This page contains a national summary of the texture from the LTPP database.

The code to generate this is displayed first - then the graphics.

Use the menu to left to go straight to the texture for all sites, State Highway sites, Local Authority sites or Individual sites.

Data Importing

The code below imports the data from the 10m databases

#Sys.Date()
Sys.time()

## [1] "2021-11-29 11:09:26 NZDT"

#load database connection library
library(RODBC)
 
db <- "C:/local_databases/NZTA_SH&LA_LTPPData_IntCalib_1Jul2001-30Jun2021.mdb"

con2 <- odbcDriverConnect(paste0("Driver={Microsoft Access Driver (*.mdb, *.accdb)}; DBQ=", db))

Texture10m <- sqlFetch(con2, "10mTexture")
CalibrationSections <- sqlFetch(con2, "CalibrationSections")

library(tidyverse)
Councils <- CalibrationSections %>% filter(is.na(Region)) %>% group_by(NMA) %>% summarise()

# Create SH/LA column
library(dplyr)
library(stringr)

CalibrationSections <- CalibrationSections %>% mutate(OwnerType = if_else((str_detect(CAL_SECTION_ID, "CAL")|str_detect(CAL_SECTION_ID, "CS")), "SH", "LA"))

Texture10m <- Texture10m %>% left_join(CalibrationSections, by = c("SECTION_ID"="CAL_SECTION_ID"))

#Texture Plots

All texture plots

library(dplyr)
Texture10mL <- Texture10m %>% filter(LWPTxt < 10)
Texture10mR <- Texture10m %>% filter(RWPTxt < 10)

library(ggplot2)
ggobj2 <- ggplot(data=Texture10mL, aes(x=FinancialYear, y=LWPTxt, col = as.factor(LANE_DIRECTION))) +
  geom_boxplot() + ggtitle("All Texture10m LWP Boxplot") + facet_wrap(~SECTION_ID, ncol=5) + theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) + labs(col = "I/D") + ylab("LWP Texture MPD (mm)") + xlab("Financial Year") 
print(ggobj2)

ggobj2 <- ggplot(data=Texture10mR, aes(x=FinancialYear, y=RWPTxt, col = as.factor(LANE_DIRECTION))) +
  geom_boxplot() + ggtitle("All Texture10m RWP Boxplot") + facet_wrap(~SECTION_ID, ncol=5) + theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) + labs(col = "I/D") + ylab("RWP Texture MPD (mm)") + xlab("Financial Year") 
print(ggobj2)

SH texture plots

#SH Sites

Texture10mLSH <- Texture10mL  %>% filter(OwnerType == "SH")
Texture10mRSH <- Texture10mR  %>% filter(OwnerType == "SH")


library(ggplot2)
ggobj2 <- ggplot(data=Texture10mLSH, aes(x=FinancialYear, y=LWPTxt, col = as.factor(LANE_DIRECTION))) +
  geom_boxplot() + ggtitle("SH Texture10m LWP Boxplot") + facet_wrap(~SECTION_ID, ncol=5) + theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) + labs(col = "I/D") + ylab("LWP Texture MPD (mm)") + xlab("Financial Year") 
print(ggobj2)

ggobj2 <- ggplot(data=Texture10mRSH, aes(x=FinancialYear, y=RWPTxt, col = as.factor(LANE_DIRECTION))) +
  geom_boxplot() + ggtitle("SH Texture10m RWP Boxplot") + facet_wrap(~SECTION_ID, ncol=5) + theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) + labs(col = "I/D") + ylab("RWP Texture MPD (mm)") + xlab("Financial Year") 
print(ggobj2)

LA texture plots - none exist

#LA Sites

Texture10mLLA <- Texture10mL  %>% filter(OwnerType == "LA")
Texture10mRLA <- Texture10mR  %>% filter(OwnerType == "LA")

Big individual texture plots LWP

library(dplyr)
ggobj2Texture10mL <- Texture10mL %>% group_by(SECTION_ID) %>% do(plots=ggplot(data=.) +
         aes(x=FinancialYear, y=LWPTxt, col = as.factor(LANE_DIRECTION)) +  geom_boxplot() + labs(col = "I/D") + ggtitle("LWP Texture", subtitle = .$SECTION_ID) + ylab("LWP Texture MPD (mm)") + xlab("Financial Year"))   

print(ggobj2Texture10mL$plots)

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Big individual texture plots RWP

library(dplyr)
ggobj2Texture10mR <- Texture10mR %>% group_by(SECTION_ID) %>% do(plots=ggplot(data=.) +
         aes(x=FinancialYear, y=RWPTxt, col = as.factor(LANE_DIRECTION)) +  geom_boxplot() + labs(col = "I/D") + ggtitle("RWP Texture", subtitle = .$SECTION_ID) + ylab("RWP Texture MPD (mm)") + xlab("Financial Year"))   

print(ggobj2Texture10mR$plots)