128 research outputs found
Coupling ground-level panoramas and aerial imagery for change detection
International audienceGeographic landscapes in all over the world may be subject to rapid changes induced, for instance, by urban, forest, and agricultural evolutions. Monitoring such kind of changes is usually achieved through remote sensing. However, obtaining regular and up-to-date aerial or satellite images is found to be a high costly process, thus preventing regular updating of land cover maps. Alternatively, in this paper, we propose a low-cost solution based on the use of ground-level geo-located landscape panoramic photos providing high spatial resolution information of the scene. Such photos can be acquired from various sources: digital cameras, smartphone, or even web repositories. Furthermore, since the acquisition is performed at the ground level, the users' immediate surroundings, as sensed by a camera device, can provide information at a very high level of precision, enabling to update the land cover type of the geographic area. In the described herein method, we propose to use inverse perspective mapping (inverse warping) to transform the geo-tagged ground-level 360 • photo onto a top-down view as if it had been acquired from a nadiral aerial view. Once re-projected, the warped photo is compared to a previously acquired remotely sensed image using standard techniques such as correlation. Wide differences in orientation, resolution, and geographical extent between the top-down view and the aerial image are addressed through specific processing steps (e.g. registration). Experiments on publicly available data-sets made of both ground-level photos and aerial images show promising results for updating land cover maps with mobile technologies. Finally, the proposed approach contributes to the crowdsourcing efforts in geo-information processing and mapping, providing hints on the evolution of a landscape. ARTICLE HISTOR
Investigating the feasibility of geo-tagged photographs as sources of land cover input data
Geo-tagged photographs are used increasingly as a source of Volunteered Geographic Information (VGI), which could potentially be used for land use and land cover applications. The purpose of this paper is to analyze the feasibility of using this source of spatial information for three use cases related to land cover: Calibration, validation and verification. We first provide an inventory of the metadata that are collected with geo-tagged photographs and then consider what elements would be essential, desirable, or unnecessary for the aforementioned use cases. Geo-tagged photographs were then extracted from Flickr, Panoramio and Geograph for an area of London, UK, and classified based on their usefulness for land cover mapping including an analysis of the accompanying metadata. Finally, we discuss protocols for geo-tagged photographs for use of VGI in relation to land cover applications
Learning to Map the Visual and Auditory World
The appearance of the world varies dramatically not only from place to place but also from hour to hour and month to month. Billions of images that capture this complex relationship are uploaded to social-media websites every day and often are associated with precise time and location metadata. This rich source of data can be beneficial to improve our understanding of the globe. In this work, we propose a general framework that uses these publicly available images for constructing dense maps of different ground-level attributes from overhead imagery. In particular, we use well-defined probabilistic models and a weakly-supervised, multi-task training strategy to provide an estimate of the expected visual and auditory ground-level attributes consisting of the type of scenes, objects, and sounds a person can experience at a location. Through a large-scale evaluation on real data, we show that our learned models can be used for applications including mapping, image localization, image retrieval, and metadata verification
APREGOAR: Development of a geospatial database applied to local news in Lisbon
Project Work presented as the partial requirement for obtaining a Master's degree in Geographic Information Systems and ScienceHá informações valiosas em formato de texto não estruturado sobre a localização, calendarização
e a essências dos eventos disponíveis no conteúdo de notícias digitais. Vários
trabalhos em curso já tentam extrair detalhes de eventos de fontes de notícias digitais,
mas muitas vezes não com a nuance necssária para representar com precisão onde as
coisas realmente acontecem. Alternativamente, os jornalistas poderiam associar manualmente
atributos a eventos descritos nos seus artigos enquanto publicam, melhorando a
exatidão e a confiança nestes atributos espaciais e temporais. Estes atributos poderiam
então estar imediatamente disponíveis para avaliar a cobertura temática, temporal e
espacial do conteúdo de uma agência, bem como melhorar a experiência do utilizador
na exploração do conteúdo, fornecendo dimensões adicionais que podem ser filtradas.
Embora a tecnologia de atribuição de dimensões geoespaciais e temporais para o
emprego de aplicaçãoes voltadas para o consumidor não seja novidade, tem ainda de
ser aplicada à escala das notícias. Além disso, a maioria dos sistemas existentes suporta
apenas uma definição pontual da localização dos artigos, que pode não representar bem
o(s) local(is) real(ais) dos eventos descritos.
Este trabalho define uma aplicação web de código aberto e uma base de dados
espacial subjacente que suporta i) a associação de múltiplos polígonos a representar
o local onde cada evento ocorre, os prazos associados aos eventos, em linha com os
atributos temáticos tradicionais associados aos artigos de notícias; ii) a contextualização
de cada artigo através da adição de mapas de eventos em linha para esclarecer aos
leitores onde os eventos do artigo ocorrem; e iii) a exploração dos corpora adicionados
através de filtros temáticos, espaciais e temporais que exibem os resultados em mapas
de cobertura interactivos e listas de artigos e eventos.
O projeto foi aplicado na área da grande Lisboa de Portugal. Para além da funcionalidade
acima referida, este projeto constroi gazetteers progressivos que podem ser
reutilizados como associações de lugares, ou para uma meta-análise mais aprofundada
do lugar, tal como é percebido coloquialmente. Demonstra a facilidade com que estas
dimensões adicionais podem ser incorporadas com grade confiança na precisão da definição, geridas, e alavancadas para melhorar a gestão de conteúdo das agências noticiosas,
a compreensão dos leitores, a exploração dos investigadores, ou extraídas para
combinação com outros conjuntos dos dados para fornecer conhecimentos adicionais.There is valuable information in unstructured text format about the location, timing,
and nature of events available in digital news content. Several ongoing efforts already
attempt to extract event details from digital news sources, but often not with the
nuance needed to accurately represent the where things actually happen. Alternatively,
journalists could manually associate attributes to events described in their articles while
publishing, improving accuracy and confidence in these spatial and temporal attributes.
These attributes could then be immediately available for evaluating thematic, temporal,
and spatial coverage of an agency’s content, as well as improve the user experience of
content exploration by providing additional dimensions that can be filtered.
Though the technology of assigning geospatial and temporal dimensions for the
employ of consumer-facing applications is not novel, it has yet to be applied at scale to
the news. Additionally, most existing systems only support a single point definition of
article locations, which may not well represent the actual place(s) of events described
within.
This work defines an open source web application and underlying spatial database
that supports i) the association of multiple polygons representing where each event
occurs, time frames associated with the events, inline with the traditional thematic
attributes associated with news articles; ii) the contextualization of each article via the
addition of inline event maps to clarify to readers where the events of the article occur;
and iii) the exploration of the added corpora via thematic, spatial, and temporal filters
that display results in interactive coverage maps and lists of articles and events.
The project was applied to the greater Lisbon area of Portugal. In addition to the
above functionality, this project builds progressive gazetteers that can be reused as place
associations, or for further meta analysis of place as it is colloquially understood. It
demonstrates the ease of which these additional dimensions may be incorporated with a
high confidence in definition accuracy, managed, and leveraged to improve news agency
content management, reader understanding, researcher exploration, or extracted for
combination with other datasets to provide additional insights
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