Volume XLII-4/W8
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W8, 117–122, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W8-117-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W8, 117–122, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W8-117-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  11 Jul 2018

11 Jul 2018

OPEN FORIS AND GOOGLE EARTH ENGINE LINKING EXPERT PARTICIPATION WITH NATURAL RESOURCE MAPPING AND REMOTE SENSING TRAINING IN TANZANIA

U. Leinonen1, J. Koskinen1, H. Makandi2, E. Mauya3, and N. Käyhkö1 U. Leinonen et al.
  • 1University of Turku (UTU), Department of Geography and Geology, Finland
  • 2University of Dar es Salaam (UDSM), Institute of Resource Assessment, Tanzania
  • 3Sokoine University of Agriculture (SUA), College of Forestry, Wildlife and Tourism, Department of Forest Operations Management and Techniques, Tanzania

Keywords: Open source, earth observation, remote sensing, geospatial, cloud computing, crowdsourcing, training, Tanzania

Abstract. There is an increasing amount of open Earth observation (EO) data available, offering solutions to map, assess and monitor natural resources and to obtain answers to global and local societal challenges. With the help of free and open source software (FOSS) and open access cloud computing resources, the remote sensing community can take the full advantage of these vast geospatial data repositories. To empower developing societies, support should be given to higher education institutions (HEIs) to train professionals in using the open data, software and tools. In this paper, we describe a participatory mapping methodology, which utilizes open source software Open Foris and QGIS, various open Earth observation data catalogues, and computing capacity of the free Google Earth Engine cloud platform. Using this methodology, we arranged a collaborative data collection event, Mapathon, in Tanzania, followed by a training of the related FOSS tools for HEIs’ teaching staff. We collected feedback from the Mapathon participants about their learning experiences and from teachers about the usability of the methodology in remote sensing training in Tanzania. Based on our experiences and the received feedback, using a participatory mapping campaign as a training method can offer effective learning about environmental remote sensing through a real-world example, as well as networking and knowledge sharing possibilities for the participating group.