calculateNSSDA.r

##################################
# Positional Accuracy Assessment #
# Script by Dakota Benjamin      #
# Based off ASPRS NSSDA Standard #
# Drafted 07-13-2016             #
##################################

#### Setup ####

rm(list=ls())
setwd("D://Akron_subset/agisoft/")

#### Load Data ####
gcp.err = read.csv("edited_GCP_errs.txt")
gcp.err.tot = gcp.err[21,6:9]
gcp.err = gcp.err[-21,]
print(cbind(gcp.err$X.Label ,gcp.err[,6:9]))


#### Horizontal accuracy ####
sq.diff.x = ( gcp.err$X.East - gcp.err$X_est )^2
sq.diff.y = ( gcp.err$Y.North - gcp.err$Y_est )^2
colK = sq.diff.x + sq.diff.y
hoz.sum = sum(colK)
hoz.avg = mean(colK)
hoz.rmse = tot.avg^0.5
hoz.nssda = tot.rmse * 1.7808
cat("Tested", hoz.nssda, "meters horizontal accuracy at 95% confidence level.")

#### Vertical Accuracy ####
sq.diff.z = ( gcp.err$Z.Altitude - gcp.err$Z_est )^2
vert.sum = sum(sq.diff.z)
vert.avg = mean(sq.diff.z)
vert.rmse = vert.avg^0.5
vert.nssda = vert.rmse * 1.9600
cat("Tested", vert.nssda, "meters vertical accuracy at 95% confidence level.")