486 search results for "spatial"

Spatial data extraction around buffered points in R

November 8, 2014
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Quantifying spatial data (e.g. land cover) around points can be done in a variety of ways, some of which require considerable amounts of patience, clicking around, and/or cash for a license. Here’s a bit of code that I cobbled together to quickly extract land cover data from the National Land Cover Database for buffered regions around points (e.g....

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Generating Hurricanes with a Markov Spatial Process

September 30, 2014
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Generating Hurricanes with a Markov Spatial Process

The National Hurricane Center (NHC) collects datasets with all  storms in North Atlantic, the North Atlantic Hurricane Database (HURDAT). For all sorms, we have the location of the storm, every six jours (at midnight, six a.m., noon and six p.m.). Note that we have also the date, the maximal wind speed – on a 6 hour window – and...

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Spatial Clustering: Conley Standard Errors for R

September 8, 2014
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I have been working quite a lot with climate and weather data, to study the impact of rainfall shocks on violence in India and how this relationship changed, after the social insurance scheme NREGA was introduced. In my context, it becomes particularly relevant to adjust for spatial correlation if you find yourself in a situation

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Clipping spatial data in R

July 28, 2014
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Clipping spatial data in R

This miniature vignette shows how to clip spatial data based on different spatial objects in R and a ‘bounding box’. Spatial overlays are common in GIS applications and R users are fortunate that the clipping and spatial subsetting functions are mature and fairly fast. We’ll also write a new function called gClip(), that will make clipping by bounding boxes...

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Using R — Working with Geospatial Data (and ggplot2)

April 16, 2014
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Using R — Working with Geospatial Data (and ggplot2)

This is a follow-up blog-post to an earlier introductory post by Steven Brey: Using R: Working with Geospatial Data. In this post, we’ll learn how to plot geospatial data in ggplot2. Why might we want to do this? Well, it’s really …   read more ...

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Aggregating spatial points by clusters

March 21, 2014
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Aggregating spatial points by clusters

With ubiquitous collection devices (e.g. smartphones), having too much data may become an increasingly common problem for spatial analysts, even with increasingly powerful computers. This is ironic, because a few short decades ago, too little data was a primary constraint. This tutorial builds on the 'Attribute joins' section of the Creating maps in R tutorial to demonstrate how clusters can be...

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Aggregating spatial points by clusters

March 21, 2014
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Aggregating spatial points by clusters

With ubiquitous collection devices (e.g. smartphones), having too much data may become an increasingly common problem for spatial analysts, even with increasingly powerful computers. This is ironic, because a few short decades ago, too little data was a primary constraint. This tutorial builds on the 'Attribute joins' section of the Creating maps in R tutorial to demonstrate how clusters can be...

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Displaying time series, spatial, and space-time data with R is available for pre-order

Displaying time series, spatial, and space-time data with R is available for pre-order

Two years ago, motivated by a proposal from John Kimmel, Executive Editor at Chapman & Hall/CRC Press, I started working …Sigue leyendo →

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Use Case: Make Contour Lines for Google Earth with Spatial R

March 3, 2014
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Use Case: Make Contour Lines for Google Earth with Spatial R

Here's comes a script I wrote for creating contour lines in KML-format to be used with Google Earth https://github.com/gimoya/theBioBucket-Archives/blob/master/R/r_contours_for_google_earth.RIf you want to check or just use the datasets I created for t...

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Seventh Torino R net meeting, free spatial data analysis workshop and R introductory course

March 3, 2014
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Seventh Torino R net meeting, free spatial data analysis workshop and R introductory course

Seventh Torino R net meeting on 27 Mar 2014, exceptionally hosted at Polo Universitario di Asti, will have three presentations: Processing and analysis methods for DNA methylation array data, Giovanni Fiorito, Complex Systems for Life Sciences, University of Turin; Temporal Dominance of Sensations (TDS) … Continue reading →

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