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The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ‘per-pixel paradigm’ and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm.

OMEGA/Mars Express hyperspectral imagery is an excellent source of data for exploring the surface composition of the planet Mars. Compared to terrestrial hyperspectral imagery, the data are challenging to work with; scene-specific transmission models are lacking, spectral features are shallow making them difficult to detect, and field data for validation is mostly not available. Software is available for calibrating the raw data to radiance-at sensor, but a processing methodology for processing the radiance data to surface reflectance is not straightforward. In this paper, we present a processing methodology for converting OMEGA data from radiance-at-sensor to surface reflectance. To overcome specific issues with OMEGA data, we developed novel methods for determining a per-scene transmittance spectrum, performing an atmospheric correction, and filtering systematic and random noise. The processing methodology produces surface reflectance images, from which single-pixel spectra can be extracted to identify surface features. Consistent with several previous studies, our results indicate the presence on the Martian surface of iron-rich clays.

OMEGA/Mars Express hyperspectral imagery is an excellent source of data for exploring the surface composition of the planet Mars. Compared to terrestrial hyperspectral imagery, the data are challenging to work with; scene-specific transmission models are lacking, spectral features are shallow making them difficult to detect, and field data for validation is mostly not available. Software is available for calibrating the raw data to radiance-at sensor, but a processing methodology for processing the radiance data to surface reflectance is not straightforward. In this paper, we present a processing methodology for converting OMEGA data from radiance-at-sensor to surface reflectance. To overcome specific issues with OMEGA data, we developed novel methods for determining a per-scene transmittance spectrum, performing an atmospheric correction, and filtering systematic and random noise. The processing methodology produces surface reflectance images, from which single-pixel spectra can be extracted to identify surface features. Consistent with several previous studies, our results indicate the presence on the Martian surface of iron-rich clays.

Natural gas leakage from underground pipelines is known to affect vegetation adversely, probably by displacement of the soil oxygen needed for respiration. This causes changes in plant and canopy reflectance, which may serve as indicators of gas leakage. In this study, a covariance analysis was performed between reflectance indices of maize (Zea mays) and wheat (Triticum aestivum) canopies and oxygen concentrations in a simulated natural gas leak. Twenty-nine days after oxygen shortage occurred, the reflectance indices had the highest correlation with oxygen concentrations in the soil, for both species. The effect was consistent within species but the absolute values varied between the species. Normalization by adding a constant value to the control index of one species resulted in significant linear regression models for several indices. The indices with the highest regression coefficients were used to predict the oxygen concentration in the soil. This showed that the gas leakage caused reflectance changes up to 0.5m from the source. As it could not be proven that oxygen shortage was the cause of the reflectance changes, further work is needed to study the side-effects of gas leakage, such as bacterial oxygen depletion, on plant growth and reflectance.

Anomalous concentrations of natural gas in the soil may be sourced from leaking underground gas pipelines or from natural microseepages. Due to the explosive nature of hydrocarbon gases, early detection of these gases is essential to avoid dangerous situations. It is known that natural gas in the soil affects vegetation health, which may be detected through analysis of reflectance spectra. This thesis characterizes the effects of underground gas leakage on plant and canopy development and reflectance. Based on the reflectance properties, a general gas leak detection method is proposed.It was assumed that natural gas displaces the soil air and that oxygen shortage is the cause of changes in vegetation growth and reflectance; however it was not known whether the hydrocarbon gases have an additional effect on the vegetation. Therefore two experiments were performed to compare the effects of small gas leaks (without oxygen shortage) with large leaks (with oxygen shortage) on plant growth and reflectance. The small gas leaks were simulated by delivering natural gas, methane and ethane to pots with maize (Zea mays) and wheat (Triticum aestivum) plants. The large natural gas leak was simulated by delivering 2200 1 of gas per day to 2 by 2 m maize and wheat canopy plots. Whereas in several studies a decrease in vegetation chlorophyll was one of the main indicators of large gas leaks, this study showed that leaf area is a better indicator of gas leakage. Moreover, it was shown that when the ethane concentration in the soil reaches 0.75%, plant growth is not only affected by oxygen shortage but also by the gas itself.The leaf reflectance of the plants was analysed using continuum removal of the blue (400-550 nm), red (550-750 nm) and two water absorption features (1370-1570 nm and 1870-2170 nm). The analysis showed that ethane caused an initial increase of 10% in reflectance between 560 and 590 nm, followed by a decrease during the course of the experiment. All gases caused a

This thesis presents statistical sampling scheme optimization for geo-environ-menta] purposes on the basis of hyperspectral data. It integrates derived products of the hyperspectral remote sensing data into individual sampling schemes. Five different issues are being dealt with.First, the optimized sampling scheme is presented to select samples that represent different ontological categories. The iterated conditional modes algorithm (ICM) is used as an unsupervised segmentation technique. Within each cate-gory, simulated annealing is applied for minimizing the mean shortest distance (MMSD) between sampling points. The number of sampling points in each category is proportional to the size and variability' of the category. The combination of the ICM algorithm for image segmentation with simulated annealing for optimized sampling, results in an elegant and powerful tool in designing optimal sampling schemes using remote sensing images. A validation study conducted shows that the optimized sampling scheme gives best estimates for commonly used vegetation indices compared to simple random sampling and rectangular grid sampling.Next, optimal sampling schemes, which focus on ground verification of minerals derived from hyperspectral data, are presented. Spectral angle mapper {SAM) and spectral feature fitting (SFF) classification techniques are applied to obtain rule mineral images. The rule images provide weights that are utilized in objective functions of the sampling schemes which are optimized by means of simulated annealing. Three weight, functions intensively sample areas where a high probability and abundance of al unite occurs. Weight function I uses binary weights derived from the SAM classification image, leading to an even distribution of sampling points over the region of interest. Weight function II uses scaled weights derived from the SAM rule image. Sample points are arranged more intensely in areas where there is an abundance of al unite. Weight function II

In Chapter 2, the results of detailed geologic mapping of sedimentary strata of the Subbeticum of Ronda are presented including a stratigraphic description of several sections near Ronda, El Burgo, Ardales, Teba, and Arriate in the Ronda-Málaga area. These are used to develop time-facies profiles on basis of which the paleogeography is reconstructed with emphasis on Miocene turning points. Timing of rift-related Mesozoic tectonic events, Early Miocene compressional tectonic events, and Late Miocene strike-slip tectonic events are derived from the result of a backstripping analysis using a synthetic composite stratigraphic section as input data. The final results are presented within the framework of Western Mediterranean plate tectonics yielding a number of deformation events characterizing the tectono-sedimentary evolution of the area.A review of recent work on field and microstructures within the Ronda peridotite body is given in Chapter 3. Paleostress analysis of fault-slip data from the peridotites are discussed. These lead to three stress tensors: an extensional, a compressional, and a strike-slip related tensor. Similar work conducted on Cretaceous and Tertiary carbonates of the Subbeticum give identical stress tensors. For the carbonates, tectonic stylolites and extension veins allow to relatively date these stress tensors. This dating together with the timing of tectonic phases from the backstripping analysis is used to derive an alternative model for the emplacement of the Ronda peridotites.Visible and near-infrared reflectance spectra of carbonate minerals, carbonate mineral mixtures, and un-weathered rock samples are discussed in Chapter 4. First, bidirectional reflectance theory is addressed forming the basis for a semi-empirical model to simulate reflectance of mineral mixtures from their single-component reflectance spectra. The following topics are discussed in the remainder of this Chapter: carbonate absorption band position, effects of particle size