Change detection using SAR data

The objective of this thesis is to find changes caused by natural disaster from two co-registered calibrated TerraSAR-X images. Three methods are used in this thesis. The first method, histogram thresholding, uses the histogram of the SAR intensity ratio image to classify the ratio image into three classes. This technique was originally proposed by Kittler et al. (1986) and modified by Bazi et al. (2005) and Moser et al. (2006) based on the Bayesian formula. In this thesis their methods are combined together to detect three classes. The relative difference of the cost function is used to detect the number of the classes instead of the determinant of the Hessian matrix suggested by Bazi et al. (2005). The second method formulates the classification problem as a hypothesis testing problem. This idea was originally used by Touzi et al. (1988) and Oliver et al. (1996). In this thesis the analytical method by Touzi et al. (1988) is replaced by using the properties of the Gamma distribution. The third method, graph-cut algorithm, is a post-processing method, which improves classification results from the first and second methods. The provement is equivalent to the global optimization of an energy function in a Markov random field (MRF). A modern method proposed by Kolmogorov et al. (2004) and Boykov et al. (2004) is used in this thesis. This method transforms the energy function of a MRF into an equivalent graph and solves the global optimization problem using a max-flow/min-cut algorithm. These three methods are applied to the test data on Queensland, Australia, and Leipzig, Germany. Most SAR ratio images can be classified into three classes successfully. The remaining problem is that the interpretation of the changed classes is still ambiguous. Other data sources should be combined to assist or improve the interpretation of the detected change.Das Ziel der Diplomarbeit ist die von Naturkatastrophen verursachten Änderungen an der Erdoberfläche mittels zwei ko-registrierten kalibrierten TerraSAR-X Intensitätsbildern zu identifizieren. Drei Methoden werden in der Diplomarbeit verwendet. Die erste Methode, Histogram Schwellwertverfahren, vewendet das Histogram vom SAR-Ratiobild um das Ratiobild in drei Klassen zu segmentieren. Diese Technik wurde zuerst von Kittler et al. (1986) veröffentlicht und von Bazi et al. (2005) und Moser et al. (2006) ans Sicht der Bayes’schen Formel weiterentwickelt. Ihre Methoden werden in der Diplomarbeit kombiniert. Der relative Unterschied der Kostenfunktion wird zur Detektion von Klassenanzahl verwerdet anstatt Determinant der Hessematrix, die von Bazi et al. (2005) verwendet wurde. Die zweite Methode beschreibt die Klassifikation als einen statistischen Test. Diese Idee wurde zuerst von Touzi et al. (1988) und Oliver et al. (1996) verwendet. In der Diplomarbeit wird die analytische Methode von Touzi et al. (1988) durch Anwendung der Eigenschaften von Gamma-Verteilungsfunktion ausgewechselt. Die dritte Methode, Graph-cut, ist ein Post-processing Verfahren, das die Klassifikationsmasken der ersten und zweiten Methoden verbessert. Die Verbesserung ist äquivalent zur globalen Optimierung einer Energiefunktion in einem Markov random field (MRF). Eine moderne Methode von Kolmogorov et al. (2004) und Boykov et al. (2004) wird verwendet um die Optimierung durchzuführen. Diese Methode wandelt die Energiefunktion in einen äquivalenten Graph um und löst das Problem der globalen Optimierung mittels ein Max-flow/Min-cut Verfahren auf. Diese drei Methoden werden auf die Testdaten von Queensland, Australien, und Leipzig, Deutschland, angewendet. Die meisten SAR Bilder von Testdaten können erfolgreich in drei Klassen klassifiziert werden. Das übrige Problem ist die nicht eindeutige Interpretation von Änderungen. Zusätzliche Daten sollten kombiniert werden um die Interpretation zu unterstützen oder verbessern

Literature analysis of SWOT mission from geodetic perspective

Satellite radar altimeter has been used for nearly twenty years to observe the variety of the global ocean surface topography. It has advanced our understanding of global ocean circulation and sea level change. However the conventional radar altimeter can not resolve the submesoscale features in the oceans because of its large spacing between satellite ground tracks and coarse ground resolution. On the other hand altimetry technique is expected to be able to observe large rivers, lakes and monitor the storage of freshwater on land. These new challenges require a new technique and a new mission. In 2016 a satellite mission called Surface Water and Ocean Topography (SWOT) will be launched by NASA and CNES according to plan. This term paper will summarize the general measurement principle, orbit design issues and applications of SWOT in the literature.Die Satelliten-Radar-Altimetrie wird seit fast zwanzig Jahren zur Beobachtung der Änderung der globalen Ozeanoberflächentopografie verwendet. Sie hat unser Verständnis von globaler Ozeanzirkulation und Meeresspiegeländerung verbessert. Die konventionale Radar-Altimetrie kann jedoch die Merkmale von Ozeanen wegen ihrer großen Distanz zwischen Bodenspuren und grober Bodenauflösung nicht im Submesoskalenbereich auflösen. Auf der anderen Seite wird erwartet, dass die Altimetrie die Beobachtung großer Flüsse und Seen sowie die Überwachung der Süßwasserspeicherung an Land ermöglicht. Diese Herausforderung verlangt eine neue Mission mit neuer Technik. Im Jahre 2016 soll nach den Plänen von NASA und CNES eine neue Satellitenmission namens Surface Water and Ocean Topography (SWOT) gestartet werden. Diese Studienarbeit fasst das in der Literatur beschriebene grundlegende Messprinzip, das Bahndesign und einigen Anwendungen von SWOT zusammen

An Instrument for In Situ Measuring the Volume Scattering Function of Water: Design, Calibration and Primary Experiments

The optical volume scattering function (VSF) of seawater is a fundamental property used in the calculation of radiative transfer for applications in the study of the upper-ocean heat balance, the photosynthetic productivity of the ocean, and the chemical transformation of photoreactive compounds. A new instrument to simultaneously measure the VSF in seven directions between 20° to 160°, the attenuation coefficient, and the depth of water is presented. The instrument is self-contained and can be automatically controlled by the depth under water. The self-contained data can be easily downloaded by an ultra-short-wave communication system. A calibration test was performed in the laboratory based on precise estimation of the scattering volume and optical radiometric calibration of the detectors. The measurement error of the VSF measurement instrument has been estimated in the laboratory based on the Mie theory, and the average error is less than 12%. The instrument was used to measure and analyze the variation characteristics of the VSF with angle, depth and water quality in Daya Bay for the first time. From these in situ data, we have found that the phase functions proposed by Fournier-Forand, measured by Petzold in San Diego Harbor and Sokolov in Black Sea do not fit with our measurements in Daya. These discrepancies could manly due to high proportion of suspended calcium carbonate mineral-like particles with high refractive index in Daya Bay

Current-oscillator correlation and Fano factor spectrum of quantum shuttle with finite bias voltage and temperature

A general master equation is derived to describe an electromechanical single-dot transistor in the Coulomb blockade regime. In the equation, Fermi distribution functions in the two leads are taken into account, which allows one to study the system as a function of bias voltage and temperature of the leads. Furthermore, we treat the coherent interaction mechanism between electron tunneling events and the dynamics of excited vibrational modes. Stationary solutions of the equation are numerically calculated. We show current through the oscillating island at low temperature appears step like characteristics as a function of the bias voltage and the steps depend on mean phonon number of the oscillator. At higher temperatures the current steps would disappear and this event is accompanied by the emergence of thermal noise of the charge transfer. When the system is mainly in the ground state, zero frequency Fano factor of current manifests sub-Poissonian noise and when the system is partially driven into its excited states it exhibits super-Poissonian noise. The difference in the current noise would almost be removed for the situation in which the dissipation rate of the oscillator is much larger than the bare tunneling rates of electrons.Comment: 14 pages, 8 figure

Carbon dots-based dual-emission ratiometric fluorescence sensor for dopamine detection

The detection of Dopamine (DA) is significant for disease surveillance and prevention. However, the development of the precise and simple detection techniques is still at a preliminary stage due to their high tester requirements, time-consuming process, and low accuracy. In this work, we present a novel dual-emission ratiometric fluorescence sensing system based on a hybrid of carbon dots (CDs) and 7-amino-4-methylcoumarin (AMC) to quickly monitor the DA concentration. Linked via amide bonds, the CDs and AMC offered dual-emissions with peaks located at 455 and 505 nm, respectively, under a single excitation wavelength of 300 nm. Attributed to the fluorescence of the CDs and AMC in the nanohybrid system can be quenched by DA, the concentration of DA could be quantitatively detected by monitoring the ratiometric ratio change in fluorescent intensity. More importantly, the CDs-AMC-based dual-emission ratiometric fluorescence sensing system demonstrated a remarkable linear relationship in the range of 0–33.6 μM to detection of DA, and a low detection limit of 5.67 nM. Additionally, this sensor successfully applied to the detection of DA in real samples. Therefore, the ratiometric fluorescence sensing system may become promising to find potential applications in biomedical dopamine detection

SAR-based change detection using hypothesis testing and Markov random field modelling

The objective of this study is to automatically detect changed areas caused by natural disasters from bi-temporal co-registered and calibrated TerraSAR-X data. The technique in this paper consists of two steps: Firstly, an automatic coarse detection step is applied based on a statistical hypothesis test for initializing the classification. The original analytical formula as proposed in the constant false alarm rate (CFAR) edge detector is reviewed and rewritten in a compact form of the incomplete beta function, which is a builtin routine in commercial scientific software such as MATLAB and IDL. Secondly, a post-classification step is introduced to optimize the noisy classification result in the previous step. Generally, an optimization problem can be formulated as a Markov random field (MRF) on which the quality of a classification is measured by an energy function. The optimal classification based on the MRF is related to the lowest energy value. Previous studies provide methods for the optimization problem using MRFs, such as the iterated conditional modes (ICM) algorithm. Recently, a novel algorithm was presented based on graph-cut theory. This method transforms a MRF to an equivalent graph and solves the optimization problem by a max-flow/min-cut algorithm on the graph. In this study this graph-cut algorithm is applied iteratively to improve the coarse classification. At each iteration the parameters of the energy function for the current classification are set by the logarithmic probability density function (PDF). The relevant parameters are estimated by the method of logarithmic cumulants (MoLC). Experiments are performed using two flood events in Germany and Australia in 2011 and a forest fire on La Palma in 2009 using pre- and post-event TerraSAR-X data. The results show convincing coarse classifications and considerable improvement by the graph-cut post-classification step

Change Detection using TerraSAR-X data

The objectives of this thesis is to find changed areas caused by natural disaster from two coregistered calibrated SAR images. Three methods are used in this thesis. The first method histogram thresholding uses the histogram of the SAR intensity ratio image to classify the ratio image into three classes. This technique was originally proposed by Kittler et al. (1986) and modified by Bazi et al. (2005) and Moser et al. (2006) based on the Bayesian formula. In this thesis their methods are combined together to detect three classes. The relative difference of the cost function is used to detect the number of the classes instead of the determinant of the Hessian matrix suggested by Bazi et al. (2005). The second method formulates the classification problem as a hypothesis testing problem. This idea was originally used by Touzi et al. (1988) and Oliver et al. (1996). In this thesis the analytical method by Touzi et al. (1988) is replaced by using the properties of the Gamma distribution. The third method graph-cut algorithm is a post-processing method, which improves classification results from the first and second methods. The improvement is equivalent to the global optimization of an energy function in a MRF. A modern method proposed by Kolmogorov et al. (2004) and Boykov et al. (2004) is used in this thesis. This method transforms the energy function of a MRF into an equivalent graph and solve the global optimization problem using a max-flow/min-cut algorithm. These three methods are applied to the test data on Queensland, Australia and Leipzig, Germany. The most SAR ratio images can be classified into three classes successfully. The remaining problem is that the interpretation of the changed classes is still ambiguous. Other data sources should be combined to assist or improve the interpretation of the detected change

Automatic SAR-based flood detection using hierarchical tile-ranking thresholding and fuzzy logic

Given the proven effectiveness of the split-based approach (SBA) for SAR image analysis in literature, the objective of this article focuses on designing a more efficient and robust version of the SBA for applications in the context of rapid flood mapping. A hierarchical tile-ranking SBA is proposed in this paper which is combined with a previous multilevel tile contrast analysis to significantly reduce the amount of data for the estimation of global threshold. A separability test is further applied to reject badly located tiles. The classification is optimized by merging pixel backscatter values, cluster size and local slope into a fuzzy-logic based post-classification framework. The proposed method was tested on Sentinel-1 SAR data acquired over Lake Liambezi in the Caprivi Strip of Namibia and validated with respect to a Landsat-8 scene. Compared to tiles selected by the conventional SBA the proposed method automatically select better relevant ones and the classification is more robust with less misclassification of water-lookalikes

Using airborne remote sensing to increase situational awareness in civil protection and humanitarian relief - the importance of user involvement

Enhancing situational awareness in real-time (RT) civil protection and emergency response scenarios requires the development of comprehensive monitoring concepts combining classical remote sensing disciplines with geospatial information science. In the VABENE++ project of the German Aerospace Center (DLR) monitoring tools are being developed by which innovative data acquisition approaches are combined with information extraction as well as the generation and dissemination of information products to a specific user. DLR’s 3K and 4k camera system which allow for a RT acquisition and pre-processing of high resolution aerial imagery are applied in two application examples conducted with end users: a civil protection exercise with humanitarian relief organisations and a large open-air music festival in cooperation with a festival organising company. This study discusses how airborne remote sensing can significantly contribute to both, situational assessment and awareness, focussing on the downstream processes required for extracting information from imagery and for visualising and disseminating imagery in combination with other geospatial information. Valuable user feedback and impetus for further developments has been obtained from both applications, referring to innovations in thematic image analysis (supporting festival site management) and product dissemination (editable web services). Thus, this study emphasises the important role of user involvement in application-related research, i.e. by aligning it closer to user’s requirements