ESP: ESP - ESTIMATION OF SCALE PARAMETER

View source: R/ESP.R

ESPR Documentation

ESP - ESTIMATION OF SCALE PARAMETER

Description

The ESP function by Dragut et al. (2010) calculates optimal segmentation scales by calculating, at first, the local variance for every segmented images and then by comparing the results of different segmentation levels (ROC-LV).

Usage

ESP(Tool, Scale.Input.Grid, Scale.Input.Grid.Cell.Size = "1",
  Scale.Statistic.Min.Size = "0", ESP.save = FALSE,
  ESP.save.path = NULL, Count = "1", Min = "0", Max = "0",
  Range = "0", Sum = "0", Mean = "0", Var = "0", Stddev = "1",
  Quantile = 0, Scales, Grass.ESP.Method = "Threshold", Segments.Poly,
  Seed.Method = "", ...)

Arguments

Tool

open-source software to compute segmentation analysis. GRASS or SAGA

Scale.Input.Grid

input grid for computing segmentation scale parameters

Scale.Input.Grid.Cell.Size

cell size of input grid. Default: "1"

Scale.Statistic.Min.Size

min size of area/polygon which is included in statistics (usefull for SAGA GIS segmentations). Default: "0"

ESP.save

save estimations of function. Default: FALSE

ESP.save.path

path where estimations are stored. Default: input path of segment.poly

Count

amount of cells (Grid Statistics). Default:"1"

Min

minimum value (Grid Statistics). Default:"0"

Max

maximum value (Grid Statistics). Default:"0"

Range

range of values (Grid Statistics). Default:"0"

Sum

sum of values (Grid Statistics). Default:"0"

Mean

mean of values (Grid Statistics). Default:"1"

Var

variance of values (Grid Statistics). Default:"0"

Stddev

standard deviation (Grid Statistics). Default:"1"

Quantile

qunatile (Grid Statistics). Default:"0"

Scales

containing scale parameters for loop-segmentation

Grass.ESP.Method

determining on which parameter the objective function (~loop) should be performed. Default: "Threshold"

Segments.Poly

...

Seed.Method

""

env

...

other...

see segmentation

Note

  • DRAGUT, L., TIEDE, D. & S.R. LEVICK (2010): ESP: a tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data. - International Journal of Geographical Information Science 24, 6, 859-871.


ggRaver/Lslide documentation built on April 8, 2022, 7:14 a.m.