. . . "Evaluate the outcome of primary productivity and vegetation growth models."@en . . "Evaluate the outcome of primary productivity and vegetation growth models."@en . . . "Identify and analyse opportunities for improvement of real time monitoring of vegetation health and functioning."@en . . "Identify and analyse opportunities for improvement of real time monitoring of vegetation health and functioning."@en . . . "Describe the state-of-the-art of satellite models for the primary productivity."@en . . "Describe the state-of-the-art of satellite models for the primary productivity."@en . . . "Apply plant physiological, radiative transfer and vegetation models for the scaling of processes from leaf to satellite levels."@en . . "Apply plant physiological, radiative transfer and vegetation models for the scaling of processes from leaf to satellite levels."@en . . "https://ltb.itc.utwente.nl/page/792/concept/152751" . . "Plant physiological processes"@en . . . . "https://ltb.itc.utwente.nl/page/792/concept/152793" . . "Optical and thermal remote sensing of vegetation"@en . . . . "https://ltb.itc.utwente.nl/page/792/concept/152844" . "https://ltb.itc.utwente.nl/page/792/concept/152845" . . "Radiative transfer model"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "The Master’s Programme Geo-Information Science and Earth Observation (M-GEO) is a two-year academic curriculum at MSc level, taught fully in English, dedicated to understanding the earth’s systems from a geographic and spatial perspective. The field of Geo-information Science and Earth Observation has, in recent years, witnessed fast scientific and technological developments. As a result, geographic information has become a vital asset to society and part of our daily life. The ubiquitous production and availability of spatial data require cloud computing and new technology to turn the increasing volume of ‘big data’ to good use. The growing range of global challenges, from climate change and resource depletion to environmental pollution and pandemic diseases, that our society and in particular the more vulnerable populations on our planet are facing, increases the demand for academic professionals who have the ability, attitudes and skills to design solutions that are sustainable, transdisciplinary and innovative with positive societal impacts. Our education focuses on addressing these global problems by means of advanced geo-information and earth observation applications."@en . "Master’s Programme Geo-Information Science and Earth Observation (M-GEO)"@en . . "Master’s Programme Geo-Information Science and Earth Observation (M-GEO)"@en . . . . "Course"@en . "201900051" . "WRS_0004" . "5"^^ . "140"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "basic knowledge on remote sensing."@en . "2"^^ . "2" . "1B " . "2022-11-13T23:00:00Z"^^ . "Plants play a crucial role in the history of the Earth. They have accelerated the water cycle, and have made soil formation possible, and provide Oxygen through photosynthesis. They are also the primary sink of carbon dioxide, and they are our food.\n\nOngoing changes in climate affect the functioning of plants, but also vice versa: Land cover changes affect the surface properties of the Earth which in turn affect the climate. For sustainable land cover, ecology and food production, we must be able to quantify the role of plants in the climate on Earth.\n\nThis course offers tools to quantify processes in terrestrial vegetation using contemporary remote sensing signals (reflectance, chlorophyll fluorescence, and thermal remote sensing) in combination with in situ data. There is attention for natural ecosystems as well as crops.The following topics will be covered:\n\nPlant physiological processes and their relation with satellite data\nThe use of radiative transfer models for scaling processes from the molecular to the satellite level\nThe retrieval of plant functional traits from satellite data, in particular Sentinel 1,2,3, and 5 (Tropomi), and airborne data collected in the frame of the ESA’s 8th Earth Explorer mission FLEX.\nThe use of these data in dynamic vegetation model\nThe participants will work on their own mini-project, such as: the effect of companion planting, the water productivity or water footprint, the effect of volcano eruptions, re- or deforestation."@en . "Remote Sensing and Modelling of Primary Productivity and Plant Growth"@en . "RS & Mod. Primary Prod. & Plant Growth"@en . "RS & Mod. Primary Prod. & Plant