC1–PC4) can bring a fused image which is spectrally more accurate. The new approach was compared to those most widely used—PCA sharpening and Gram–Schmidt sharpening (GS), both available in ENVI software (Version 5.2 and lower) as well as to the standard approach—sharpening Landsat 8 multispectral bands (MUL) using its own panchromatic (PAN) band. The visual assessment and the spectral quality indicators proved that the spectral performance of the proposed sharpening approach employing PC1 and PC2 improve the performance of the PCA algorithm, moreover, comparable or better results are achieved compared to the GS method. It was shown that, when using the PC1, the visible-near infrared (VNIR) part of the spectrum was preserved better, however, if the PC2 was used, the short-wave infrared (SWIR) part was preserved better. Furthermore, this approach improved the output spectral quality when fusing image data from different sensors (e.g., ASTER and WorldView-2) while keeping the proper albedo scaling when substituting the second PC

Modelling Diverse Soil Attributes with Visible to Longwave Infrared Spectroscopy Using PLSR Employed by an Automatic Modelling Engine

The study tested a data mining engine (PARACUDA®) to predict various soil attributes (BC, CEC, BS, pH, Corg, Pb, Hg, As, Zn and Cu) using reflectance data acquired for both optical and thermal infrared regions. The engine was designed to utilize large data in parallel and automatic processing to build and process hundreds of diverse models in a unified manner while avoiding bias and deviations caused by the operator(s). The system is able to systematically assess the effect of diverse preprocessing techniques; additionally, it analyses other parameters, such as different spectral resolutions and spectral coverages that affect soil properties. Accordingly, the system was used to extract models across both optical and thermal infrared spectral regions, which holds significant chromophores. In total, 2880 models were evaluated where each model was generated with a different preprocessing scheme of the input spectral data. The models were assessed using statistical parameters such as coefficient of determination (R2), square error of prediction (SEP), relative percentage difference (RPD) and by physical explanation (spectral assignments). It was found that the smoothing procedure is the most beneficial preprocessing stage, especially when combined with spectral derivation (1st or 2nd derivatives). Automatically and without the need of an operator, the data mining engine enabled the best prediction models to be found from all the combinations tested. Furthermore, the data mining approach used in this study and its processing scheme proved to be efficient tools for getting a better understanding of the geochemical properties of the samples studied (e.g., mineral associations)

Assessment of Red-Edge Position Extraction Techniques: A Case Study for Norway Spruce Forests Using HyMap and Simulated Sentinel-2 Data

Systematic quantification and monitoring of forest biophysical and biochemical variables is required to assess the response of ecosystems to climate change and gain a deeper understanding of the carbon cycle. Red-Edge Position (REP) is a hyperspectrally detectable parameter, which is sensitive to Chlorophyll (Chl) content. In the current study, REP was modelled for Norway spruce Forest canopy Reflectance and Transmittance (FRT) using Radiative Transfer Modelling (RTM) (resampled to HyMap and Sentinel-2 spectral resolution) as well as calculated from the real HyMap and simulated Sentinel-2 image data. Different REP extraction methods (PF, LE, 4PLI and its optimized versions for HyMap and Sentinel-2 spectral resolution) were assessed. The lowest differences in REP values calculated from image-extracted spectra and from the theoretical RTM simulations were found for the 4PLI method including its HyMap and Sentinel-2 optimized versions (4PLIH and 4PLIS). Despite its simplicity, the 4PLI REP extraction technique demonstrated its potential usefulness for estimating canopy chlorophyll (Chl × LAI) content using both airborne hyperspectral (HyMap) data as well as space-borne Sentinel-2 image data

Canopy Top, Height and Photosynthetic Pigment Estimation Using Parrot Sequoia Multispectral Imagery and the Unmanned Aerial Vehicle (UAV)

Remote sensing is one of the modern methods that have significantly developed over the last two decades and, nowadays, it provides a new means for forest monitoring. High spatial and temporal resolutions are demanded for the accurate and timely monitoring of forests. In this study, multi-spectral Unmanned Aerial Vehicle (UAV) images were used to estimate canopy parameters (definition of crown extent, top, and height, as well as photosynthetic pigment contents). The UAV images in Green, Red, Red-Edge, and Near infrared (NIR) bands were acquired by Parrot Sequoia camera over selected sites in two small catchments (Czech Republic) covered dominantly by Norway spruce monocultures. Individual tree extents, together with tree tops and heights, were derived from the Canopy Height Model (CHM). In addition, the following were tested: (i) to what extent can the linear relationship be established between selected vegetation indexes (Normalized Difference Vegetation Index (NDVI) and NDVIred edge) derived for individual trees and the corresponding ground truth (e.g., biochemically assessed needle photosynthetic pigment contents) and (ii) whether needle age selection as a ground truth and crown light conditions affect the validity of linear models. The results of the conducted statistical analysis show that the two vegetation indexes (NDVI and NDVIred edge) tested here have the potential to assess photosynthetic pigments in Norway spruce forests at a semi-quantitative level; however, the needle-age selection as a ground truth was revealed to be a very important factor. The only usable results were obtained for linear models when using the second year needle pigment contents as a ground truth. On the other hand, the illumination conditions of the crown proved to have very little effect on the model’s validity. No study was found to directly compare these results conducted on coniferous forest stands. This shows that there is a further need for studies dealing with a quantitative estimation of the biochemical variables of nature coniferous forests when employing spectral data that were acquired by the UAV platform at a very high spatial resolution