70 lines
1.8 KiB
R
70 lines
1.8 KiB
R
## Laboratory exercise 9
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rm(list=ls())
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library(leaflet)
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library(sf)
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library(DataExplorer)
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library(lubridate)
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setwd('E://')
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pnt_data <- read.csv('rec.csv',header = FALSE,
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sep='',skip=15)
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#Time instants reformatting
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doy <- yday(pnt_data$V1)
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res1 <- ymd_hms(paste(pnt_data$V1,pnt_data$V2, sep=' '))
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hour <- hour(res1)
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min <- minute(res1)
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sec <- second(res1)
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timer <- doy + hour/24 + min/(24*60) + sec/(24*3600)
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latitude <- (pnt_data$V3 + 12.843697222222223)*6378137*pi/180
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longitude <- (pnt_data$V4 - 131.13274444444443)*6378137*pi/180
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height <- pnt_data$V5 - 125.1
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data <- as.data.frame(cbind(longitude, latitude, height))
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summary(data)
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plot(timer, latitude, type='l', col = 'red',
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ylim = c(min(latitude, longitude,height),
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max(latitude, longitude,height)),
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xlab='time [day in 2015]',ylab='errors [m]')
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lines(timer, longitude, col= 'dark green')
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lines(timer, height, col= 'blue')
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legend('topright', legend=c('latitude', 'longitude','height'),
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col=c('red','dark green', 'blue'), lty=1:1, cex=0.8,
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box.lty=0)
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plot_histogram(data)
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plot_correlation(data, maxcat = 5L)
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plot_boxplot(data, by = "height")
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boxplot(data, names=c('easting [m]',
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'northing [m]',
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'height [m]'),
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ylab='# of occurences', main='GPS only')
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# Define the coordinates
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lat2 <- -12.844
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lon2 <- 131.133
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# Create a spatial object from the data frame
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lon = lon2
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lat = lat2
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points <- st_as_sf(data.frame(lon= lon,
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lat = lat), coords = c("lon", "lat")) #,
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#crs = 4326)
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# Add tiles to the map
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map <- leaflet(points) %>%
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addTiles() %>%
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# Add markers for the two points with popup labels
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addMarkers(lng = ~lon, lat = ~lat,
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popup = ~paste("Point", round(lat), round(lon)))
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map
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