The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIV-M-3-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-M-3-2021, 73–78, 2021
https://doi.org/10.5194/isprs-archives-XLIV-M-3-2021-73-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-M-3-2021, 73–78, 2021
https://doi.org/10.5194/isprs-archives-XLIV-M-3-2021-73-2021

  10 Aug 2021

10 Aug 2021

INTEGRATION OF REMOTE SENSING & ENVIRONMENTAL SCIENCE IN PLACED-BASED LEARNING

A. R. Ignatius1 and M. G. Flood2 A. R. Ignatius and M. G. Flood
  • 1Institute for Environmental and Spatial Analysis, University of North Georgia. Oakwood, GA 30566, USA
  • 2Department of Biology, University of North Georgia. Oakwood, GA 30566, USA

Keywords: Remote Sensing, Pedagogy, Google Earth Engine, Environmental Science, Place-Based Education, STEM

Abstract. Integration of remote sensing techniques and Environmental Science methodologies in placed-based curriculum design creates unique learning opportunities. To promote introductory-level student engagement with STEM, our team designed a set of multidisciplinary teaching materials to intensely examine a single location: the Lake Sidney Lanier watershed of North Georgia, USA. Using a combination of scientific approaches from a variety of disciplines, course exercises encourage students to holistically learn about environmental conditions within the watershed. Remote sensing exercises are embedded throughout the course content and include analysis of historic aerial imagery, Landsat-derived dynamic surface water extent, google timelapse land cover change, Sentinel 2 spectral bands, and evaluation of topography.

Fundamental spatial concepts of scale and connectivity are considered using interdisciplinary approaches and local data. Landscape ecology is presented alongside remote sensing concepts of spatial and temporal resolution. This allows students to think about the diverse ways scientists understand scale, pattern, and the definition of “place”. Multiple data sources are also provided for each topic. For example, remote sensing imagery is used to investigate surface water conditions during drought and high-rainfall time periods. In addition, USGS streamgage river discharge data and rainfall estimates are provided for students to examine drought history using multiple parameters. Lastly, sensor deployment and limitations of each data source are described so that students understand both the history of place as well as the process and development of science. Through the use of a place-based curriculum design and interdisciplinary lab exercises, students gain a holistic understanding of a regional watershed.