mapping and monitoring of natural resources - 10 ects
The 21st century has witnessed an increase in the availability of Earth observation (EO) data and their use in addressing critical problems in natural resources management (NRM). The myriad of datasets and stakeholder needs can make the selection of a specific sensor and analytical technique to address a problem a daunting task. At the heart of this dilemma is the scale of observation at which we can effectively address the problem. Biophysical processes, flows or interactions can occur at the plant, canopy or regional scale. These scales of observation correspond to spatial resolutions of 0.01-1m, 1-100m and 1-1000km over daily, monthly and annual time steps, respectively. Similarly, image-based map products have a specific purpose. For example, food security analysts may want to know the location of crop field boundaries in an agroecosystem, while foresters may want to assess forest stand biomass. We can address these problems effectively with very high spatial resolution (VHR) optical imagery. Object-based image analysis (OBIA) and vegetation indices, which are common analytical techniques applied to VHR optical imagery, can delineate discrete crop field boundaries and estimate vegetation index-based tree fractions correlated to forest stand biomass.
The guiding principle of this course, therefore, is to use the scale observation together with stakeholder needs to select and apply an appropriate EO dataset and analytical technique to solve problems within the three NRS Forest, Agriculture and Environment in the Spatial Sciences (FORAGES) themes (biodiversity conservation, forest management and food security analysis). In the end, students will be able to design a workflow to address these problems that includes the appropriate selection of EO data and analytical techniques.
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