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Jingtao Sun, Jin Qi, Zhen Yan, Yadong Li, Jie Liang and Sensen Wu
The COVID-19 pandemic has had a profound impact on people?s lives, making accurate prediction of epidemic trends a central focus in COVID-19 research. This study innovatively utilizes a spatiotemporal heterogeneity analysis (GTNNWR) model to predict COVI...
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Kaiwen Song, Xiujuan Jiang, Tianye Wang, Dengming Yan, Hongshi Xu and Zening Wu
The uneven spatial and temporal distribution of water resources has consistently been one of the most significant limiting factors for social development in many regions. Furthermore, with the intensification of climate change, this inequality is progres...
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Luís P. N. Mendes, Ana M. C. Ricardo, Alexandre J. M. Bernardino and Rui M. L. Ferreira
We present novel velocimetry algorithms based on the hybridization of correlation-based Particle Image Velocimetry (PIV) and a combination of Lucas?Kanade and Liu?Shen optical flow (OpF) methods. An efficient Aparapi/OpenCL implementation of those method...
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Younes Hamdani, Guohui Xiao, Linfang Ding and Diego Calvanese
The integration of the raster data cube alongside another form of geospatial data (e.g., vector data) raises considerable challenges when it comes to managing and representing it using knowledge graphs. Such integration can play an invaluable role in han...
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Gregorio Rosario Michel, María Ester Gonzalez-Campos, Fernando Manzano Aybar and Joep Crompvoets
The Dominican Republic (DR) is a small island developing state (SIDS) highly exposed to disaster-risk phenomena, such as earthquakes, hurricanes, etc. The Spatial Data Infrastructure (SDI) enables coordination and sharing of spatial information and servi...
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