G
Gilberto Camara
Researcher at National Institute for Space Research
Publications - 41
Citations - 1803
Gilberto Camara is an academic researcher from National Institute for Space Research. The author has contributed to research in topics: Spatial analysis & Geographic information system. The author has an hindex of 17, co-authored 40 publications receiving 1714 citations.
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Journal ArticleDOI
Using Ontologies for Integrated Geographic Information Systems
TL;DR: The basic motivation of this paper is to introduce a GIS architecture that can enable geographic information integration in a seamless and flexible way based on its semantic value and regardless of its representation.
Journal ArticleDOI
Parameter selection for region‐growing image segmentation algorithms using spatial autocorrelation
Giovana Mira de Espindola,Gilberto Camara,Ilka Afonso Reis,L. S. Bins,Antônio Miguel Vieira Monteiro +4 more
TL;DR: An objective function is proposed for selecting suitable parameters for region‐growing algorithms to ensure best quality results and considers that a segmentation has two desirable properties: each of the resulting segments should be internally homogeneous and should be distinguishable from its neighbourhood.
Proceedings ArticleDOI
Next-Generation Digital Earth: A position paper from the Vespucci Initiative for the Advancement of Geographic Information Science
Max Craglia,Michael F. Goodchild,Alessandro Annoni,Gilberto Camara,Michael Gould,Werner Kuhn,David M. Mark,Ian Masser,David J. Maguire,Steve H. L. Liang,Ed Parsons +10 more
TL;DR: It is argued that the vision of Digital Earth put forward by VicePresident Al Gore 10 years ago needs to be re-evaluated in the light of the many developments in the fields of information technology, data infrastructures, and earth observation that have taken place since.
Journal ArticleDOI
DMSP/OLS night¿time light imagery for urban population estimates in the Brazilian Amazon
TL;DR: In this article, the authors analyzed DMSP/OLS night-time imagery as an information source to detect human settlements and to estimate the urban population in the Amazon region, where most of the urban settlements with a population higher than 5000 inhabitants were precisely identified.
Journal ArticleDOI
Tabu Search Heuristic for Point-Feature Cartographic Label Placement
TL;DR: It is concluded that TS is a recommended method to solve cartographic label placement problem of point features, due to its simplicity, practicality, efficiency and good performance along with its ability to generate quality solutions in acceptable computational time.