Screenshot of nextstrain By reconstructing a phylogeny we can learn about important epidemiological phenomena. By adding geography to where the sample was taken we can map the spatial spread of a pathogen as well as how it may be changing in a certain location. By looking at this in context by adding in different geographies … Continue reading Mapping genomic data
Suitability Analysis
Recently I was putting together a short tutorial where the participants were going to use a suitability analysis approach to create a map. During the process I realised that I had not explained this process clearly so here is my short post about suitability analysis. Suitability mapping methods (also known as overlay or multi-criteria decision … Continue reading Suitability Analysis
Interpolation Methods for spatial data
Spatial Interpolation Methods For those of you new to interpolation methods. Interpolation is a procedure used to predict the values at locations that lack sampled points. It is based on the principle of spatial autocorrelation or spatial dependence (e.g. Tobler’s First Law of Geography), which measures degree of relationship or dependence between near and distant … Continue reading Interpolation Methods for spatial data
the geospatial ecosystem: Software, Libraries and Data Platforms
With more than 30 software packages to choose from to perform a range of analyses, where does one start? What software or data platforms, programming languages and libraries? To get you started see the image below where I have provided an overview of GIS and EO (Earth Observation) software tools, libraries in R and Python and … Continue reading the geospatial ecosystem: Software, Libraries and Data Platforms
GeoSpatialSense 