Integrating geographical information in the Linked Digital Earth

Many progresses have been made since the Digital Earth notion was envisioned thirteen years ago. However, the mechanism for integrating geographic information into the Digital Earth is still quite limited. In this context, we have developed a process to generate, integrate and publish geospatial Linked Data from several Spanish National data-sets. These data-sets are related to four Infrastructure for Spatial Information in the European Community (INSPIRE) themes, specifically with Administrative units, Hydrography, Statistical units, and Meteorology. Our main goal is to combine different sources (heterogeneous, multidisciplinary, multitemporal, multiresolution, and multilingual) using Linked Data principles. This goal allows the overcoming of current problems of information integration and driving geographical information toward the next decade scenario, that is, ?Linked Digital Earth.?

Sea Bottom Classification by Means of Bathymetric LIDAR Data

Light Detection and Ranging (LIDAR) provides high horizontal and vertical resolution of spatial data located in point cloud images, and is increasingly being used in a number of applications and disciplines, which have concentrated on the exploit and manipulation of the data using mainly its three dimensional nature. Bathymetric LIDAR systems and data are mainly focused to map depths in shallow and clear waters with a high degree of accuracy. Additionally, the backscattering produced by the different materials distributed over the bottom surface causes that the returned intensity signal contains important information about the reflection properties of these materials. Processing conveniently these values using a Simplified Radiative Transfer Model, allows the identification of different sea bottom types. This paper presents an original method for the classification of sea bottom by means of information processing extracted from the images generated through LIDAR data. The results are validated using a vector database containing benthic information derived by marine surveys.

Onyx: A Linked Data approach to emotion representation

Extracting opinions and emotions from text is becoming increasingly important, especially since the advent of micro-blogging and social networking. Opinion mining is particularly popular and now gathers many public services, datasets and lexical resources. Unfortunately, there are few available lexical and semantic resources for emotion recognition that could foster the development of new emotion aware services and applications. The diversity of theories of emotion and the absence of a common vocabulary are two of the main barriers to the development of such resources. This situation motivated the creation of Onyx, a semantic vocabulary of emotions with a focus on lexical resources and emotion analysis services. It follows a linguistic Linked Data approach, it is aligned with the Provenance Ontology, and it has been integrated with the Lexicon Model for Ontologies (lemon), a popular RDF model for representing lexical entries. This approach also means a new and interesting way to work with different theories of emotion. As part of this work, Onyx has been aligned with EmotionML and WordNet-Affect.

Contribute to the Study of Vertical Distribution of Conventional No-Till Seeders and Spatial Variability of Seed Depth Placement of Maize in Alentejo, Portugal

Entre os vários fatores que contribuem para a produção de uma cultura de milho, a distribuição vertical dos semeadores avaliada através da localização da semente em profundidade é um fator-chave, especialmente na técnica de sementeira direta. Simultaneamente, dada a complexidade dos ecossistemas naturais e agrícolas em sistemas de agricultura de conservação, a gestão diferenciada e localizada das parcelas assume um importante papel na análise e gestão da variabilidade das propriedades do solo e estabelecimento das culturas, nomeadamente utilizando informação geo referenciada e tecnologia expedita. Assim, o principal objetivo desta Tese foi a avaliação em culturas de milho da variabilidade espacial da localização de semente em profundidade e estabelecimento da cultura em sementeira direta usando sistemas convencionais de controlo de profundidade, tendo-se comparado com diferentes sistemas de mobilização e recorrendo a tecnologias de agricultura de precisão. Os ensaios decorreram na região Mediterrânea do Alentejo, em propriedades agrícolas no decorrer das campanhas de 2010, 2011, 2012 e 2015 em 6 diferentes campos experimentais. O trabalho experimental consistiu em ensaios com avaliações in loco do solo e cultura, consumo de combustível das operações e deteção remota. Os resultados obtidos indicam que não só o sistema de mobilização afetou a localização da semente em profundidade, como em sementeira direta a profundidade de sementeira foi afetada pelo teor de humidade do solo, resistência do solo à profundidade e velocidade da operação de sementeira. Adicionalmente observaram-se condições heterogéneas de emergência e estabelecimento da cultura afetadas por condições físicas de compactação do solo. Comparando os diferentes sistemas de mobilização, obteve-se uma significativa redução de combustível para a técnica de sementeira direta, apesar de se terem observado diferenças estatísticas significativas considerando diferentes calibrações de profundidade de sementeira Do trabalho realizado nesta Tese ressalva-se a importância que as tecnologias de agricultura de precisão podem ter no acompanhamento e avaliação de culturas em sementeira direta, bem como a necessidade de melhores procedimentos no controlo de profundidade dos semeadores pelo respetivos operadores ou ao invés, a adoção de semeadores com mecanismos ativos de controlo de profundidade. ABSTRACT Among the various factors that contribute towards producing a successful maize crop, seeders vertical distribution evaluated through seed depth placement is a key determinant, especially under a no-tillage technique. At the same time in conservation agriculture systems due to the complexity of natural and agricultural ecosystems site specific management became an important approach to understand and manage the variability of soil properties and crop establishment, especially when using geo spatial information and affording readily technology Thus, the main objective of this Thesis was to evaluate the spatial variability of seed depth placement and crop establishment in maize crops under no-tillage conditions compared to different tillage systems, using conventional seed depth control no till seeders and precision farming technologies. Trials were carried out in the Mediterranean region of Alentejo, in private farms along the sowing operations season over the years 2010, 2011, 2012 and 2015 in 6 different experimental fields. Experimental work covered field tests with in loco soil and crop evaluations, fuel operation evaluations and aerial sensing. The results obtained indicate that not only tillage system affected seed depth placement but under no till conditions seed depth was affected by soil moisture content, soil resistance to penetration and seeders forward speed. In addition uneven crop seedling and establishment depended on seed depth placement and could be affected by physical problems of compaction layers. Significant reduction in fuel consumption was observed for no till operations although significant differences observed according to different setting calibrations of seed depth control. According to the results, precision agriculture is an important tool to evaluate crops under no till conditions and seed depth mechanisms should be more accurate by the operators or is determinant the adoption of new active depth control technology to improve seeders performance.

Visual constraints in foraging bumblebees: Flower size and color affect search time and flight behavior

In optimal foraging theory, search time is a key variable defining the value of a prey type. But the sensory-perceptual processes that constrain the search for food have rarely been considered. Here we evaluate the flight behavior of bumblebees (Bombus terrestris) searching for artificial flowers of various sizes and colors. When flowers were large, search times correlated well with the color contrast of the targets with their green foliage-type background, as predicted by a model of color opponent coding using inputs from the bees' UV, blue, and green receptors. Targets that made poor color contrast with their backdrop, such as white, UV-reflecting ones, or red flowers, took longest to detect, even though brightness contrast with the background was pronounced. When searching for small targets, bees changed their strategy in several ways. They flew significantly slower and closer to the ground, so increasing the minimum detectable area subtended by an object on the ground. In addition, they used a different neuronal channel for flower detection. Instead of color contrast, they used only the green receptor signal for detection. We relate these findings to temporal and spatial limitations of different neuronal channels involved in stimulus detection and recognition. Thus, foraging speed may not be limited only by factors such as prey density, flight energetics, and scramble competition. Our results show that understanding the behavioral ecology of foraging can substantially gain from knowledge about mechanisms of visual information processing.

Contexto e modularização em redes neurais recorrentes para aprendizagem de seqüências temporais

Este trabalho apresenta um sistema neural modular, que processa separadamente informações de contexto espacial e temporal, para a tarefa de reprodução de sequências temporais. Para o desenvolvimento do sistema neural foram considerados redes neurais recorrentes, modelos estocásticos, sistemas neurais modulares e processamento de informações de contexto. Em seguida, foram estudados três modelos com abordagens distintas para aprendizagem de seqüências temporais: uma rede neural parcialmente recorrente, um exemplo de sistema neural modular e um modelo estocástico utilizando a teoria de modelos markovianos escondidos. Com base nos estudos e modelos apresentados, esta pesquisa propõe um sistema formado por dois módulos sucessivos distintos. Uma rede de propagação direta (módulo estimador de contexto espacial) realiza o processamento de contexto espacial identificando a seqüência a ser reproduzida e fornecendo um protótipo do contexto para o segundo módulo. Este é formado por uma rede parcialmente recorrente (módulo de reprodução de sequências temporais) para aprender as informações de contexto temporal e reproduzir em suas saídas a seqüência identificada pelo módulo anterior. Para a finalidade mencionada, este mestrado utiliza a distribuição de Gibbs na saída do módulo para contexto espacial de forma que este forneça probabilidades de contexto espacial, indicando o grau de certeza do módulo e possibilitando a utilização de procedimentos especiais para os casos de dúvida. O sistema neural foi testado em conjuntos contendo trajetórias abertas, fechadas, e com diferentes situações de ambigüidade e complexidade. Duas situações distintas foram avaliadas: (a) capacidade do sistema em reproduzir trajetórias a partir de pontos iniciais treinados; e (b) capacidade de generalização do sistema reproduzindo trajetórias considerando pontos iniciais ou finais em situações não treinadas. A situação (b) é um problema de difícil ) solução em redes neurais devido à falta de contexto temporal, essencial na reprodução de seqüências. Foram realizados experimentos comparando o desempenho do sistema modular proposto com o de uma rede parcialmente recorrente operando sozinha e um sistema modular neural (TOTEM). Os resultados sugerem que o sistema proposto apresentou uma capacidade de generalização significamente melhor, sem que houvesse uma deterioração na capacidade de reproduzir seqüências treinadas. Esses resultados foram obtidos em sistema mais simples que o TOTEM.

TextMess 2.0: las tecnologías del lenguaje humano ante los nuevos retos de la comunicación digital

El objetivo general de este proyecto se centra en el estudio, desarrollo y experimentación de diferentes técnicas y sistemas basados en Tecnologías del Lenguaje Humano (TLH) para el desarrollo de la próxima generación de sistemas de procesamiento inteligente de la información digital (modelado, recuperación, tratamiento, comprensión y descubrimiento) afrontando los actuales retos de la comunicación digital. En este nuevo escenario, los sistemas deben incorporar capacidades de razonamiento que descubrirán la subjetividad de la información en todos sus contextos (espacial, temporal y emocional) analizando las diferentes dimensiones de uso (multilingualidad, multimodalidad y registro).

Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language

This paper addresses the problem of the automatic recognition and classification of temporal expressions and events in human language. Efficacy in these tasks is crucial if the broader task of temporal information processing is to be successfully performed. We analyze whether the application of semantic knowledge to these tasks improves the performance of current approaches. We therefore present and evaluate a data-driven approach as part of a system: TIPSem. Our approach uses lexical semantics and semantic roles as additional information to extend classical approaches which are principally based on morphosyntax. The results obtained for English show that semantic knowledge aids in temporal expression and event recognition, achieving an error reduction of 59% and 21%, while in classification the contribution is limited. From the analysis of the results it may be concluded that the application of semantic knowledge leads to more general models and aids in the recognition of temporal entities that are ambiguous at shallower language analysis levels. We also discovered that lexical semantics and semantic roles have complementary advantages, and that it is useful to combine them. Finally, we carried out the same analysis for Spanish. The results obtained show comparable advantages. This supports the hypothesis that applying the proposed semantic knowledge may be useful for different languages.

Advances in camera trap data management tools: Towards collaborative development and integration with GIS

Camera traps have become a widely used technique for conducting biological inventories, generating a large number of database records of great interest. The main aim of this paper is to describe a new free and open source software (FOSS), developed to facilitate the management of camera-trapped data which originated from a protected Mediterranean area (SE Spain). In the last decade, some other useful alternatives have been proposed, but ours focuses especially on a collaborative undertaking and on the importance of spatial information underpinning common camera trap studies. This FOSS application, namely, “Camera Trap Manager” (CTM), has been designed to expedite the processing of pictures on the .NET platform. CTM has a very intuitive user interface, automatic extraction of some image metadata (date, time, moon phase, location, temperature, atmospheric pressure, among others), analytical (Geographical Information Systems, statistics, charts, among others), and reporting capabilities (ESRI Shapefiles, Microsoft Excel Spreadsheets, PDF reports, among others). Using this application, we have achieved a very simple management, fast analysis, and a significant reduction of costs. While we were able to classify an average of 55 pictures per hour manually, CTM has made it possible to process over 1000 photographs per hour, consequently retrieving a greater amount of data.

Concepts for a low-cost motorist information system. Final report.

Federal Highway Administration, Washington, D.C.

Spacelab Data Processing Facility.

Cover title.

Considerations in the selection of security measures for automatic data processing systems /

"Contributed to the Federal Information Processing Standards Task Group 15 - Computer Systems Security" -t.p.

Digital surface model, hillshade and orthophoto of the world's largest fossil oyster reef, links to GeoTIFFs

The world's largest fossil oyster reef, formed by the giant oyster Crassostrea gryphoides and located in Stetten (north of Vienna, Austria) is studied by Harzhauser et al., 2015, 2016; Djuricic et al., 2016. Digital documentation of the unique geological site is provided by terrestrial laser scanning (TLS) at the millimeter scale. Obtaining meaningful results is not merely a matter of data acquisition with a suitable device; it requires proper planning, data management, and postprocessing. Terrestrial laser scanning technology has a high potential for providing precise 3D mapping that serves as the basis for automatic object detection in different scenarios; however, it faces challenges in the presence of large amounts of data and the irregular geometry of an oyster reef. We provide a detailed description of the techniques and strategy used for data collection and processing in Djuricic et al., 2016. The use of laser scanning provided the ability to measure surface points of 46,840 (estimated) shells. They are up to 60-cm-long oyster specimens, and their surfaces are modeled with a high accuracy of 1 mm. In addition to laser scanning measurements, more than 300 photographs were captured, and an orthophoto mosaic was generated with a ground sampling distance (GSD) of 0.5 mm. This high-resolution 3D information and the photographic texture serve as the basis for ongoing and future geological and paleontological analyses. Moreover, they provide unprecedented documentation for conservation issues at a unique natural heritage site.

Approaches and Strategy for Cancer Research and Surveillance Data: Integration, Information Pipeline, Data Models, and Informatics Opportunities

Thesis (Ph.D.)--University of Washington, 2016-04

Simulation modelling applied to runoff modelling using mapscript

Dynamic spatial analysis addresses computational aspects of space–time processing. This paper describes the development of a spatial analysis tool and modelling framework that together offer a solution for simulating landscape processes. A better approach to integrating landscape spatial analysis with Geographical Information Systems is advocated in this paper. Enhancements include special spatial operators and map algebra language constructs to handle dispersal and advective flows over landscape surfaces. These functional components to landscape modelling are developed in a modular way and are linked together in a modelling framework that performs dynamic simulation. The concepts and modelling framework are demonstrated using a hydrological modelling example. The approach provides a modelling environment for scientists and land resource managers to write and to visualize spatial process models with ease.