62 research outputs found

    Hyperspectral Remote Sensing Data Analysis and Future Challenges

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    Satellite-based monitoring of pasture degradation on the Tibetan Plateau: A multi-scale approach

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    The Tibetan Plateau has been entitled Third-Pole-Environment'' because of its outstanding importance for the global climate and the hydrological system of East and Southeast Asia. Its climatological and hydrological influences are strongly affected by the local vegetation which is supposed to be subject to ongoing degradation. The degradation of the Tibetan pastures was investigated on the local scale by numerous studies. However, because methods and scales substantially differed among the previous studies, the overall pattern of degradation on the Tibetan Plateau is hitherto unknown. Consequently, the aims of this thesis are to monitor recent changes in the grassland degradation on the Tibetan Plateau and to detect the underlying driving forces of the observed changes. Therefore, a comprehensive remote sensing based approach is developed. The new approach consists of three parts and incorporates different spatial and temporal scales: (i) the development and testing of an indicator system for pasture degradation on the local scale, (ii) the development of a MODIS-based product usable for degradation monitoring from the local to the plateau scale, and (iii) the application of the new product to delineate recent changes in the degradation status of the pastures on the Tibetan Plateau. The first part of the new approach comprised the test of the suitability of a new two-indicator system and its transferability to spaceborne data. The indicators were land-cover fractions (e.g.,~green vegetation, bare soil) derived from linear spectral unmixing and chlorophyll content. The latter was incorporated as a proxy for nutrient and water availability. It was estimated combining hyperspectral vegetation indices as predictors in partial least squares regression. The indicator system was established and tested on the local scale using a transect design and textit{in situ} measured data. The promising results revealed clear spatial patterns attributed to degradation, indicating that the combination of vegetation cover and chlorophyll content is a suitable indicator system for the detection of pasture degradation on local scales on the Tibetan Plateau. To delineate patterns of degradation changes on the plateau scale, the green plant coverage of the Tibetan pastures was derived in the second part. Therefore, an upscaling approach was developed. It is based on satellite data from high spatial resolution sensors on the local scale (WorldView-type) via medium resolution data (Landsat) to low resolution data on the plateau scale (MODIS). The different spatial resolutions involved in the methodology were incorporated to enable the cross-validation of the estimations in the new product against field observations (over 600 plots across the entire Tibetan Plateau). Four methods (linear spectral unmixing, spectral angle mapper, partial least squares regression, and support vector machine regression) were tested on their predictive performance for the estimation of plant cover and the method with the highest accuracy (support vector machine regression) was applied to 14 years of MODIS data to generate a new vegetation coverage product. In the third part, the changes in vegetation cover between the years 2000 and 2013 and their driving forces were investigated by comparing the trends in the new vegetation coverage product against climate variables (precipitation from tropical rainfall measuring mission and 2 m air temperature from ERA-Interim reanalysis data) on the entire Tibetan Plateau. Large areas in southern Qinghai were identified where vegetation cover increased as a result of positive precipitation trends. Thus, degradation did not proceed in these regions. Contrasting with this, large areas in the central and western parts of the Tibetan Autonomous Region were subject to an ongoing degradation. This degradation can be attributed to the coincidence of rising temperatures and anthropogenic induced increases in livestock numbers as a consequence of local land-use change. In those areas, the ongoing degradation influenced local precipitation patterns because sensible heat fluxes were accelerated above degraded pastures. In combination with advected moist air masses at higher atmospheric levels, the accelerated heat fluxes led to an intensification of local convective rainfall. The ongoing degradation detected by the new remote sensing approach in this thesis is alarming. The affected regions encompass the river systems of the Indus and Brahmaputra Rivers, where the ongoing degradation negatively affects the water storage capacities of the soils and enhances erosion. In combination with the feed-back mechanisms between plant coverage and the changed precipitation on the Tibetan Plateau, the reduced water storage capacity will exacerbate runoff extremes in the middle and lower reaches of those important river systems

    Multispectral and Hyperspectral Remote Sensing Data for Mineral Exploration and Environmental Monitoring of Mined Areas

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    In recent decades, remote sensing technology has been incorporated in numerous mineral exploration projects in metallogenic provinces around the world. Multispectral and hyperspectral sensors play a significant role in affording unique data for mineral exploration and environmental hazard monitoring. This book covers the advances of remote sensing data processing algorithms in mineral exploration, and the technology can be used in monitoring and decision-making in relation to environmental mining hazard. This book presents state-of-the-art approaches on recent remote sensing and GIS-based mineral prospectivity modeling, offering excellent information to professional earth scientists, researchers, mineral exploration communities and mining companies

    Visible and Near Infrared imaging spectroscopy and the exploration of small scale hydrothermally altered and hydrated environments on Earth and Mars

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    The use of Visible and Near Infrared (VNIR) imaging spectroscopy is a cornerstone of planetary exploration. This work shall present an investigation into the limitations of scale, both spectral and spatial, in the utility of VNIR images for identifying small scale hydrothermal and potential hydrated environments on Mars, and regions of the Earth that can serve as martian analogues. Such settings represent possible habitable environments; important locations for astrobiological research. The ESA/Roscosmos ExoMars rover PanCam captures spectrally coarse but spatially high resolution VNIR images. This instrument is still in development and the first field trial of an emulator fitted with the final set of geological filters is presented here. Efficient image analysis techniques are explored and the ability to accurately characterise a hydrothermally altered region using PanCam data products is established. The CRISM orbital instrument has been returning hyperspectral VNIR images with an 18 m2 pixel resolution since 2006. The extraction of sub-pixel information from CRISM pixels using Spectral Mixture Analysis (SMA) algorithms is explored. Using synthetic datasets a full SMA pipeline consisting of publically available Matlab algorithms and optimised for investigation of mineralogically complex hydrothermal suites is developed for the first time. This is validated using data from Námafjall in Iceland, the region used to field trial the PanCam prototype. The pipeline is applied to CRISM images covering four regions on Mars identified as having potentially undergone hydrothermal alteration in their past. A second novel use of SMA to extract a unique spectral signature for the potentially hydrated Recurring Slope Lineae features on Mars is presented. The specific methodology presented shows promise and future improvements are suggested. The importance of combining different scales of data and recognising their limitations is discussed based on the results presented and ways in which to take the results presented in this thesis forward are given

    Remote sensing of reef fish communities

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    During the last three decades of coral reefs studies, the large areal coverage of data derived from satellite images has increasingly been used to complement the more detailed but spatially limited data produced by conventional fieldwork. Continuous improvement in sensor capabilities, along with the development of increasingly refined methods for image processing, has lead to ever more accurate maps of physical and biological variables of importance to reef ecology. During the same period, an abundance of field studies have documented statistical relationships between aspects of the reef habitat and its fish community. Despite numerous stochastic influences, such as spatially concentrated and temporally variable fish recruitment pulses or the selective and patchy mortality caused by fishing, several aspects of habitat have been shown to significantly influence the fish community. Fortunately the most important of these, water depth, the structural complexity of the reef, and the cover of live coral, are possible to estimate from currently available satellite imagery. The research presented in the following pages has combined the statistical relationships between the fish community and its habitat with the capability of satellite imagery to map that habitat, thereby answering the research question: How can remote sensing be used to map coral reef fish communities? In the process, a set of new techniques for predictive modeling of complex relationships have been compared, the influence of a range of habitat variables on the fish community quantified, the spatial scales at which the fish-habitat relationships are strongest have been explored, and new methods for deriving estimates of some aspects of the coral reef habitat from satellite imagery have been developed. The results presented in this thesis thus contribute to the further understanding of fish-habitat relationships, while providing a template for producing spatially explicit predictive models of fish community variables. This is not only of scientific interest, but also of substantial value to the conservation community that tries to protect the world’s remaining healthy coral reef ecosystems, and their fish communities, from an array of man-made influences
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