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I've recently setup an elevation lookup service using https://github.com/perliedman/elevation-service. My use case is significantly different than yours, a few requests for lots of points vs lots of requests for a few points: the incoming requests a GeoJSON LineString features with a few thousand points. I currently have it deployed on a single t2.micro ec2 ...


Simple kriging may stay inside the data range, depending on the simple kriging mean, but ordinary kriging typically will not: > library(gstat) > library(sp) > p = SpatialPoints(cbind(c(0,0,0,0), 1:4)) > p$z = c(0,1,1,0) > p coordinates z 1 (0, 1) 0 2 (0, 2) 1 3 (0, 3) 1 4 (0, 4) 0 > krige(z~1, p, ...


Let's start with some assumptions: You really need 5000 web requests per second, and It would be possible to service those requests in only 5 seconds, and The queries could be serviced by exactly one CPU core, and Each core only needs 4GB of RAM, and The optimal core to CPU chassis distribution is 32, and Each CPU chasis has enough SSD disk to service all ...


Hypsography deals with the peak hights or one can say spot heights which we derive hights after completion of top maps


There are different types of kriging, which make different assumptions. Simple kriging assumes a known mean for the total extent and ordinary kriging assume a local mean defined within a radius. With those you should not predict larger values than your largest observed value. Universal kriging assumes a general polynomial trend model. The polynomial ...


Using the Contour plugin. Generate isolines and/or filled contours a set of data points.

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