Mapping urban surface materials using imaging spectroscopy data

Die Kartierung der städtische Oberflächenmaterialien ist aufgrund der komplexen räumlichen Muster eine Herausforderung. Daten von bildgebenden Spektrometern können hierbei durch die feine und kontinuierliche Abtastung des elektromagnetischen Spektrums detaillierte spektrale Merkmale von Oberflächenmaterialien erkennen, was mit multispektralen oder RGB-Bildern nicht mit der gleichen Genauigkeit erreicht werden kann. Bislang wurden in zahlreichen Studien zur Kartierung von städtischen Oberflächenmaterialien Daten von flugzeuggestützten abbildenden Spektrometern mit hoher räumlicher Auflösung verwendet, die ihr Potenzial unter Beweis stellen und gute Ergebnisse liefern. Im Vergleich zu diesen Sensoren haben weltraumgestützte abbildende Spektrometer eine regionale oder globale Abdeckung, eine hohe Wiederholbarkeit und vermeiden teure, zeit- und arbeitsaufwändige Flugkampagnen. Allerdings liegt die räumliche Auflösung der aktuellen weltraumgestützten abbildenden Spektroskopiedaten bei etwa 30 m, was zu einem Mischpixelproblem führt, welches mit herkömmlichen Kartierungsansätzen nur schwer zu bewältigen ist. Das Hauptziel dieser Studie ist die Kartierung städtischer Materialien mit bildgebenden Spektroskopiedaten in verschiedenen Maßstäben und die gleichzeitige Nutzung des Informationsgehalts dieser Daten, um die chemischen und physikalischen Eigenschaften von Oberflächenmaterialien zu erfassen sowie das Mischpixelproblem zu berücksichtigen. Konkret zielt diese Arbeit darauf ab, (1) photovoltaische Solarmodule mit Hilfe von luftgestützten bildgebenden Spektroskopiedaten auf der Grundlage ihrer spektralen Merkmale zu kartieren; (2) die Robustheit der Stichprobe von städtischen Materialgradienten zu untersuchen; (3) die Übertragbarkeit von städtischen Materialgradienten auf andere Gebiete zu analysieren.Mapping urban surface materials is challenging due to the complex spatial patterns. Data from imaging spectrometers can identify detailed spectral features of surface materials through the fine and continuous sampling of the electromagnetic spectrum, which cannot be achieved with the same accuracy using multispectral or RGB images. To date, numerous studies in urban surface material mapping have been using data from airborne imaging spectrometers with high spatial resolution, demonstrating the potential and providing good results. Compared to these sensors, spaceborne imaging spectrometers have regional or global coverage, high repeatability, and avoid expensive, time-consuming, and labor-intensive flight campaigns. However, the spatial resolution of current spaceborne imaging spectroscopy data (also known as hyperspectral data) is about 30 m, resulting in a mixed pixel problem that is challenging to handle with conventional mapping approaches. The main objective of this study is to perform urban surface material mapping with imaging spectroscopy data at different spatial scales, simultaneously explore the information content of these data to detect the chemical and physical properties of surface materials, and take the mixed-pixel problem into account. Specifically, this thesis aims to (1) map solar photovoltaic modules using airborne imaging spectroscopy data based on their spectral features; (2) investigate the sampling robustness of urban material gradients; (3) analyze the area transferability of urban material gradients

Sampling Robustness in Gradient Analysis of Urban Material Mixtures

Many studies analyzing spaceborne hyperspectral images (HSIs) have so far struggled to deal with a lack of pure pixels due to complex mixtures of urban surface materials. Recently, an alternative concept of gradients in urban surface material composition has been proposed and successfully applied to map cities with spaceborne HSIs without the requirement for a previous determination of pure pixels. The gradient concept treats all pixels as mixed and aims to describe and quantify gradual transitions in the cover fractions of surface materials. This concept presents a promising approach to tackle urban mapping using spaceborne HSIs. However, since gradients are determined in a data-driven way, their transferability within urban areas needs to be investigated. For this purpose, we analyze the robustness of urban surface material gradients and their dependence across six systematic and three simple random sampling schemes. The results show high similarity between nine sampling schemes in the primary gradient feature space (Pspace) and individual gradient feature spaces (Ispaces). Comparing the Pspace with the Ispaces, the Mantel statistics show the resemblance of samples' distribution in the Pspace, and each Ispace is rather strong with high credibility, as the significance level is P < 0.01. Therefore, it can be concluded that the material gradients defined in the test area are independent of the specific sampling scheme. This study paves the way for subsequent analysis of the stability of urban surface material gradients and the interpretation of material gradients in other urban environments

Mapping urban Surface Materials Using Imaging Spectroscopy Data

Urban environment and its processes directly affect human life. Detailed and up-to-date urban surface material maps are of great importance to modelers studying meteorology, climatology and ecology, as well as to authorities seeking to understand the urban growth dynamics and spatial evolution. However, mapping urban surface materials is challenging due to the complex spatial patterns. An established source of up-to-date information is remote sensing, as demonstrated by the widespread usage of SAR, LiDAR and optical data. Data from imaging spectrometers can identify detailed spectral features of surface materials through the fine and continuous sampling of the electromagnetic spectrum, which cannot be achieved with the same accuracy using multispectral or RGB images. To date, numerous studies in urban surface material mapping have been using data from airborne imaging spectrometers with high spatial resolution, demonstrating the potential and providing good results. Compared to these sensors, spaceborne imaging spectrometers have regional or global coverage, high repeatability, and avoid expensive, time-consuming, and labor-intensive flight campaigns. However, the spatial resolution of current spaceborne imaging spectroscopy data (also known as hyperspectral data) is about 30 m, resulting in a mixed pixel problem that is challenging to handle with conventional mapping approaches. The main objective of this study is to perform urban surface material mapping with imaging spectroscopy data at different spatial scales, simultaneously explore the information content of these data to detect the chemical and physical properties of surface materials, and take the mixed-pixel problem into account. Specifically, this thesis aims to (1) map solar photovoltaic modules using airborne imaging spectroscopy data based on their spectral features; (2) investigate the sampling robustness of urban material gradients; (3) analyze the area transferability of urban material gradients. To this end, we detected solar photovoltaics with an overall accuracy of about 80% to 90% by creating and combining spectral indices. This dissertation proved that the developed approach is suitable for accurate photovoltaic detection. We also demonstrated that the concept of urban surface material gradients is robust in sampling and transferable between similar urban areas. With these results, urban material gradients can be a generic technique for urban mapping with spaceborne imaging spectroscopy data. The methods developed invi the three parts of this dissertation improve the usefulness of imaging spectroscopy data for urban material detection from a classical method to the new concept of urban gradients, from airborne to spaceborne data, from pure pixel detection to solving the mixed pixel problem. By introducing and enhancing the gradient concept in urban mapping, the mixed pixel problem can be tackled, which is a promising approach for the analysis of imaging spectroscopy data from ongoing and upcoming spaceborne sensors. Overall, this thesis provides promising urban surface material mapping results by proposing a physical feature based approach as well as confirming and laying the foundation of the generic gradient concept in urban material studies. Further work can build on these results and could open a new field for the application of spaceborne imaging spectroscopy data

Mapping urban surface materials with imaging spectroscopy data on different spatial scales

This work focuses on the development of methods for mapping urban surface materials by means of imaging spectroscopy data with different spatial resolution. General findings from this work represent a sensor- and site-independent framework for the automated extraction of spectrally pure pixels using an urban image spectral library while coping with its potential incompleteness. The extraction of spectrally pure pixels serves as a basic prerequisite for the subsequent use of image analysis methods to obtain detailed urban surface material maps. These material maps enabled the determination of gradual material transitions that were finally related to complex spectral mixtures resulting from 30 m spatial resolution imaging spectroscopy data to analyse typical material compositions within certain administrative units. The findings demonstrate the great potential of using upcoming spaceborne imaging spectroscopy data for a regular area-wide mapping of surface materials in urban areas. Im Fokus dieser Arbeit stand die Entwicklung von Methoden zur Kartierung urbaner Oberflächenmaterialien mittels abbildender Spektroskopiedaten unterschiedlicher räumlicher Auflösung. Das vorgestellte Konzept zur automatisierten sensor- und ortsunabhängigen Extraktion spektral reiner Pixel aus flugzeuggetragenen Fernerkundungsdaten berücksichtigt dabei die mögliche Unvollständigkeit einer urbanen Bildspektralbibliothek. Die Extraktion spektral reiner Pixel dient als Grundvoraussetzung für den späteren Einsatz von Bildanalyseverfahren zur Gewinnung detaillierter Kartierungen urbaner Oberflächenmaterialien. Aus diesen sind Materialgradienten ableitbar, die mit den komplexen Spektralmischungen aus Hyperspektraldaten mit 30 m räumlicher Auflösung in Verbindung gebracht wurden. Die Analyse typischer Materialzusammensetzungen innerhalb städtischer Verwaltungseinheiten zeigt das enorme Potential zukünftiger Hyperspektralsatelliten für die Erfassung des Materialvorkommens von Städten

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Investigation of HIV anti-viral drug effect on HPV16 E6 expressing cervical carcinoma cells using advanced metabolomics methods

Metabolomics approaches have recently been used to understand the complex molecular interactions of biological systems. One popular area in which these methods are being developed is to understand the biochemical changes during abiotic and biotic stresses; for example, how a cell may respond to a drug. Since metabolites are the end products of gene expression, these can be used to indicate the result of the activities and interaction of the cell or organism with its environment. The investigation of the level and compositional changes of metabolites against metabolic stresses such as chemotherapeutic treatment (drug exposure) are required to understand more fully abiotic perturbation to biological systems. The aim of this project was to understand the metabolic effect that the anti-viral drugs indinavir and lopinavir (currently used by HIV patients) have on HPV-related cervical cancer cell lines by measuring changes in metabolism using a wide range of analytical techniques; including Fourier transform infrared (FT-IR) and Raman spectroscopies, and gas and liquid chromatography-mass spectrometry (GC and LC-MS). The analyses and interpretation of the large volumes of complex multidimensional data generated by metabolomics approaches were performed with a combination of multivariate data analysis techniques such as principal components analysis (PCA) and canonical variates analysis (CVA), as well as univariate approaches such as N-Way analysis of variance (ANOVA). By combining biochemical imaging, metabolite fingerprinting and footprinting, and metabolite profiling, with multi- and uni-variate analyses, the actions and effects of the anti-viral drugs were investigated. FT-IR spectroscopy was initially used to generate global biochemical finger- and foot-prints, and Raman spectroscopy was employed to investigate intracellular distribution of metabolites, and other cellular species, as well as the localisation of drug molecules within cells. FT-IR spectroscopy ascertained that the intra- and extra-cellular metabolomes were being directly influenced in a fashion that correlated with increasing anti-viral dosing; these effects were phenotypic rather than measurements of the drug level. Raman imaging spectroscopy indicated that the indinavir but not lopinavir was being compartmentalised within the cell nucleus, but only in HPV early protein 6 (E6) expressing cells. This observation was further confirmed by fractionation of cell samples into nuclear and cytoplasmic fractions and assessing the indinavir concentrations via LC-MS. Finally, LC-MS and GC-MS metabolite profiling were employed to investigate changes in the intracellular metabolome in response to the anti-viral compounds across a range of physiologically relevant concentrations and in the presence and absence of the E6 oncoprotein. General effects of both anti-viral compounds included the regulation of metabolites such as glutathione, octenedionoic and octadecenoic acids, which may be involved in stress related responses, reduced levels of sugars and sugar-phosphates indicating a potential arrest of glycolysis, and reduced levels of malic acid indicating potential decreased flux into the TCA cycle; all indicating that central metabolism was being reduced. Finally, LC-MS based quantification indicated that in the presence of E6, lopinavir was actively removed from the cell, whereas the indinavir intracellular concentration increased concomitantly with the level of dosing. These investigations have revealed that metabolomics approaches are an apt tool for the study of anti-viral effects within cell cultures, but improvements need to be made with respect to the major limitation of metabolite identification.EThOS - Electronic Theses Online ServiceORSSchool award from School of ChemistryGBUnited Kingdo

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