Remote Sensing in Land Science Studies

Mapping Land-Use Land-Cover Change (LULCC) with satellite remote sensing provides a reference for understanding the trajectories, patterns, drivers, and consequences of land-cover change. During the course, we will take a look at the advancement of classification and change detection techniques to map LULCC and land-use intensity. The course will cover state-of-the-art non-parametric machine learning classification methods (e.g., SVM, Random Forests, hybrid classifications, deep learning), enhancement of classifications, accuracy assessment, and multisource image fusion techniques, and analysis of large data composites, including cloud computation environment, such as GoogleEarth Engine. We will primarily concentrate on the utilization of freely available datasets: optical, such as Landsat, Sentinel-2 and MODIS imagery, and radar Sentinel-1. We will also revisit the utility of microsatellites, such as Planetscope. Last but not least, we will cover socio-economic and environmental applications, such as mapping wildfires, floodings, land-cover change, but also socio-economic footprint, i.e., with night-time lights (VIIRS and DMSP OLS).

The course builds on prior knowledge of working with satellite imagery, such as passing via Bachelor level class-Introduction to Remote Sensing, Classification of Spatial Data. However, we will try to accommodate the students without prior experience in remote sensing. The course also complements the class on Remote Sensing of the Biogeosphere. The course will be particularly useful for students who envision interdisciplinary use of satellite remote sensing in the Biogeosphere and Anthroposphere studies (human dimensions of land-cover change).

We will concentrate on the application of remote sensing to study land-cover transformation, such as urban sprawl and decline, agricultural and forestry dynamics. However, students are more than welcome to bring their own research projects, as well as to suggest alternate topics in line with their own interests. Students are also highly encouraged to incorporate knowledge gained via other classes and to perform interdisciplinary projects.