1. Is there a standard name for the "number of available data points as a function
of the distance"? It is in fact a kind of two-point structure function.
Yes. I think what you want is the kernel, or the density of points within chosen distance. This is the smoothed histogram of the number of points within a given distance, commonly called a bandwidth. Look up kernel estimation for references. A good reference is Bailey and Gatrell. 1995. Interactive Spatial Data Analysis. Prentice Hall. 413 pp.
There are several other methods to quantify patchiness such as the K-function, also discussed in Bailey and Gatrell and numerous other texts.
As far as using this information in kriging reconstrucion, the variogram of cloud coverage should incorporate the patchiness of the clouds. I would expect there to be a rather pronounced "hole" effect due to either having a cloud or not.
good luck.
John
L. wrote:
Dear community,
we are applying kriging to remove clouds from satellite observations of chlorophyll
(phytoplankton). In order to estimate the error we need also to quantify cloud
patchiness. We do this by using the histogram of the number of available data
points as a function of the distance (that I will call just ''histogram" in the
following) as a kind of spectral analysis of the cloud coverage. The scale of the
patches appear very clear in this histogram. My questions are:
1. Is there a standard name for the "number of available data points as a function
of the distance"? It is in fact a kind of two-point structure function.
2. Has anybody before used this histogram for quantifying patchiness? Since
patches in kriging reconstruction are typical, the use of this histogram should
be quite standard, but I could not find anything in the literature.
Laurent Dubrocca, Francesco d'Ovidio, Yoav Lehahn
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