Applied Spatial Analysis

Applied Spatial Data Analysis with R, Second Edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data.

Applied Spatial Data Analysis with R, Second Edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data.

Become proficient in applied Remote Sensing (RS)/GQIS spatial analysis/ project analysis & fundamental concepts in QGIS.

Written by the 2018 Mindel C. Sheps Award winner, this textbook offers a unique method for teaching how to model spatial (multiregional) population dynamics through models of increasing complexity. Each chapter in this programmed workbook starts with a descriptive text, followed by a sequence of exercises focused on particular multiregional models, of increasing complexity, and then ends with the solutions.

Advanced spatial analysis in QGIS & using cloud computing tools: change detection, time series analysis, trends & more

Applied Spatial Data Analysis with R is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS.