Geotecnologias e recursos de multimídia no ensino de cartografia: percepção sócio ambiental do rio Alcântara no município de São Gonçalo/RJ

A disponibilidade gratuita na Internet de imagens de satélite e SIG somada à facilidade dos alunos no manuseio de multimídia através dos seus smartphones criam possibilidades para trabalhar com geotecnologias e recursos de multimídia no ensino de Cartografia. Nesta pesquisa foram avaliadas as contribuições, os limites e as possibilidades da inserção da tecnologia espacial, geoprocessamento e recursos de multimídia nas aulas de Geografia do sétimo ano da rede pública municipal de São Gonçalo/RJ; foi desenvolvida uma metodologia em meio digital, por meio da Internet, denominada Mapeando Meu Rio (MMR) cuja temática abordada foi a Percepção Socioambiental do Rio Alcântara. Observaram-se o interesse e o envolvimento dos alunos no decorrer das atividades propostas, por meio do uso de recursos de multimídia e geotecnologias como materiais de apoio à Educação Ambiental. Os resultados da avaliação do MMR mostraram que os alunos chegaram ao final do sétimo ano com dificuldades em relação à alfabetização cartográfica; isso foi constatado tanto na produção dos mapas mentais como também pela utilização do GPS, Google Earth e do ArcGIS Online. Os alunos tiveram dificuldades em utilizar os conhecimentos básicos da Cartografia para elaborar uma representação espacial, mais especificamente, legenda, coordenadas geográficas e orientação espacial. A alfabetização cartográfica não deve ser considerada como conteúdo que se restringe ao 6 ano, mas uma linguagem de comunicação para o entendimento da dinâmica espacial no decorrer do Ensino Fundamental e do Ensino Médio. As atividades geográficas deve permitir ao aluno melhorar a compreensão do espaço geográfico de uma maneira mais significativa para construir abstrações a partir da própria realidade, ou seja, do espaço vivido.

Sensoriamento remoto hidroacústico no mapeamento de macrófitas aquáticas submersas

Macrófitas são importantes produtoras primárias do ecossistema aquático, e o desequilíbrio do ambiente pode ocasionar seu crescimento acelerado. Portanto, levantamentos de dados relacionados a macrófitas submersas são importantes para contribuir na gestão de corpos de água. Contudo, a amostragem dessa vegetação requer um enorme esforço físico. Nesse sentido, a técnica hidroacústica é apropriada para o estudo de macrófitas submersas. Assim, os objetivos deste trabalho foram avaliar os tipos de dados gerados pelo ecobatímetro e analisar como esses dados caracterizam a vegetação. Utilizou-se o ecobatímetro BioSonics DT-X acoplado a um GPS. A área de estudo é um trecho do Rio Uberaba, MG. A amostragem foi feita por meio de transectos, navegando de uma margem à outra. Depois de processar os dados, obteve-se informação a respeito de ocorrência de macrófitas submersas, profundidade, altura média das plantas, porcentagem da cobertura vegetal e posição. A partir desse conjunto de dados, foi possível extrair outras duas métricas: biovolume e altura efetiva do dossel. Os dados foram importados de um Sistema de Informação Geográfica e geraram-se mapas ilustrativos das variáveis estudadas. Além disso, quatro perfis foram selecionados para analisar a diferença entre as grandezas de representação de macrófitas. O ecobatímetro mostrou-se uma ferramenta eficaz no mapeamento de macrófitas submersas. Cada uma das medidas - altura do dossel, ECH ou biovolume - caracteriza de forma diferente a vegetação submersa. Dessa forma, a escolha do tipo de representação depende da aplicação desejada.

Determinação de cenários futuros de uso e cobertura do solo e sua influência na vulnerabilidade ambiental : o caso do município de Formosa – GO

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, Programa de Pós-Graduação em Tecnologia Ambiental e Recursos Hídricos, 2015.

Efficient Processing of Spatial Group Keyword Queries

With the proliferation of geo-positioning and geo-tagging techniques, spatio-textual objects that possess both a geographical location and a textual description are gaining in prevalence, and spatial keyword queries that exploit both location and textual description are gaining in prominence. However, the queries studied so far generally focus on finding individual objects that each satisfy a query rather than finding groups of objects where the objects in a group together satisfy a query.

We define the problem of retrieving a group of spatio-textual objects such that the group's keywords cover the query's keywords and such that the objects are nearest to the query location and have the smallest inter-object distances. Specifically, we study three instantiations of this problem, all of which are NP-hard. We devise exact solutions as well as approximate solutions with provable approximation bounds to the problems. In addition, we solve the problems of retrieving top-k groups of three instantiations, and study a weighted version of the problem that incorporates object weights. We present empirical studies that offer insight into the efficiency of the solutions, as well as the accuracy of the approximate solutions.

SOPS: A System for Efficient Processing of Spatial-Keyword Publish/Subscribe

Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. These geo-textual data cover a wide range of topics. Users are interested in receiving up-to-date geo-textual objects (e.g., geo-tagged Tweets) such that their locations meet users’ need and their texts are interesting to users. For example, a user may want to be updated with tweets near her home on the topic “dengue fever headache.” In this demonstration, we present SOPS, the Spatial-Keyword Publish/Subscribe System, that is capable of efficiently processing spatial keyword continuous queries. SOPS supports two types of queries: (1) Boolean Range Continuous (BRC) query that can be used to subscribe the geo-textual objects satisfying a boolean keyword expression and falling in a specified spatial region; (2) Temporal Spatial-Keyword Top-k Continuous (TaSK) query that continuously maintains up-to-date top-k most relevant results over a stream of geo-textual objects. SOPS enables users to formulate their queries and view the real-time results over a stream of geotextual objects by browser-based user interfaces. On the server side, we propose solutions to efficiently processing a large number of BRC queries (tens of millions) and TaSK queries over a stream of geo-textual objects.

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Image processing technique to count the number of logs in a timber truck

This paper summarises the results of using image processing technique to get information about the load of timber trucks before their arrival using digital images or geo tagged images. Once the images are captured and sent to sawmill by drivers from forest, we can predict their arrival time using geo tagged coordinates, count the number of (timber) logs piled up in a truck, identify their type and calculate their diameter. With this information we can schedule and prioritise the inflow and unloading of trucks in the light of production schedules and raw material stocks available at the sawmill yard. It is important to keep all the actors in a supply chain integrated coordinated, so that optimal working routines can be reached in the sawmill yard.   

Aerial video geo-registration using terrain models from dense and coherent stereo matching

In the context of aerial imagery, one of the first steps toward a coherent processing of the information contained in multiple images is geo-registration, which consists in assigning geographic 3D coordinates to the pixels of the image. This enables accurate alignment and geo-positioning of multiple images, detection of moving objects and fusion of data acquired from multiple sensors. To solve this problem there are different approaches that require, in addition to a precise characterization of the camera sensor, high resolution referenced images or terrain elevation models, which are usually not publicly available or out of date. Building upon the idea of developing technology that does not need a reference terrain elevation model, we propose a geo-registration technique that applies variational methods to obtain a dense and coherent surface elevation model that is used to replace the reference model. The surface elevation model is built by interpolation of scattered 3D points, which are obtained in a two-step process following a classical stereo pipeline: first, coherent disparity maps between image pairs of a video sequence are estimated and then image point correspondences are back-projected. The proposed variational method enforces continuity of the disparity map not only along epipolar lines (as done by previous geo-registration techniques) but also across them, in the full 2D image domain. In the experiments, aerial images from synthetic video sequences have been used to validate the proposed technique.

Question answering and multi-search engines in geo-temporal information retrieval

In this paper we present a complete system for the treatment of both geographical and temporal dimensions in text and its application to information retrieval. This system has been evaluated in both the GeoTime task of the 8th and 9th NTCIR workshop in the years 2010 and 2011 respectively, making it possible to compare the system to contemporary approaches to the topic. In order to participate in this task we have added the temporal dimension to our GIR system. The system proposed here has a modular architecture in order to add or modify features. In the development of this system, we have followed a QA-based approach as well as multi-search engines to improve the system performance.

Standardized geo-referenced catch, fishing effort and length-frequency data for the Indian Ocean Bigeye Tuna, Thunnus obesus (1952-2014)

Geo-referenced catch and fishing effort data of the bigeye tuna fisheries in the Indian Ocean over 1952-2014 were analysed and standardized to facilitate population dynamics modelling studies. During this sixty-two years historical period of exploitation, many changes occurred both in the fishing techniques and the monitoring of activity. This study includes a series of processing steps used for standardization of spatial resolution, conversion and standardization of catch and effort units, raising of geo-referenced catch into nominal catch level, screening and correction of outliers, and detection of major catchability changes over long time series of fishing data, i.e., the Japanese longline fleet operating in the tropical Indian Ocean. A total of thirty fisheries were finally determined from longline, purse seine and other-gears data sets, from which 10 longline and four purse seine fisheries represented 96% of the whole historical catch. The geo-referenced records consists of catch, fishing effort and associated length frequency samples of all fisheries.