Cultural skills (knowledge of): spatial attributes of ecological processes - spatial ecology: concepts and applications - GIS: functionality, data model and types of software
Methodological skills (knowing how to perform): practical use of GIS software - retrieval, analysis and interpretation of spatial data - identification and evaluation of ecological spatial patterns
Methodological skills (knowing how to perform): practical use of GIS software - retrieval, analysis and interpretation of spatial data - identification and evaluation of ecological spatial patterns
scheda docente
materiale didattico
- Intro to spatial ecology and cartography
- GIS: functions, geographical approach and modeling of reality
- Types of GIS software: open source and proprietary software
- Data models: vectorial (points, lines and polygons) and raster (pixel)
- Principles and methods in remote sensing: electromagnetic reflectance, remote sensed image resolution, active and passive sensors, remote sensing platforms
- Species distributions and biodiversity mapping
Practicals (software: QGIS and R)
- Visualization of geographical objects(features) on a map
- Preparation of plant and animal maps
- Preparation and analysis of environmental maps (land use/land cover, habitat maps, photosynthetic activity, etc.) in time and in space
- Principles and methods of cartographic extraction of bio-environmental features
- Introduction to Species Distribution Modeling (SDM)
Software:
QGIS.org, 2022. QGIS Geographic Information System. QGIS Association. http://www.qgis.org
R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
Office hours by appointment via email: marta.carboni@uniroma3.it
Programma
Theory- Intro to spatial ecology and cartography
- GIS: functions, geographical approach and modeling of reality
- Types of GIS software: open source and proprietary software
- Data models: vectorial (points, lines and polygons) and raster (pixel)
- Principles and methods in remote sensing: electromagnetic reflectance, remote sensed image resolution, active and passive sensors, remote sensing platforms
- Species distributions and biodiversity mapping
Practicals (software: QGIS and R)
- Visualization of geographical objects(features) on a map
- Preparation of plant and animal maps
- Preparation and analysis of environmental maps (land use/land cover, habitat maps, photosynthetic activity, etc.) in time and in space
- Principles and methods of cartographic extraction of bio-environmental features
- Introduction to Species Distribution Modeling (SDM)
Testi Adottati
Materials, PDFs of lecture slides and scripts are made available during the courseSoftware:
QGIS.org, 2022. QGIS Geographic Information System. QGIS Association. http://www.qgis.org
R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
Office hours by appointment via email: marta.carboni@uniroma3.it
Modalità Valutazione
Evaluation will consist in a final exam with an oral discussion and a practical exam and in a written report based on a GIS project.