. . . . "ITC Bok"@en . . "https://ltb.itc.utwente.nl/page/792/concept/152798" . . "Sampling statistics"@en . . . . . "https://ltb.itc.utwente.nl/page/792/concept/152955" . . "Descriptive statistics"@en . . . . . . . . . "https://ltb.itc.utwente.nl/page/792/concept/152962" . . "Inferential statistics"@en . . . . . . . . . . "https://ltb.itc.utwente.nl/page/792/concept/152857" . . "Bayesian statistics"@en . . . . "https://ltb.itc.utwente.nl/page/792/concept/152891" . . "Co-kriging"@en . . . . "201800299" . "NRM_004" . "7"^^ . "196"^^ . "10"^^ . "2023-07-06T22:00:00Z"^^ . "f2f" . "online" . "With lectures, we will introduce you to background knowledge, concepts and theory behind environmental models. Supervised and unsupervised practicals on the environmental models are scheduled throughout the course for hands-on experience. A day is typically closed with a plenary question and answer session. Knowledge is tested with one graded individual assignment and one written test."@en . . . . . . . "(NRM3 is not a prerequisite) Basic knowledge on and skills in remote sensing and GIS. ,Basic knowledge on and skills in remote sensing and GIS."@en . . . . . . . . . "7"^^ . "4" . "2B" . . . . "2023-04-23T22:00:00Z"^^ . "The previous Natural Resource Management (NRM) courses have focused on the inventory natural resources and to detect and assess changes in the environment such as loss of ecosystems and biodiversity, deforestation and forest degradation and threats to food security due to decreased crop yields. Different methods and techniques are available to guide NRM in its efforts to reverse resource degradation or alleviate its consequences. Proper understanding of cause and effect of changes in natural resources is crucial to achieve this. As these changes occur in the real-world, and not in a laboratory set-up, making statements about causal relations is a challenge.\n\nIn this course, students will study generic techniques and apply and evaluate environmental models that aim to estimate change in natural resources in response to environmental changes."@en . "Environmental modelling: causes and impacts of changing resources"@en . . "Environmental modelling: causes and impacts of changing resources"@en . "Env. Modelling: Changing Resources"@en . . "5.0" . "140.0" . "10.0" . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "4.0" . "3.0" . "[CONCEPT] Monitoring of physical and chemical atmospheric, land and ocean variables with remote sensing requires an understanding of Earth’s ecosystems. Understanding of systems can be based on expert knowledge, experimental relations or physical relations, and this understanding can be captured in a descriptive model. Models are to understand, detect, predict, and describe interactions within and between ecosystems and the atmosphere across scales that range from local to global.\n\nRemote sensing can be used for parameter input in models, but also for spatial and temporal interpolation or extrapolation. This course provides an introduction to knowledge-driven, data-driven and physical modelling, starting with appropriate model selection given a specific problem or data availability. The course therefore deals with basic concepts and boundary conditions. Much emphasis is on integration of remote sensing observations into models, and selecting optimal object / pixel / time based mapping method for a given problem "@en . "Modeling & Mapping"@en . . "Modeling & Mapping"@en . "Modeling & Mapping"@en . "https://ltb.itc.utwente.nl/page/792/concept/152741" . . "Statistics"@en