An introduction to spatial data analysis : remote sensing and GIS with open source software

Wegmann, Martin (author.). Schwalb-Willmann, Jakob, (author.).

Summary: "This book is for novice spatial data users and does not assume any prior knowledge of spatial data itself or practical experience working with such data sets. Readers will likely include student and professional ecologists, geographers and any environmental scientists or practitioners who need to collect, visualize and analyse spatial data." -- amazon.com

Record details

ISBN: 1784272132
ISBN: 9781784272135 (softcover)
Physical Description: print
xiii, 216 pages : illustrations (some color) ; 25 cm.
Publisher: Exeter, UK : Pelagic Publishing, [2020]
Copyright: ©2020

Content descriptions

Formatted Contents Note:

Machine generated contents note: 1. Introduction and overview -- 1.1. Spatial data -- 1.2. First spatial data analysis -- 1.3. Next steps -- pt. I Data acquisition, data preparation and map creation -- 2. Data acquisition -- 2.1. Spatial data for a research question -- 2.2. AOI -- 2.3. Thematic raster map acquisition -- 2.4. Thematic vector map acquisition -- 2.5. Satellite sensor data acquisition -- 2.6. Summary and further reading -- 3. Data preparation -- 3.1. Deciding on a projection -- 3.2. Reprojecting raster and vector layers -- 3.3. Clipping to an AOI -- 3.4. Stacking raster layers -- 3.5. Visualizing a raster stack as RGB -- 3.6. Summary and further reading -- 4. Creating maps -- 4.1. Maps in QGIS -- 4.2. Maps for presentations -- 4.3. Maps with statistical information -- 4.4. Common mistakes and recommendations -- 4.5. Summary and further reading -- pt. II Spatial field data acquisition and auxiliary data -- 5. Field data planning and preparation -- 5.1. Field sampling strategies -- 5.2. From GIS to global positioning system (GPS) -- 5.3. On-screen digitization -- 5.4. Summary and further reading -- 6. Field sampling using a global positioning system (GPS) -- 6.1. GPS in the field -- 6.2. GPX from GPS -- 6.3. Summary -- 7. From global positioning system (GPS) to geographic information system (GIS) -- 7.1. Joint coordinates and measurement sheet -- 7.2. Separate coordinates and measurement sheet -- 7.3. Point measurement to information -- 7.4. Summary -- pt. III Data analysis and new spatial information -- 8. Vector data analysis -- 8.1. Percentage area covered -- 8.2. Spatial distances -- 8.3. Summary and further analyses -- 9. Raster analysis -- 9.1. Spectral landscape indices -- 9.2. Topographic indices -- 9.3. Spectral landscape categories -- 9.4. Summary and further analysis -- 10. Raster-vector intersection -- 10.1. Point statistics -- 10.2. Zonal statistics -- 10.3. Summary -- pt. IV Spatial coding -- 11. Introduction to coding -- 11.1. Why use the command line and what is `R'? -- 11.2. Getting started -- 11.3. Your very first command -- 11.4. Classes of data -- 11.5. Data indexing (subsetting) -- 11.6. Importing and exporting data -- 11.7. Functions -- 11.8. Loops -- 11.9. Scripts -- 11.10. Expanding functionality -- 11.11. Bugs, problems and challenges -- 11.12. Notation -- 11.13. Summary and further reading -- 12. Getting started with spatial coding -- 12.1. Spatial data in R -- 12.2. Importing and exporting data -- 12.3. Modifying spatial data -- 12.4. Downloading spatial data from within R -- 12.5. Organization of spatial analysis scripts -- 12.6. Summary -- 13. Spatial analysis in R -- 13.1. Vegetation indices -- 13.2. Digital elevation model (DEM) derivatives -- 13.3. Classification -- 13.4. Raster-vector interaction -- 13.5. Calculating and saving aggregated values -- 13.6. Summary and further reading -- 14. Creating graphs in R -- 14.1. Aggregated environmental information -- 14.2. Non-aggregated environmental information -- 14.3. Finalizing and saving the plot -- 14.4. Summary and further reading -- 15. Creating maps in R -- 15.1. Vector data -- 15.2. Plotting study area data -- 15.3. Summary and further reading.