%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.16.13.15
%2 sid.inpe.br/marte2/2017/10.27.16.13.16
%@isbn 978-85-17-00088-1
%F 61650
%T Movement ecology and human mobility in the GPS tracking era: new opportunities and challenges for remote sensing application
%D 2017
%A Brum-Bastos, Vanessa,
%@electronicmailaddress vdsbb@st-andrews.ac.uk
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
%C Santos
%8 28-31 maio 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 7047-7054
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X Recent advances in tracking technology and remote sensing have been shifting the core of movement research. The unprecedented quantity and quality of movement data along with the increasing availability of remotely sensed products allows movement researchers to investigate the role played by the environment in the phenomenon of movement. Environmental triggers of movement can be analysed using Context Aware Analysis (CAMA), a methodology that links trajectories to environmental data. Environmental data in CAMA comes from diverse sources, such as meteorological, weather radar and most often remote sensing data integrates context into movement and creates the so-called semantic trajectories which facilitates context-aware analysis and supports understanding of how environmental situation affects movement behaviour. However, CAMA is challenging due to the 1) complexity of remote sensing data; 2) spatial and temporal incompatibilities between movement and remotely sensed data; 3) multi dimensionality and 4) poor interpenetration between the remote sensing and movement science communities. Hoping to encourage this interdisciplinary dialogue, this paper presents preliminary results of CAMA using remotely sensed data from the NIMROD rainfall radar and gull tracking data which can be downloaded for free. The preliminary results show the potential of remote sensing to help answering movement research questions, as well as the potential of movement research as a new application domain for remote sensing.
%9 Mapeamento
%@language en
%3 61650.pdf