6 research outputs found

    GeoAI-enhanced Techniques to Support Geographical Knowledge Discovery from Big Geospatial Data

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    abstract: Big data that contain geo-referenced attributes have significantly reformed the way that I process and analyze geospatial data. Compared with the expected benefits received in the data-rich environment, more data have not always contributed to more accurate analysis. “Big but valueless” has becoming a critical concern to the community of GIScience and data-driven geography. As a highly-utilized function of GeoAI technique, deep learning models designed for processing geospatial data integrate powerful computing hardware and deep neural networks into various dimensions of geography to effectively discover the representation of data. However, limitations of these deep learning models have also been reported when People may have to spend much time on preparing training data for implementing a deep learning model. The objective of this dissertation research is to promote state-of-the-art deep learning models in discovering the representation, value and hidden knowledge of GIS and remote sensing data, through three research approaches. The first methodological framework aims to unify varied shadow into limited number of patterns, with the convolutional neural network (CNNs)-powered shape classification, multifarious shadow shapes with a limited number of representative shadow patterns for efficient shadow-based building height estimation. The second research focus integrates semantic analysis into a framework of various state-of-the-art CNNs to support human-level understanding of map content. The final research approach of this dissertation focuses on normalizing geospatial domain knowledge to promote the transferability of a CNN’s model to land-use/land-cover classification. This research reports a method designed to discover detailed land-use/land-cover types that might be challenging for a state-of-the-art CNN’s model that previously performed well on land-cover classification only.Dissertation/ThesisDoctoral Dissertation Geography 201

    Carta nautica eletronica : uma implementação

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    Orientador: Neucimar Jeronimo LeiteDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Este trabalho visa descrever os problemas encontrados e soluções apresentadas durante o desenvolvimento de protótipo de uma carta náutica eletrônica, bem como os procedimentos de processamento de imagens usados como apoio. A primeira parte é composta de uma breve descrição da história e da teoria cartográfica utilizada. São apresentados os métodos aplicados na resolução dos problemas, tanto de navegação como planejamento, e como estes aspectos se mesclam para auxiliar na especificação da interface operacional da carta náutica eletrônica. A segunda parte tem sua maior ênfase na apresentação do modelo de dados e das operações básicas implementadas no protótipo da carta náutica eletrônica. A modelagem é feita tendo como base um banco de dados relacional que armazena tanto os dados geográficos como os operacionais. A abordagem da terceira parte visa descrever um sistema de processamento digital de imagens cujo objetivo é o aproveitamento de cartas náuticas impressas como fontes de dados para o sistema eletrônico. A ênfase é dada ao processamento das imagens de cartas náuticas digitalizadas e à obtenção das coordenadas geográficas dos elementos .. de interesse que estejam nelas representados. Um exemplo de como os procedimentos e operações descritos interagem é dado na quarta parte juntamente com as conclusões e comentários finaisAbstract: In this work we describe some problems concerned with the development of an electronic nautical chart prototype and the related digital image processing procedures. The first part presents a brief description of the cartography history and theory. The methods applied to solve navigational and planning problems are also presented together with the electronic nautical chart operational interface. The second part describes the data model and the basic system's operations. The model is given according to a relational database which stores the geographic and the operational data. The escription of a digital image processing system, defined to use the regular printed nautical charts as a data source for the electronic system, is presented in the third part. The emphasis is on the processing of scanned nautical charts to obtain the geographical coordinates of the different components. An example considering the different procedures and operations is given in the fourth part, followed by some conclusions and final commentsMestradoMestre em Ciência da Computaçã

    An Evolutionary Approach to Adaptive Image Analysis for Retrieving and Long-term Monitoring Historical Land Use from Spatiotemporally Heterogeneous Map Sources

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    Land use changes have become a major contributor to the anthropogenic global change. The ongoing dispersion and concentration of the human species, being at their orders unprecedented, have indisputably altered Earth’s surface and atmosphere. The effects are so salient and irreversible that a new geological epoch, following the interglacial Holocene, has been announced: the Anthropocene. While its onset is by some scholars dated back to the Neolithic revolution, it is commonly referred to the late 18th century. The rapid development since the industrial revolution and its implications gave rise to an increasing awareness of the extensive anthropogenic land change and led to an urgent need for sustainable strategies for land use and land management. By preserving of landscape and settlement patterns at discrete points in time, archival geospatial data sources such as remote sensing imagery and historical geotopographic maps, in particular, could give evidence of the dynamic land use change during this crucial period. In this context, this thesis set out to explore the potentials of retrospective geoinformation for monitoring, communicating, modeling and eventually understanding the complex and gradually evolving processes of land cover and land use change. Currently, large amounts of geospatial data sources such as archival maps are being worldwide made online accessible by libraries and national mapping agencies. Despite their abundance and relevance, the usage of historical land use and land cover information in research is still often hindered by the laborious visual interpretation, limiting the temporal and spatial coverage of studies. Thus, the core of the thesis is dedicated to the computational acquisition of geoinformation from archival map sources by means of digital image analysis. Based on a comprehensive review of literature as well as the data and proposed algorithms, two major challenges for long-term retrospective information acquisition and change detection were identified: first, the diversity of geographical entity representations over space and time, and second, the uncertainty inherent to both the data source itself and its utilization for land change detection. To address the former challenge, image segmentation is considered a global non-linear optimization problem. The segmentation methods and parameters are adjusted using a metaheuristic, evolutionary approach. For preserving adaptability in high level image analysis, a hybrid model- and data-driven strategy, combining a knowledge-based and a neural net classifier, is recommended. To address the second challenge, a probabilistic object- and field-based change detection approach for modeling the positional, thematic, and temporal uncertainty adherent to both data and processing, is developed. Experimental results indicate the suitability of the methodology in support of land change monitoring. In conclusion, potentials of application and directions for further research are given

    Automatic Archeological Feature Extraction from Satellite VHR Images

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    Abstract Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term ‘‘morphology’’ stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were applied to different archaeological sites in Turkmenistan (Nisa) and in Iraq (Babylon); a further change detection analysis was applied to the Babylon site using two HR images as a pre–post second gulf war. We had different results or outputs, taking into consideration the fact that the operative scale of sensed data determines the final result of the elaboration and the output of the information quality, because each of them was sensitive to specific shapes in each input image, we had mapped linear and nonlinear objects, updating archaeological cartography, automatic change detection analysis for the Babylon site. The discussion of these techniques has the objective to provide the archaeological team with new instruments for the orientation and the planning of a remote sensing application. & 2009 Elsevier Ltd. All rights reserved

    Analysis of Engineering Drawings: State of the Art and Challenges

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    Contribution à un ouvrage.In this paper, we analyze the state of the art in interpretation of engineering drawings, both from a methodological point of view and from the perspective of the applications. We try to emphasize where techniques are mature, where they need further maturing, and where we still have open challenges. Special attention is given to the progress in the last two years
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