Robust Modular Feature-Based Terrain-Aided Visual Navigation and Mapping

The visual feature-based Terrain-Aided Navigation (TAN) system presented in this thesis addresses the problem of constraining inertial drift introduced into the location estimate of Unmanned Aerial Vehicles (UAVs) in GPS-denied environment. The presented TAN system utilises salient visual features representing semantic or human-interpretable objects (roads, forest and water boundaries) from onboard aerial imagery and associates them to a database of reference features created a-priori, through application of the same feature detection algorithms to satellite imagery. Correlation of the detected features with the reference features via a series of the robust data association steps allows a localisation solution to be achieved with a finite absolute bound precision defined by the certainty of the reference dataset. The feature-based Visual Navigation System (VNS) presented in this thesis was originally developed for a navigation application using simulated multi-year satellite image datasets. The extension of the system application into the mapping domain, in turn, has been based on the real (not simulated) flight data and imagery. In the mapping study the full potential of the system, being a versatile tool for enhancing the accuracy of the information derived from the aerial imagery has been demonstrated. Not only have the visual features, such as road networks, shorelines and water bodies, been used to obtain a position ’fix’, they have also been used in reverse for accurate mapping of vehicles detected on the roads into an inertial space with improved precision. Combined correction of the geo-coding errors and improved aircraft localisation formed a robust solution to the defense mapping application. A system of the proposed design will provide a complete independent navigation solution to an autonomous UAV and additionally give it object tracking capability

A Global Human Settlement Layer from optical high resolution imagery - Concept and first results

A general framework for processing of high and very-high resolution imagery for creating a Global Human Settlement Layer (GHSL) is presented together with a discussion on the results of the first operational test of the production workflow. The test involved the mapping of 24.3 millions of square kilometres of the Earth surface spread over four continents, corresponding to an estimated population of 1.3 billion of people in 2010. The resolution of the input image data ranges from 0.5 to 10 meters, collected by a heterogeneous set of platforms including satellite SPOT (2 and 5), CBERS-2B, RapidEye (2 and 4), WorldView (1 and 2), GeoEye-1, QuickBird-2, Ikonos-2, and airborne sensors. Several imaging modes were tested including panchromatic, multispectral and pan-sharpened images. A new fully automatic image information extraction, generalization and mosaic workflow is presented that is based on multiscale textural and morphological image features extraction. New image feature compression and optimization are introduced, together with new learning and classification techniques allowing for the processing of HR/VHR image data using low-resolution thematic layers as reference. A new systematic approach for quality control and validation allowing global spatial and thematic consistency checking is proposed and applied. The quality of the results are discussed by sensor, by band, by resolution, and eco-regions. Critical points, lessons learned and next steps are highlighted.JRC.G.2-Global security and crisis managemen

Automatic Positional Accuracy Assessment of Imagery Segmentation Processes: A Case Study

There are many studies related to Imagery Segmentation (IS) in the field of Geographic Information (GI). However, none of them address the assessment of IS results from a positional perspective. In a field in which the positional aspect is critical, it seems reasonable to think that the quality associated with this aspect must be controlled. This paper presents an automatic positional accuracy assessment (PAA) method for assessing this quality component of the regions obtained by means of the application of a textural segmentation algorithm to a Very High Resolution (VHR) aerial image. This method is based on the comparison between the ideal segmentation and the computed segmentation by counting their differences. Therefore, it has the same conceptual principles as the automatic procedures used in the evaluation of the GI's positional accuracy. As in any PAA method, there are two key aspects related to the sample that were addressed: (i) its size-specifically, its influence on the uncertainty of the estimated accuracy values-and (ii) its categorization. Although the results obtained must be taken with caution, they made it clear that automatic PAA procedures, which are mainly applied to carry out the positional quality assessment of cartography, are valid for assessing the positional accuracy reached using other types of processes. Such is the case of the IS process presented in this study

A methodology to produce geographical information for land planning using very-high resolution images

Actualmente, os municípios são obrigados a produzir, no âmbito da elaboração dos instrumentos de gestão territorial, cartografia homologada pela autoridade nacional. O Plano Director Municipal (PDM) tem um período de vigência de 10 anos. Porém, no que diz respeito à cartografia para estes planos, principalmente em municípios onde a pressão urbanística é elevada, esta periodicidade não é compatível com a dinâmica de alteração de uso do solo. Emerge assim, a necessidade de um processo de produção mais eficaz, que permita a obtenção de uma nova cartografia de base e temática mais frequentemente. Em Portugal recorre-se à fotografia aérea como informação de base para a produção de cartografia de grande escala. Por um lado, embora este suporte de informação resulte em mapas bastante rigorosos e detalhados, a sua produção têm custos muito elevados e consomem muito tempo. As imagens de satélite de muito alta-resolução espacial podem constituir uma alternativa, mas sem substituir as fotografias aéreas na produção de cartografia temática, a grande escala. O tema da tese trata assim da satisfação das necessidades municipais em informação geográfica actualizada. Para melhor conhecer o valor e utilidade desta informação, realizou-se um inquérito aos municípios Portugueses. Este passo foi essencial para avaliar a pertinência e a utilidade da introdução de imagens de satélite de muito alta-resolução espacial na cadeia de procedimentos de actualização de alguns temas, quer na cartografia de base quer na cartografia temática. A abordagem proposta para solução do problema identificado baseia-se no uso de imagens de satélite e outros dados digitais em ambiente de Sistemas de Informação Geográfica. A experimentação teve como objectivo a extracção automática de elementos de interesse municipal a partir de imagens de muito alta-resolução espacial (fotografias aéreas ortorectificadas, imagem QuickBird, e imagem IKONOS), bem como de dados altimétricos (dados LiDAR). Avaliaram-se as potencialidades da informação geográfica extraídas das imagens para fins cartográficos e analíticos. Desenvolveram-se quatro casos de estudo que reflectem diferentes usos para os dados geográficos a nível municipal, e que traduzem aplicações com exigências diferentes. No primeiro caso de estudo, propõe-se uma metodologia para actualização periódica de cartografia a grande escala, que faz uso de fotografias aéreas vi ortorectificadas na área da Alta de Lisboa. Esta é uma aplicação quantitativa onde as qualidades posicionais e geométricas dos elementos extraídos são mais exigentes. No segundo caso de estudo, criou-se um sistema de alarme para áreas potencialmente alteradas, com recurso a uma imagem QuickBird e dados LiDAR, no Bairro da Madre de Deus, com objectivo de auxiliar a actualização de cartografia de grande escala. No terceiro caso de estudo avaliou-se o potencial solar de topos de edifícios nas Avenidas Novas, com recurso a dados LiDAR. No quarto caso de estudo, propõe-se uma série de indicadores municipais de monitorização territorial, obtidos pelo processamento de uma imagem IKONOS que cobre toda a área do concelho de Lisboa. Esta é uma aplicação com fins analíticos onde a qualidade temática da extracção é mais relevante.Currently, the Portuguese municipalities are required to produce homologated cartography, under the Territorial Management Instruments framework. The Municipal Master Plan (PDM) has to be revised every 10 years, as well as the topographic and thematic maps that describe the municipal territory. However, this period is inadequate for representing counties where urban pressure is high, and where the changes in the land use are very dynamic. Consequently, emerges the need for a more efficient mapping process, allowing obtaining recent geographic information more often. Several countries, including Portugal, continue to use aerial photography for large-scale mapping. Although this data enables highly accurate maps, its acquisition and visual interpretation are very costly and time consuming. Very-High Resolution (VHR) satellite imagery can be an alternative data source, without replacing the aerial images, for producing large-scale thematic cartography. The focus of the thesis is the demand for updated geographic information in the land planning process. To better understand the value and usefulness of this information, a survey of all Portuguese municipalities was carried out. This step was essential for assessing the relevance and usefulness of the introduction of VHR satellite imagery in the chain of procedures for updating land information. The proposed methodology is based on the use of VHR satellite imagery, and other digital data, in a Geographic Information Systems (GIS) environment. Different algorithms for feature extraction that take into account the variation in texture, color and shape of objects in the image, were tested. The trials aimed for automatic extraction of features of municipal interest, based on aerial and satellite high-resolution (orthophotos, QuickBird and IKONOS imagery) as well as elevation data (altimetric information and LiDAR data). To evaluate the potential of geographic information extracted from VHR images, two areas of application were identified: mapping and analytical purposes. Four case studies that reflect different uses of geographic data at the municipal level, with different accuracy requirements, were considered. The first case study presents a methodology for periodic updating of large-scale maps based on orthophotos, in the area of Alta de Lisboa. This is a situation where the positional and geometric accuracy of the extracted information are more demanding, since technical mapping standards must be complied. In the second case study, an alarm system that indicates the location of potential changes in building areas, using a QuickBird image and LiDAR data, was developed for the area of Bairro da Madre de Deus. The goal of the system is to assist the updating of large scale mapping, providing a layer that can be used by the municipal technicians as the basis for manual editing. In the third case study, the analysis of the most suitable roof-tops for installing solar systems, using LiDAR data, was performed in the area of Avenidas Novas. A set of urban environment indicators obtained from VHR imagery is presented. The concept is demonstrated for the entire city of Lisbon, through IKONOS imagery processing. In this analytical application, the positional quality issue of extraction is less relevant.GEOSAT – Methodologies to extract large scale GEOgraphical information from very high resolution SATellite images (PTDC/GEO/64826/2006), e-GEO – Centro de Estudos de Geografia e Planeamento Regional, da Faculdade de Ciências Sociais e Humanas, no quadro do Grupo de Investigação Modelação Geográfica, Cidades e Ordenamento do Territóri

Information Extraction and Modeling from Remote Sensing Images: Application to the Enhancement of Digital Elevation Models

To deal with high complexity data such as remote sensing images presenting metric resolution over large areas, an innovative, fast and robust image processing system is presented. The modeling of increasing level of information is used to extract, represent and link image features to semantic content. The potential of the proposed techniques is demonstrated with an application to enhance and regularize digital elevation models based on information collected from RS images

Remote Sensing for International Stability and Security - Integrating GMOSS Achievements in GMES

The Joint Research Centre of the European Commission hosted a two-day workshop "Remote sensing for international stability and security: integrating GMOSS achievements in GMES". Its aim was to disseminate the scientific and technical achievements of the Global Monitoring for Security and Stability (GMOSS) network of excellence to partners of ongoing and future GMES projects such as RESPOND, LIMES, RISK-EOS,PREVIEW, BOSS4GMES, SAFER, G-MOSAIC. The objectives of this workshop were: ¿ To bring together scientific and technical people from the GMOSS NoE and from thematically related GMES projects. ¿ To discuss and compare alternative technical solutions (e.g. final experimental understanding from GMOSS, operational procedures applied in projects such as RESPOND, pre-operational application procedures foreseen from LIMES, etc.) ¿ To draft a list of technical and scientific challenges relevant in the next future. ¿ To open GMOSS to a wider forum in the JRC This report contains abstracts of the fifteen contributions presented by European researchers. The different presentations addressed pre-processing, feature recognition, change detection and applications which represents also the structure of the report. The second part includes poster abstracts presented during a separate poster session.JRC.G.2-Global security and crisis managemen

Creating 3D city models from satellite imagery for integrated assessment and forecasting of solar energy

Buildings are the most prominent component in the urban environment. The geometric identification of urban buildings plays an important role in a range of urban applications, including 3D representations of buildings, energy consumption analysis, sustainable development, urban planning, risk assessment, and change detection. In particular, 3D building models can provide a comprehensive assessment of surfaces exposed to solar radiation. However, the identification of the available surfaces on urban structures and the actual locations which receive a sufficient amount of sunlight to increase installed power capacity (e.g. Photovoltaic systems) are crucial considerations for solar energy supply efficiency. Although considerable research has been devoted to detecting the rooftops of buildings, less attention has been paid to creating and completing 3D models of urban buildings. Therefore, there is a need to increase our understanding of the solar energy potential of the surfaces of building envelopes so we can formulate future adaptive energy policies for improving the sustainability of cities. The goal of this thesis was to develop a new approach to automatically model existing buildings for the exploitation of solar energy potential within an urban environment. By investigating building footprints and heights based on shadow information derived from satellite images, 3D city models were generated. Footprints were detected using a two level segmentation process: (1) the iterative graph cuts approach for determining building regions and (2) the active contour method and the adjusted-geometry parameters method for modifying the edges and shapes of the extracted building footprints. Building heights were estimated based on the simulation of artificial shadow regions using identified building footprints and solar information in the image metadata at pre-defined height increments. The difference between the actual and simulated shadow regions at every height increment was computed using the Jaccard similarity coefficient. The 3D models at the first level of detail were then obtained by extruding the building footprints based on their heights by creating image voxels and using the marching cube approach. In conclusion, 3D models of buildings can be generated solely from 2D data of the buildings’attributes in any selected urban area. The approach outperforms the past attempts, and mean error is reduced by at least 21%. Qualitative evaluations of the study illustrate that it is possible to achieve 3D building models based on satellite images with a mean error of less than 5 m. This comprehensive study allows for 3D city models to be generated in the absence of elevation attributes and additional data. Experiments revealed that this novel, automated method can be useful in a number of spatial analyses and urban sustainability applications

Integration of GIS and DSS: a methodology to evaluate low carbon strategies in a smart urban metabolism context

An Urban Metabolism system can be examined by evaluating the incoming and outgoing energy flows of a city. Academics and researchers have utilized Urban Metabolism framework to analyze different urban areas and have begun to extend the framework beyond the city-region unit of analysis to inform related aspects of the Urban Metabolism: in this context UM framework is a tool that can be useful in the decision making process. This study aims to be an opportunity and an example of environmental analysis of UM, from the point of view of CO2eq emissions and absorptions. A multi-objective Decision Support System is developed with the aim of minimizing the environmental, social and economic impacts of the CO2eq emissions at the municipal level. The Decision Support System has been implemented and a few scenario analyses were developed: enhancement of energy efficiency of residential and industrial buildings, increase of green areas, production of electricity by means of photovoltaic installation on site, efficiency of the vehicle fleet and finally, proper recycling of waste. The municipality of Tavagnacco recognizes this approach as a new perspective of analysis for a future comparison project with other municipalities. From this comparison it is expected to get results that can accredit the most convenient method from the environmental, social and economic point of view, and can offer the basis for the improvement of energy efficiency. Results of this work can provide evidence in support of an increased awareness in issues related to the CO2eq reduction.Il metabolismo di un sistema urbano pu`o essere esaminato cercando di sviluppare e comprendere i flussi energetici in ingresso e in uscita dalla citt`a. Accademici e ricercatori hanno utilizzato questo approccio al fine di valutare diverse aree urbane e hanno recentemente esteso il quadro di indagine al di l`a dell\u2019unit`a di citt`a-regione al fine di utilizzare questo strumento nell\u2019ambito del processo decisionale di pianificazione del territorio. Questo percorso vuole definire una possibile metodologia e un esempio di approccio spaziale ad un\u2019analisi di bilancio comunale di CO2eq. E\u2019 stato sviluppato un Sistema di Supporto alle Decisioni multiobiettivo, con il fine di minimizzare l\u2019impatto ambientale oltre a quello sociale e quello economico delle emissioni di CO2eq su scala comunale. Il Sistema di Supporto alle Decisioni ha previsto l\u2019implementazione di alcuni scenari di analisi quali l\u2019incentivazione dell\u2019efficientamento energetico degli edi- fici residenziali ma anche industriali, l\u2019aumento delle aree a verde, la produzione di energia elettrica in loco mediante impianto fotovoltaico, l\u2019efficientamento del parco veicolare e infine una valida raccolta differenziata. Il comune di Tavagnacco conosce le sfide future in merito ai problemi ambientali e si impegna in un progetto pilota di valutazione delle emissioni di CO2eq. In un prossimo futuro si delinea un lavoro di confronto tra comuni che utilizzano metodi di abbattimento delle emissioni. Da questo confronto ci si aspetta di ottenere risultati che possano accreditare il metodo pi`u conveniente dal punto di vista ambientale, economico e sociale, e quindi offrire delle basi per una valutazione sull\u2019opportunit`a di miglioramento ed efficientamento energetico a livello comunale e sovracomunale. Si auspica che i risultati di questo lavoro possano offrire elementi convincenti a supporto di un atteggiamento sempre pi`u attento alle problematiche legate alla riduzione delle emissioni di CO2eq

Advanced Techniques based on Mathematical Morphology for the Analysis of Remote Sensing Images

Remote sensing optical images of very high geometrical resolution can provide a precise and detailed representation of the surveyed scene. Thus, the spatial information contained in these images is fundamental for any application requiring the analysis of the image. However, modeling the spatial information is not a trivial task. We addressed this problem by using operators defined in the mathematical morphology framework in order to extract spatial features from the image. In this thesis novel techniques based on mathematical morphology are presented and investigated for the analysis of remote sensing optical images addressing different applications. Attribute Profiles (APs) are proposed as a novel generalization based on attribute filters of the Morphological Profile operator. Attribute filters are connected operators which can process an image by removing flat zones according to a given criterion. They are flexible operators since they can transform an image according to many different attributes (e.g., geometrical, textural and spectral). Furthermore, Extended Attribute Profiles (EAPs), a generalization of APs, are presented for the analysis of hyperspectral images. The EAPs are employed for including spatial features in the thematic classification of hyperspectral images. Two techniques dealing with EAPs and dimensionality reduction transformations are proposed and applied in image classification. In greater detail, one of the techniques is based on Independent Component Analysis and the other one deals with feature extraction techniques. Moreover, a technique based on APs for extracting features for the detection of buildings in a scene is investigated. Approaches that process an image by considering both bright and dark components of a scene are investigated. In particular, the effect of applying attribute filters in an alternating sequential setting is investigated. Furthermore, the concept of Self-Dual Attribute Profile (SDAP) is introduced. SDAPs are APs built on an inclusion tree instead of a min- and max-tree, providing an operator that performs a multilevel filtering of both the bright and dark components of an image. Techniques developed for applications different from image classification are also considered. In greater detail, a general approach for image simplification based on attribute filters is proposed. Finally, two change detection techniques are developed. The experimental analysis performed with the novel techniques developed in this thesis demonstrates an improvement in terms of accuracies in different fields of application when compared to other state of the art methods