Automatic extraction of faults and fractal analysis from remote sensing data

Object-based classification is a promising technique for image classification. Unlike pixel-based methods, which only use the measured radiometric values, the object-based techniques can also use shape and context information of scene textures. These extra degrees of freedom provided by the objects allow the automatic identification of geological structures. In this article, we present an evaluation of object-based classification in the context of extraction of geological faults. Digital elevation models and radar data of an area near Lake Magadi (Kenya) have been processed. We then determine the statistics of the fault populations. The fractal dimensions of fault dimensions are similar to fractal dimensions directly measured on remote sensing images of the study area using power spectra (PSD) and variograms. These methods allow unbiased statistics of faults and help us to understand the evolution of the fault systems in extensional domains. Furthermore, the direct analysis of image texture is a good indicator of the fault statistics and allows us to classify the intensity and type of deformation. We propose that extensional fault networks can be modeled by iterative function system (IFS)

GIS based Integration and Analysis of multiple source Information for Non-Proliferation Studies

In recent years the volume and variety of information that needs to be analysed in the context of non-proliferation have been increasing continuously Therefore, an integrated, all-source information analysis is paramount for an efficient and effective monitoring of the Non-Proliferation Treaty (NPT). The ¿Treaty Monitoring¿ workpackage of the LIMES research project addressed this issue by developing an integrated platform supporting the non-proliferation image analyst in verifying treaty compliance. The main benefits of the platform are (i) integrating information from multiple sources and time-frames, including satellite imagery, site models, open source information, reports, etc; (ii) improved information management using a GIS-based platform and (iii) enhanced methodologies for satellite image analysis. The platform components facilitate the analysis by highlighting changes and anomalies, which are potentially safeguards-relevant and by providing quantitative measurements which are not readily available from the images. It improves the efficiency and effectiveness of the information assessment by providing all-source integration capabilities, which allow to easily access supporting collateral information (e.g. Open Source information) from an image analysis task, an vice versa. The paper presents the components of the integration platform and the results of the demonstration which monitored the construction of a nuclear reactor in Olkiluoto, Finland.JRC.E.9-Nuclear security (Ispra

Avaliação de critérios de heterogeneidade baseados em atributos morfológicos para segmentação de imagens por crescimento de regiões

Avalia-se neste trabalho o impacto de se considerar atributos morfológicos na formulação do critério que governa o crescimento de regiões na segmentação de imagens. Para tanto, uma extensão do algoritmo de segmentação multiresolução proposto por Baatz e Schäpe (2000) foi proposta e implementada, permitindo que se testassem critérios derivados de diferentes atributos morfológicos. O estudo valeu-se de um método supervisionado para medir numericamente a qualidade da segmentação. O resultado ideal da segmentação foi representado por um conjunto de segmentos de referência delineados manualmente para três recortes de imagens Quickbird-2. Para cada critério testado, os valores ótimos para os parâmetros do algoritmo de segmentação foram determinados por um processo estocástico que procurou minimizar a discrepância entre as referências e o resultado de cada segmentação. Uma análise tanto quantitativa quanto qualitativa dos resultados indicou inequivocamente que a inclusão de atributos morfológicos no critério de heterogeneidade, que decide a fusão entre segmentos adjacentes no processo de crescimento de regiões, pode resultar numa substancial melhoria da qualidade da segmentação. O artigo realça ainda a importância de se adotar atributos morfológicos apropriados para cada classe de objetos e tece considerações que orientam a escolha destes atributos

Improving Change Detection Results of IR-MAD by Eliminating Strong Changes

This letter examines the effect of the prior elimination of strong changes on the results of change detection in bitemporal multispectral images using the previously published iteratively reweighted multivariate alteration detection (IR-MAD) method. An initial change mask is calculated by identifying strong changes between two images. By using the mask and hence eliminating the strong changes from the analysis, the IR-MAD method is able to identify a better no-change background. This effect is demonstrated on a multitemporal Landsat Enhanced Thematic Mapper Plus data set from an agricultural region in Germany with substantial improvement in the results even for the scenes which have a large number of changes