18 research outputs found

    Remote Sensing

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    This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

    Earth Observation: Data, Processing and Applications. Volume 2C: Processing — Image Transformations

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    [Edited by] Harrison, B.A., Jupp, D.L.B., Lewis, M.M., Sparks, T., Mueller, N., Byrne,

    A novel approach to estimate glacier mass balance in the Tien Shan and Pamir based on transient snowline observations

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    Glaciers are recognised as an excellent proxy for climate change and their centennial massloss has accelerated during the past decades. The Central Asian mountain ranges Tien Shan and Pamir host over 25,000 glaciers that have been observed to respond heterogeneous to climate change. Glacier changes in the region have very important consequences on the water availability for the densely populated lowlands. Despite the significance and severity that climate change exerts on the Central Asian water towers, the glacier response is still poorly understood, hampering sound interpretations and predictions of future threats and opportunities. A significant data gap in the field measurement series from the mid-1990s to around 2010, limits the analysis of long-term trends. Despite the recent efforts to re-established the historical cryospheric monitoring network, continuous long-term glacier mass balance time series remain sparse for Central Asia. Thus, improved temporal and spatial coverage of glacier monitoring is essential. Remote sensing techniques are a powerful tool to study a large number of remotely located and unmeasured glaciers and provide a possibility to partly bridge the aforementioned deficit in data availability. However, the coarse temporal resolution of geodetic mass balance assessments is not suitable to improve the understanding of ongoing processes. This accentuates the indispensable need for improved and extended annual to seasonal observations of mass change of inaccessible and remote glaciers on a cost and labour effective basis as well as for a more elaborated and enhanced, process-orientated methodology. This work provides a combination of detailed in situ measurements and remote sensing based glacier mass change observation from local to regional scale. A multi-level strategy is applied to complement data from long-term glaciological surveys and remote sensing (snowline observations and geodetic mass balance measurements) with numerical modelling to obtain information at high temporal and spatial resolution for individual glaciers. Through modelling constrained with transient snowlines, annual mass balance time series for a large amount of glaciers located in the Tien Shan and Pamir were made available. Such mass balance estimates provide valuable baseline data for climate change assessments, runoff projection, hazard evaluation and enhance process understanding. A better understanding of the regional annual variability of glacier response to climate change in the Pamir and Tien Shan became possible based on the outcome of this thesis. In the presented thesis the results are discussed in detail, the weaknesses and strengths of the developed methodology are unfolded and the relevant perspective and future research outlined.Gletscher sind ausgezeichnete Indikatoren für den Klimawandel. Ihr langjähriger Massen- verlust hat sich in den letzten Jahrzehnten weltweit akzentuiert. Die zentralasiatischen Bergketten Tien Shan und Pamir beherbergen u¨ber 25’000 Gletscher. Studien zeigen, dass diese Gletscher heterogen auf den Klimawandel reagieren. Gletscherver¨anderungen in der Region haben wichtige Auswirkungen auf die Wasserverfügbarkeit für das dicht besiedelte Flachland. Trotz den bedeutenden Konsequenzen welche durch den Klimawandel auf diese regionalen Wasserspeicher ausgeübt wird, ist die Veränderung der Gletscher im Tien Shan und Pamir immer noch relativ unbekannt, was fundierte Interpretationen und Vorhersagen zukünftiger Gefahren und Chancen erschwert. Eine prägnante Datenlücke in den existierenden Messreihen von Mitte der 1990er Jahren bis ca. 2010 schränkt eine detaillierte Analyse langfristiger Entwicklungen weiter ein. Trotz der jüngsten Bemühungen, das historische Kryosphäremessnetz wieder herzustellen, bleiben kontinuierliche Langzeitmessungen für die Gletscher in Zentralasien limitiert. Eine verbesserte zeitliche und räumliche Abdeckung der Gletscherbeobachtungen ist daher unerlässlich. Fernerkundungstechniken sind gängige Methoden, um eine große Anzahl abgelegener und unerforschter Gletscher zu untersuchen. Mit solchen Methoden kann das Defizit an Datenverfügbarkeit der Region teilweise kompensiert werden. Die grobe zeitliche Auflösung der geodätischen Massenbilanzberechnungen und das somit limitierte Prozessverständnis unterstreichen jedoch den unabdingbaren Bedarf nach verbesserten und erweiterten jährlichen bis saisonalen Massenbilanzbeobachtungen. Ab- schätzungen auf ausgedehnter räumlicher Skala, sowie eine stärkere Prozess orientierte Forschung sind nötig. Die vorliegende Arbeit beschreibt eine Kombination aus detaillierten Feldmessungen und Fernerkundungsbeobachtungen der Gletschermassenänderung im Tien Shan und Pamir. Die angewandte Strategie basiert auf mehreren Ebenen aus lokalen bis regionalen Studien. Mit dieser Strategie werden Daten aus langzeit-glaziologischen Feldmessungen und aus der Fernerkundung (Schneelinienbeobachtungen, geodätische Massenbilanzmessungen) mit numerischen Modellierungen komplementieren. Dabei werden Informationen für ausgewählte Gletscher mit hoher zeitlicher und räumlicher Auflösung extrahiert. Durch das Modellieren mit wiederholten Schneelinienbeobachtungen, welche zur Kalibrierung verwendet werden, konnten jährliche Massenbilanzzeitreihen für eine große Anzahl von Gletschern im Studiengebiet berechnet werden. Solche grossräumigen und zeitlich hochaufgelösten Abschätzungen liefern wertvolle Grundlagen für detaillierte Studien über die Auswirkungen des Klimawandels, ermöglichen fundierte Abflussprojektionen und erlauben verbesserte Gefahrenanalysen. Basierend auf den Ergebnissen dieser Arbeit, wird ein besseres Verständnis der regionalen jährlichen Variabilität der Gletscherreaktionen auf den Klimawandel im Pamir und Tien Shan ermöglicht. In der hier vorgelegten Arbeit werden die Resultate im Detail diskutiert, die Schwächen und Stärken der entwickelten Methodik offengelegt und die relevanten Perspektiven abgefasst

    Earth Observation Data, Processing and Applications. Volume 2A. Processing - Basic Image Operations

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    Eds. Harrison, B.A., Jupp, D.L.B., Lewis, M.M, Sparks, T., Phinn, S.F., Mueller, N., Byrne, G

    Mapeamento de óxidos de ferro usando imagens landsat-8/OLI e EO-1/hyperion nos depósitos ferríferos da Serra Norte, província mineral de Carajás, Brasil

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    FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOMapping methods for iron oxides and clay minerals, using Landsat-8/Operational Land Imager (OLI) and Earth Observing 1 (EO-1)/Hyperion imagery integrated with airborne geophysical data, were applied in the N4, N5, and N4WS iron deposits, Serra Norte, Carajás, Brazil. Band ratios were achieved on Landsat-8/OLI imagery, allowing the recognition of the main minerals from iron deposits. The Landsat-8/OLI imagery showed a robust performance for iron oxide exploration, even in vegetated shrub areas. Feature extraction and Spectral Angle Mapper hyperspectral classification methods were carried out on EO-1/Hyperion imagery with good results for mapping high-grade iron ore, the hematite-goethite ratio, and clay minerals from regolith. The EO-1/Hyperion imagery proved an excellent tool for fast remote mineral mapping in open-pit areas, as well as mapping waste and tailing disposal facilities. An unsupervised classification was carried out on a data set consisting of EO-1/Hyperion visible near-infrared 74 bands, Landsat-8/OLI-derived Normalized Difference Vegetation Index, Laser Imaging Detection and Ranging-derived Digital Terrain Model, and high-resolution airborne geophysical data (gamma ray spectrometry, Tzz component of gradiometric gravimetry data). This multisource classification proved to be an adequate alternative for mapping iron oxides in vegetated shrub areas and to enhance the geology of the regolith and mineralized areas463331349FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOsem informação307177/2014-9Métodos de mapeamento para óxidos de ferro e argilas, aplicados em imagens Landsat-8/Operational Land Imager (OLI) e Earth Observing 1 (EO-1)/Hyperion e integrados com dados aerogeofísicos, foram testados nos depósitos de ferro de N4, N5 e N4WS, Serra Norte, Carajás, Brasil. Razões de banda foram aplicadas à imagem Landsat-8/OLI, identificando os principais minerais dos depósitos de ferro de N4 e N5. As imagens Landsat-8/OLI mostraram um bom desempenho para a exploração de óxido de ferro, mesmo em áreas vegetadas. Extração de feições espectrais e o método de classificação hiperespectral Spectral Angle Mapper foram aplicados na imagem EO-1/Hyperion com bons resultados para o mapeamento de minério de ferro de alto teor, bem como da proporção de hematita-goethita do minério e de argilas nos regolitos. A imagem EO-1/Hyperion provou ser uma excelente ferramenta para o mapeamento remoto de minerais em áreas de mina a céu aberto, bem como no mapeamento das pilhas de minério. Uma classificação não supervisionada foi aplicada a dados de 74 bandas do visível e infravermelho próximo do EO-1/Hyperion, índice Normalized Difference Vegetation Index derivado do Landsat-8/OLI, Modelo Digital do Terreno derivado do Laser Imaging Detection and Ranging, e dados aerogeofísicos (gamaespectrometria e componente Tzz do dado gravimétrico gradiométrico). Essa classificação de dados multifonte mostrou ser uma alternativa para mapeamento de óxidos de ferro em áreas vegetadas, bem como da geologia do regolito e das áreas mineralizada

    Mapping iron oxides with Landsat-8/OLI and EO-1/Hyperion imagery from the Serra Norte iron deposits in the Carajás Mineral Province, Brazil

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    Métodos de mapeamento para óxidos de ferro e argilas, aplicados em imagens Landsat-8/Operational Land Imager (OLI) e Earth Observing 1 (EO-1)/Hyperion e integrados com dados aerogeofísicos, foram testados nos depósitos de ferro de N4, N5 e N4WS, Serra Norte, Carajás, Brasil. Razões de banda foram aplicadas à imagem Landsat-8/OLI, identificando os principais minerais dos depósitos de ferro de N4 e N5. As imagens Landsat-8/OLI mostraram um bom desempenho para a exploração de óxido de ferro, mesmo em áreas vegetadas. Extração de feições espectrais e o método de classificação hiperespectral Spectral Angle Mapper foram aplicados na imagem EO-1/Hyperion com bons resultados para o mapeamento de minério de ferro de alto teor, bem como da proporção de hematita-goethita do minério e de argilas nos regolitos. A imagem EO-1/Hyperion provou ser uma excelente ferramenta para o mapeamento remoto de minerais em áreas de mina a céu aberto, bem como no mapeamento das pilhas de minério. Uma classificação não supervisionada foi aplicada a dados de 74 bandas do visível e infravermelho próximo do EO-1/Hyperion, índice Normalized Difference Vegetation Index derivado do Landsat-8/OLI, Modelo Digital do Terreno derivado do Laser Imaging Detection and Ranging, e dados aerogeofísicos (gamaespectrometria e componente Tzz do dado gravimétrico gradiométrico). Essa classificação de dados multifonte mostrou ser uma alternativa para mapeamento de óxidos de ferro em áreas vegetadas, bem como da geologia do regolito e das áreas mineralizadas.Mapping methods for iron oxides and clay minerals, using Landsat-8/Operational Land Imager (OLI) and Earth Observing 1 (EO-1)/Hyperion imagery integrated with airborne geophysical data, were applied in the N4, N5, and N4WS iron deposits, Serra Norte, Carajás, Brazil. Band ratios were achieved on Landsat-8/OLI imagery, allowing the recognition of the main minerals from iron deposits. The Landsat-8/OLI imagery showed a robust performance for iron oxide exploration, even in vegetated shrub areas. Feature extraction and Spectral Angle Mapper hyperspectral classification methods were carried out on EO-1/Hyperion imagery with good results for mapping high-grade iron ore, the hematite-goethite ratio, and clay minerals from regolith. The EO-1/Hyperion imagery proved an excellent tool for fast remote mineral mapping in open-pit areas, as well as mapping waste and tailing disposal facilities. An unsupervised classification was carried out on a data set consisting of EO-1/Hyperion visible near-infrared 74 bands, Landsat-8/OLI-derived Normalized Difference Vegetation Index, Laser Imaging Detection and Ranging-derived Digital Terrain Model, and high-resolution airborne geophysical data (gamma ray spectrometry, Tzz component of gradiometric gravimetry data). This multisource classification proved to be an adequate alternative for mapping iron oxides in vegetated shrub areas and to enhance the geology of the regolith and mineralized areas

    Gradient-based assessment of habitat quality for spectral ecosystem monitoring

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    The monitoring of ecosystems alterations has become a crucial task in order to develop valuable habitats for rare and threatened species. The information extracted from hyperspectral remote sensing data enables the generation of highly spatially resolved analyses of such species’ habitats. In our study we combine information from a species ordination with hyperspectral reflectance signatures to predict occurrence probabilities for Natura 2000 habitat types and their conservation status. We examine how accurate habitat types and habitat threat, expressed by pressure indicators, can be described in an ordination space using spatial correlation functions from the geostatistic approach. We modeled habitat quality assessment parameters using floristic gradients derived by non-metric multidimensional scaling on the basis of 58 field plots. In the resulting ordination space, the variance structure of habitat types and pressure indicators could be explained by 69% up to 95% with fitted variogram models with a correlation to terrestrial mapping of >0.8. Models could be used to predict habitat type probability, habitat transition, and pressure indicators continuously over the whole ordination space. Finally, partial least squares regression (PLSR) was used to relate spectral information from AISA DUAL imagery to floristic pattern and related habitat quality. In general, spectral transferability is supported by strong correlation to ordination axes scores (R2^{2} = 0.79–0.85), whereas second axis of dry heaths (R2^{2} = 0.13) and first axis for pioneer grasslands (R2^{2} = 0.49) are more difficult to describe

    Reduction of Uncorrelated Striping Noise—Applications for Hyperspectral Pushbroom Acquisitions

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    Hyperspectral images are of increasing importance in remote sensing applications. Imaging spectrometers provide semi-continuous spectra that can be used for physics based surface cover material identification and quantification. Preceding radiometric calibrations serve as a basis for the transformation of measured signals into physics based units such as radiance. Pushbroom sensors collect incident radiation by at least one detector array utilizing the photoelectric effect. Temporal variations of the detector characteristics that differ with foregoing radiometric calibration cause visually perceptible along-track stripes in the at-sensor radiance data that aggravate succeeding image-based analyses. Especially, variations of the thermally induced dark current dominate and have to be reduced. In this work, a new approach is presented that efficiently reduces dark current related stripe noise. It integrates an across-effect gradient minimization principle. The performance has been evaluated using artificially degraded whiskbroom (reference) and real pushbroom acquisitions from EO-1 Hyperion and AISA DUAL that are significantly covered by stripe noise. A set of quality indicators has been used for the accuracy assessment. They clearly show that the new approach outperforms a limited set of tested state-of-the-art approaches and achieves a very high accuracy related to ground-truth for selected tests. It may substitute recent algorithms in the Reduction of Miscalibration Effects (ROME) framework that is broadly used to reduce radiometric miscalibrations of pushbroom data takes

    Detecting soil erosion in semi-arid Mediterranean environments using simulated EnMAP data

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    Soil is an essential nature resource. Management of this resource is vital for sustainability and the continued functioning of earths atmospheric, hydrospheric and lithospheric functioning. The assessment and continued monitoring of surface soil state provides the information required to effectively manage this resource. This research used a simulated Environmental Mapping and Analysis Program (EnMAP) hyperspectral image cube of an agricultural region in semi- arid Mediterranean Spain to classify soil erosion states. Multiple Endmember Spectral Mixture Analysis (MESMA) was used to derive within pixel fractions of eroded and accumulated soils. A Classification of the soil erosion states using the scene fraction outputs and digital terrain information. The information products generated in this research provided an optimistic outlook for the applicability of the future EnMAP sensor for soil erosion investigations in semi-arid Mediterranean environments. Additionally, this research verifies that the launch of the EnMAP satellite sensor in 2018 will provide the opportunity to further improve the monitoring of earth finite soil resources.NSERC create AMETHYST , Alberta Terrestrial Imaging Centre

    Mediterranean Forest Species Mapping Using Hyperspectral Imagery

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    2011/2012Advances in hyperspectral technology provides scientists the opportunity to investigate problems that were difficult if not impossible to approach using multispectral data; among those, species composition which is a very important and dynamic forest parameter, linked with many environmental qualities that we want to map and monitor. This study addresses the problem of Mediterranean forest species mapping using satellite EO-1 Hyperion imagery (30m, 196 bands). Two pixel based techniques were evaluated, namely Spectral Angle Mapper (SAM) and Support Vector Machines (SVM), as well as an object oriented approach (GEOBIA). These techniques were applied in two study areas with different species composition and pattern complexity, namely Thasos and Taksiarchis. Extensive field work provided reference data for the accuracy assessment of the produced maps. Image preprocessing included several steps of data corrections and the Minimum Noise Fraction transformation, as means for data dimensionality reduction. In the case of Thasos, where two conifer species are present, SAM technique resulted in an overall accuracy (OA) of 3.9%, SVM technique yielded OA of 89.0% and GEOBIA achieved an OA of 85.3%. In the case of Taksiarchis, where more species are present – both conifers and broadleaved- the respective OA was 80.0%, 82.6% and 74.1%. All three methodologies implemented to investigate the value of hyperspectral imagery in Mediterranean forest species mapping, achieved very accurate results; in some cases equivalent to forest inventory maps. SAM was the straightest forward to implement, only depending on the training samples. Implementation SVM involved the specification of several parameters as well as the use of custom software and was more successful in the challenging landscape of Taksiarchis. GEOBIA adapted to scale through segmentation and extended the exercise of classification, allowing for knowledge based refinement. Lower accuracies could be attributed to the assessment method, as research on alternative assessment methods better adapted to the nature of object space is ongoing. Two typical Mediterranean forests were studied. In Thasos, two conifer species of the same genus, namely Pinus brutia and Pinus nigra, dominate a big part of the island. Both of them were accurately mapped by all methodologies. In Taksiarchis primarily stands of Quercus frainetto mix with stands of Fagus sylvatica and the aforementioned pines. The two pines were again mapped with high accuracy. However, there was a notable confusion between the two broadleaved species, indicating the need for further research, possibly taking advantage of species phenology. The outcome of the proposed methodologies could confidently meet the current needs for vegetation geographical data in regional to national scale, and demonstrate the value of hyperspectral imagery in Mediterranean forest species mapping.XXIII Ciclo198
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