Impacts of the Modernization of Global Navigation Satellite Systems on Intelligent Transport Systems

ICCTP 2009 ◽  
2009 ◽  
Author(s):  
Xin Shi
Author(s):  
Chen Yu ◽  
Nigel T. Penna ◽  
Zhenhong Li

Real-time centimetre-level precise positioning from Global Navigation Satellite Systems (GNSS) is critical for activities including landslide, glacier and coastal erosion monitoring, flood modelling, precision agriculture, intelligent transport systems, autonomous vehicles and the Internet of Things. This may be achieved via the real-time kinematic (RTK) GNSS approach, which uses a single receiver and a network of continuously operating GNSS reference stations (CORS). However, existing CORS networks have often been established simply by attempting regular spacing or in clusters around cities, with little consideration of weather, climate and topography effects, which influence the GNSS tropospheric delay, a substantial GNSS positional error and which prevents homogeneous RTK accuracy attainment. Here, we develop a framework towards optimizing the design of CORS ground infrastructure, such that tropospheric delay errors reduce to 1.5 mm worth of precipitable water vapour (PWV) globally. We obtain average optimal station spacings of 52 km in local summer and 70 km in local winter, inversely related to the atmospheric PWV variation, with denser networks typically required in the tropics and in mountainous areas. We also consider local CORS network infrastructure case studies, showing how after network modification interpolated PWV errors can be reduced from around 2.7 to 1.4 mm.


2013 ◽  
Vol 19 (4) ◽  
pp. 746-764 ◽  
Author(s):  
Luciana Maria da Silva ◽  
Rodrigo Mikosz Gonçalves ◽  
Milde Maria da Silva Lira ◽  
Pedro de Souza Pereira

O crescimento da urbanização vem provocando grandes transformações nas relações sociais e morfológica das áreas costeiras. O presente trabalho tem como objetivo modelar massa de dados de diversas fontes como GNSS (Global Navigation Satellite Systems) e sensoriamento remoto para posteriormente prover a espacialização da vulnerabilidade costeira à erosão utilizando a lógica fuzzy. O método aplicado para análise da vulnerabilidade utilizou variáveis linguísticas, partições fuzzy, intervalos e análises paramétricas que caracterizam a modelagem fuzzy. Após análise, os níveis de vulnerabilidade à erosão costeira ao longo da linha de costa nas cidades do Recife e Jaboatão dos Guararapes no litoral de Pernambuco apresentaram os seguintes resultados: 33,33% da linha de costa possuem vulnerabilidade baixa, 38,15% possui vulnerabilidade moderada, 14,26% vulnerabilidade alta e 14,26% muito alta.


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