README.md

In ragram: Radargrammetry

ragram

Radargrammetry R package

Installation

library(devtools)
install_github('Kleebaum/ragram')

Example usage

Load Sentinel-1 data of Kilimanjaro region

master <- sarRecord('extdata/S1A_IW_GRDH_1SDV_20151220T155517.SAFE/', satellite = 'sentinel') 
slave <- sarRecord('extdata/S1A_IW_GRDH_1SDV_20151215T154711.SAFE/', satellite = 'sentinel')

data(kili)

Plot (google) maps

plotMap(kili, orbit = F)
show(kili[[1]])
plotGmap(kili[[1]])

Plot incidence angles

plotAngles(kili[[1]])
plotAngles(kili[[5]])

plotAnglesDif(kili[[1]], kili[[2]])
plotOrbitNumber(kili[[1]])
plotOrbitNumber(kili[[2]])

plotAnglesDif(kili[[1]], kili[[5]])
plotOrbitNumber(kili[[1]], x=35.5)
plotOrbitNumber(kili[[5]], x=37.8)

Plot expected disparity

plotAnglesDif(kili[[1]], kili[[5]], disparity = T,
              legend.lab = 'Expected disparity [m]', h=100)

Inspect cropped Sentinel-1 same side stereo pair

plotGmap(master, xlim=c(37,37.7), ylim=c(-3.6,-2.8), sar=F)
plot(spTransform(border(master), CRS('+init=epsg:4326')), 
     add=T, col='white')
plotSAR(master, maxpixels = 500000)
plotSAR(slave, maxpixels = 500000)

Plot incidence angles and expected disparity

plotAngles(master, interpolate = T, aggregate.fact = 10)
plotAngles(slave, interpolate = T, aggregate.fact = 10)
plotAnglesDif(master, slave, interpolate = T, aggregate.fact = 10)

Calculate disparity map using zero normalied cross correlation (ZNCC)

master <- aggregate(master, 2)
dispMap <- disparityMap(master, slave, window.size = 25,
             search.area.size = 51)

dispMapLon <- raster(dispMap[,,1])
extent(dispMapLon) <- extent(master)
plot(dispMapLon)

dispMapLat <- raster(dispMap[,,2])
extent(dispMapLat) <- extent(master)
plot(dispMapLat)

dispMapDiagonal <- dispMapLon
values(dispMapDiagonal) <- sqrt(dispMapLon[]^2 + dispMapLat[]^2)
plot(dispMapDiagonal)

ragram documentation built on May 2, 2019, 4:42 p.m.