Search for dissertations about: "Meteorological Data"
Showing result 6 - 10 of 98 swedish dissertations containing the words Meteorological Data.
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6. Deep Learning for Geo-referenced Data : Case Study: Earth Observation
Abstract : The thesis focuses on machine learning methods for Earth Observation (EO) data, more specifically, remote sensing data acquired by satellites and drones. EO plays a vital role in monitoring the Earth’s surface and modelling climate change to take necessary precautionary measures. READ MORE
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7. An Informed System Development Approach to Tropical Cyclone Track and Intensity Forecasting
Abstract : Introduction: Tropical Cyclones (TCs) inflict considerable damage to life and property every year. A major problem is that residents often hesitate to follow evacuation orders when the early warning messages are perceived as inaccurate or uninformative. READ MORE
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8. Hydro-Climatic Variability and Change in Central America : Supporting Risk Reduction Through Improved Analyses and Data
Abstract : Floods and droughts are frequent in Central America and cause large social, economic and environmental impacts. A crucial step in disaster risk reduction is to have a good understanding of the causing mechanisms of extreme events and their spatio-temporal characteristics. READ MORE
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9. Meteorological impact and transmission errors in outdoor wireless sensor networks
Abstract : Wireless sensor networks have been deployed outdoors ever since their inception. They have been used in areas such as precision farming, tracking wildlife, and monitoring glaciers. These diverse application areas all have different requirements and constraints, shaping the way in which the sensor network communicates. READ MORE
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10. Data Assimilation in Fluid Dynamics using Adjoint Optimization
Abstract : Data assimilation arises in a vast array of different topics: traditionally in meteorological and oceanographic modelling, wind tunnel or water tunnel experiments and recently from biomedical engineering. Data assimilation is a process for combine measured or observed data with a mathematical model, to obtain estimates of the expected data. READ MORE