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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

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

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.