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UID:pretalx-foss4g-2022-BEFEBC@talks.staging.osgeo.org
DTSTART;TZID=CET:20220826T120000
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DESCRIPTION:Spatial stratification of landscapes allows for the development
  of efficient sampling surveys\, the inclusion of domain knowledge in data
 -driven modeling frameworks\, and the production of information relating t
 he spatial variability of response phenomena to that of landscape processe
 s. This work presents the rassta package as a collection of algorithms for
  spatial stratification developed in the R environment. The core ideas imp
 lemented in the rassta package include the multi-scale\, hierarchical land
 scape stratification based on spatial intersection\, the application of no
 n-parametric distribution estimators to define the typical landscape confi
 guration of stratification units\, and the use of spatially explicit lands
 cape correspondence metrics for non-probability sampling and predictive mo
 deling. The theoretical background of rassta is presented through referenc
 es to several studies which have benefited from landscape stratification r
 outines. The functionality of rassta is presented through code examples wh
 ich are complemented with the geographic visualization of their outputs. M
 oreover\, domain-specific applications are presented to demonstrate the ap
 plicability of rassta for the spatial modeling of diverse environmental ph
 enomena.
DTSTAMP:20260404T205932Z
LOCATION:General online
SUMMARY:rassta: Raster-based Spatial Stratification Algorithms - Bryan Fuen
 tes
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/BEFEBC/
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