Section outline

  • Description

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    Online & in-person

    Ecotekne University Campus, Via Lecce-Monteroni, 73100 LE

            The password is   GGA2025!     and it will be valid also for the the recording video class.

            The class officially start at 15:00

            During the video class, please endeavor to keep your screen on as much as possible. This simple action fosters a sense of familiarity among participants, allowing for a more natural interaction. By seeing each other's faces, we move beyond mere avatars and engage more authentically with one another. Let's bring our virtual classroom to life with our video presence! Thanks for your support.

    In-person: Classroom Ce.S.I.L.D. in building C

    https://maps.app.goo.gl/YNoqSCaMH85QPmMTA

    (To open the maps press down CTRL+left mouse button on the google maps link)

    1-3 April 2025 (online)

    8-10 April, 2025 (online)

    17-18 April 2025 (in-person)

    25 (in-person)

    Giuseppe Amatulli (Spatial-Ecology), Saverio Mancino (Spatial-Ecology)

    On this course, students will be introduced to an array of powerful open-source geocomputation tools (GDAL & python) under Linux environment. Students who have never been exposed to programming under Linux are expected to reach a stage where they feel confident to understand and modify advanced open source data processing routines.  Our aim is to equip attendees with powerful tools and hone their ability for independent study afterwards. The acquired skills will be beneficial, not only for GIS related applications, but also for general data processing and applied statistical computing in a number of fields. We aim to provide a sound foundation for career development as a geographic data scientist.

    All course information will first be posted on the following link and then shared on this platform.

  • Course objectives

    On this course, students will be introduced to an array of powerful open-source geocomputation tools (GDAL & python) under Linux environment. Students who have never been exposed to programming under Linux are expected to reach a stage where they feel confident to understand and modify advanced open source data processing routines. Our aim is to equip attendees with powerful tools and hone their ability for independent study afterwards. The acquired skills will be beneficial, not only for GIS related applications, but also for general data processing and applied statistical computing in a number of fields. We aim to provide a sound foundation for career development as a geographic data scientist.

    All the class will be recorded. The video link will be posted in the syllabus below

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