View source: R/relationalObjectFunction.R
relationalObjectFunction | R Documentation |
This function calculates statistics of SpatialPolygonsDataFrame object relations
relationalObjectFunction(spdf, nb, var, quiet = TRUE)
spdf |
SpatialPolygonsDataFrame, or full path of a shapefile |
nb |
object neighborhood based on |
var |
vector with number or name defining 1. field of evaluation (i.e. slope) and 2. field of weights (i.e. area). For example: c("Slope", "Area") or c(1,2) |
quiet |
no outputs in console. Default: TRUE |
data.frame containing object statistics
relational object statistics according to ECOGNITION DEVELOPER (2014: 253-255):
m_wei - mean value of selected features of an object and its neighbors (of a selected class, see). For averaging, the feature values are weighted with the area of the objects.
sd_nb - standard deviation of selected features of an object and its neighbors It is also possible to calculate this feature with respect to a class, see
m_dif - mean difference between the feature value of an object and its neighbors (of a selected class, see) The feature values are weighted by the area of the respective objects
m_dif_abs - mean absolute difference
m_dif_hv - mean difference between the feature value of an object and the feature values of its neighbors (of a selected class, see), which have higher values than the object itself. The feature values are weighted by the area of the respective objects
m_dif_lw - mean difference between the feature value of an object and the feature values of its neighbors (of a selected class, see), which have lower values than the object itself. The feature values are weighted by the area of the respective objects
ratio_nb - proportion between the feature value of an object and the mean feature value of its neighbors (of a selected class, see) For averaging the feature values are weighted with the area of the corresponding objects
sum_nb - sum of the feature values of the neighbors (of a selected class, see )
num_nb - number of neighbors of (of a selected class, see )
min_nb - minimum value of the feature values of an object and its neighbors (of a selected class, see)
max_nb - maximum value of the feature values of an object and its neighbors (of a selected class, see)
ECOGNITION DEVELOPER (2014) Reference Book. Trimble Documentation, München, Germany
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