Sökning: "Spatiotemporal data"

Visar resultat 1 - 5 av 70 avhandlingar innehållade orden Spatiotemporal data.

  1. 1. Bayesian Models for Spatiotemporal Data from Transportation Networks

    Författare :Héctor Rodriguez Déniz; Mattias Villani; Augusto Voltes-Dorta; Yusak Susilo; Linköpings universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian statistics; Transportation networks; Spatiotemporal data; Machine learning; Bayesiansk statistik; Transportnätverk; Spatiotemporal data; Maskininlärning;

    Sammanfattning : Urbanization has caused a historical transformation at a global scale, and humanity is moving towards a fully connected society where cities will concentrate population, infrastructure and economic activity. A key element in the cities’ infrastructure is the transportation system, as it facilitates the mobility of people and goods. LÄS MER

  3. 2. Disinformative and Uncertain Data in Global Hydrology : Challenges for Modelling and Regionalisation

    Författare :Anna Kauffeldt; Sven Halldin; Allan Rodhe; Chong-Yu Xu; András Bárdossy; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Data uncertainty; Discharge; Disinformative data; Evaporation; Flow-duration curve; Global hydrology; Neural networks; Numerical weather prediction; Precipitation; Quality control; Regionalisation; Ungauged basins; Water balance; Avdunstning; avrinningsområden utan vattenföringsdata; dataosäkerhet; desinformativa data; global hydrologi; kvalitetskontroll; nederbörd; neurala nät; numerisk vädermodell; regionalisering; varaktighetskurva; vattenbalans; vattenföring; Hydrology; Hydrologi;

    Sammanfattning : Water is essential for human well-being and healthy ecosystems, but population growth and changes in climate and land-use are putting increased stress on water resources in many regions. To ensure water security, knowledge about the spatiotemporal distribution of these resources is of great importance. LÄS MER

  4. 3. Understanding Human Mobility with Emerging Data Sources: Validation, spatiotemporal patterns, and transport modal disparity

    Författare :Yuan Liao; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; travel mode; data mining; travel time; mobility; social media data; gravity model; Twitter; geographical information systems;

    Sammanfattning : Human mobility refers to the geographic displacement of human beings, seen as individuals or groups, in space and time. The understanding of mobility has broad relevance, e.g., how fast epidemics spread globally. LÄS MER

  5. 4. Spatiotemporal prediction of arbovirus outbreak risk : the role of weather and population mobility

    Författare :Aditya L. Ramadona; Joacim Rocklöv; Yesim Tozan; Hari Kusnanto; Lutfan Lazuardi; Paula Moraga; Umeå universitet; []
    Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; arbovirus; dengue; temperature; rainfall; extreme weather; climate variability; population mobility; twitter data; social media; forecasting model; early warning; epidemic; big data; INLA; spatiotemporal model; climate services;

    Sammanfattning : Background: Arboviruses such as dengue and chikungunya have been a significant public health burden globally for several decades. In Indonesia, all four dengue serotypes are circulating. LÄS MER

  7. 5. Understanding Mobility and Transport Modal Disparities Using Emerging Data Sources: Modelling Potentials and Limitations

    Författare :Yuan Liao; Chalmers tekniska högskola; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; data mining; geographical information systems; mobility models; big trip data; transport modes; traffic data; social media data;

    Sammanfattning : Transportation presents a major challenge to curb climate change due in part to its ever-increasing travel demand. Better informed policy-making requires up-to-date empirical mobility data to model viable mitigation options for reducing emissions from the transport sector. LÄS MER