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FR_paperBased_Annex.R
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FR_paperBased_Annex.R
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#setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard")
library(dplyr)
library(tidyr)
require(plyr)
library(rgdal)
library(raster)
library(dismo)
library(maptools)
library(rgeos)
require(RColorBrewer)
require(graphics)
require(rasterVis)
require(sp)
library(ggthemes)
require(ggplot2)
library(gridExtra)
library(hexbin)
library(viridis)
library(sf)
library(ggspatial)
library(grid)
require(qpdf)
#######################################################################################
## Read the GIS layers
#######################################################################################
TownsNG <- readOGR(dsn = ".", layer = "Places_towns")
RiversNG <- readOGR(dsn = ".", layer = "Rivers")
boundaryNG <- readOGR(dsn=getwd(), layer="gadm36_NGA_1")
ngstate <- readOGR(dsn=getwd(), layer="gadm36_NGA_2")
boundaryTZ <- readOGR(dsn=getwd(), layer="gadm36_TZA_1")
tzRegion <- readOGR(dsn=getwd(), layer="gadm36_TZA_2")
###################################################################################################
## NG fertilizer recom for FCY 1:5
###################################################################################################
FR_NG_FCY1 <- readRDS("/home/akilimo/projects/PaperbasedDashboard_v2/FRrecom_lga_level1_NG_2020.RDS")
FR_NG_FCY2 <- readRDS("/home/akilimo/projects/PaperbasedDashboard_v2/FRrecom_lga_level2_NG_2020.RDS")
FR_NG_FCY3 <- readRDS("FRrecom_lga_level3_NG_2020.RDS")
FR_NG_FCY4 <- readRDS("FRrecom_lga_level4_NG_2020.RDS")
FR_NG_FCY5 <- readRDS("FRrecom_lga_level5_NG_2020.RDS")
###########################################################################
## TZ fertilizer recom for FCY 1:5
###########################################################################
FR_TZ_FCY1 <- readRDS("FRrecom_lga_level1_TZ_2020.RDS")
FR_TZ_FCY2 <- readRDS("FRrecom_lga_level2_TZ_2020.RDS")
FR_TZ_FCY3 <- readRDS("FRrecom_lga_level3_TZ_2020.RDS")
FR_TZ_FCY4 <- readRDS("FRrecom_lga_level4_TZ_2020.RDS")
FR_TZ_FCY5 <- readRDS("FRrecom_lga_level5_TZ_2020.RDS")
###########################################################################
## Ghana fertilizer recom for FCY 1:5
###########################################################################
FCY_FRData <- readRDS("/home/akilimo/projects/PaperbasedDashboard_v2/GH_FR_CassavaPaperBased.RDS")
FR_GH_FCY1 <- FCY_FRData[FCY_FRData$FCY == "level1", ]
FR_GH_FCY2 <- FCY_FRData[FCY_FRData$FCY == "level2", ]
FR_GH_FCY3 <- FCY_FRData[FCY_FRData$FCY == "level3", ]
FR_GH_FCY4 <- FCY_FRData[FCY_FRData$FCY == "level4", ]
FR_GH_FCY5 <- FCY_FRData[FCY_FRData$FCY == "level5", ]
head(FCY_FRData)
ghRegion
unique(FR_GH_FCY2[FR_GH_FCY2$Regions == "Central",]$Districts)
###########################################################################
## Rwanda fertilizer recom for FCY 1:5
###########################################################################
FCY_FRData <- readRDS("/home/akilimo/projects/PaperbasedDashboard_v2/RW_CassavaPaperBased.RDS")
names(FCY_FRData)[18] <- "DISTRICT"
FCY_FRData <- FCY_FRData[FCY_FRData$harvMonth == 12, ]
FR_RW_FCY1 <- FCY_FRData[FCY_FRData$FCY == "level1", ]
FR_RW_FCY2 <- FCY_FRData[FCY_FRData$FCY == "level2", ]
FR_RW_FCY3 <- FCY_FRData[FCY_FRData$FCY == "level3", ]
FR_RW_FCY4 <- FCY_FRData[FCY_FRData$FCY == "level4", ]
FR_RW_FCY5 <- FCY_FRData[FCY_FRData$FCY == "level5", ]
head(FCY_FRData)
unique(FCY_FRData$STATE)
unique(FCY_FRData$District)
###########################################################################
## Burundi fertilizer recom for FCY 1:5
###########################################################################
FCY_FRData <- readRDS("/home/akilimo/projects/PaperbasedDashboard_v2/Bu_FR_CassavaPaperBased.RDS")
FCY_FRData <- FCY_FRData[FCY_FRData$harvMonth == 12, ]
FR_Bu_FCY1 <- FCY_FRData[FCY_FRData$FCY == "level1", ]
FR_Bu_FCY2 <- FCY_FRData[FCY_FRData$FCY == "level2", ]
FR_Bu_FCY3 <- FCY_FRData[FCY_FRData$FCY == "level3", ]
FR_Bu_FCY4 <- FCY_FRData[FCY_FRData$FCY == "level4", ]
FR_Bu_FCY5 <- FCY_FRData[FCY_FRData$FCY == "level5", ]
head(FCY_FRData)
unique(FCY_FRData$plw)
FCY_FRData[FR_Bu_FCY2$plw == 42 & FCY_FRData$Commune == "Mugina" & FCY_FRData$FCY == "level2", ]
###########################################################################
## adding planting month
###########################################################################
addplm <- function(ds, country){
ds$respY <- ds$TargetY - ds$CurrentY
ds$groRev <- ds$NR + ds$TC
ds$plm <- as.factor(ds$plw)
if(country == "Bu"){
ds$plm <- ifelse(ds$plm %in% c(2), "January",
ifelse(ds$plm %in% c(33), "August",
ifelse(ds$plm == 38, "September",
ifelse(ds$plm == 42, "October",
ifelse(ds$plm == 46, "November", "December")))))
}else if(country == "RW"){
ds$plm <- ifelse(ds$plm %in% c(6,7,8,9), "February",
ifelse(ds$plm %in% c(10,11,12,13,14), "March",
ifelse(ds$plm %in% c(37,38,39,40), "September", "October")))
}else{
levels(ds$plm)[levels(ds$plm) %in% 1:4] <- "January"
levels(ds$plm)[levels(ds$plm) %in% 5:8] <- "February"
levels(ds$plm)[levels(ds$plm) %in% 9:13] <- "March"
levels(ds$plm)[levels(ds$plm) %in% 14:17] <- "April"
levels(ds$plm)[levels(ds$plm) %in% 18:22] <- "May"
levels(ds$plm)[levels(ds$plm) %in% 23:26] <- "June"
levels(ds$plm)[levels(ds$plm) %in% 27:30] <- "July"
levels(ds$plm)[levels(ds$plm) %in% 31:35] <- "August"
levels(ds$plm)[levels(ds$plm) %in% 36:39] <- "September"
levels(ds$plm)[levels(ds$plm) %in% 40:43] <- "October"
levels(ds$plm)[levels(ds$plm) %in% 44:48] <- "November"
levels(ds$plm)[levels(ds$plm) %in% 49:53] <- "December"
}
if(country=="NG"){
ds$rateUrea <- ds$urea
ds$rateNPK151515 <- ds$NPK15_15_15
}else if (country == "TZ"){
ds$rateUrea <- ds$urea
ds$rateNPK171717 <- ds$NPK17_17_17
ds$rateDAP <- ds$DAP
}else if (country == "GH"){
ds$rateUrea <- ds$Urea
ds$rateNPK112221 <- ds$NPK112221
ds$rateNPK251010 <- ds$NPK251010
ds$rateNPK152020 <- ds$NPK152020
ds$rateNPK123017 <- ds$NPK123017
}else if (country == "RW"){
ds$rateUrea <- ds$Urea
ds$rateNPK171717 <- ds$NPK17_17_17
ds$rateMOP <- ds$MOP
ds$rateNDAP <- ds$DAP
}else if (country == "Bu"){
ds$rateFOMI_TOTAHAZA <- ds$FOMI_TOTAHAZA
ds$rateFOMI_IMBURA <- ds$FOMI_IMBURA
ds$rateFOMI_BAGARA <- ds$FOMI_BAGARA
}
return(ds)
}
FR_NG_FCY1_plm <- addplm(ds=FR_NG_FCY1, country = "NG") ## NG if user current yield is level 1
FR_NG_FCY2_plm <- addplm(ds=FR_NG_FCY2, country = "NG") ## NG if user current yield is level 2
FR_NG_FCY3_plm <- addplm(ds=FR_NG_FCY3, country = "NG") ## NG if user current yield is level 3
FR_NG_FCY4_plm <- addplm(ds=FR_NG_FCY4, country = "NG") ## NG if user current yield is level 4
FR_NG_FCY5_plm <- addplm(ds=FR_NG_FCY5, country = "NG") ## NG if user current yield is level 5
FR_TZ_FCY1_plm <- addplm(ds=FR_TZ_FCY1, country = "TZ") ## TZ if user current yield is level 1
FR_TZ_FCY2_plm <- addplm(ds=FR_TZ_FCY2, country = "TZ") ## TZ if user current yield is level 1
FR_TZ_FCY3_plm <- addplm(ds=FR_TZ_FCY3, country = "TZ") ## TZ if user current yield is level 1
FR_TZ_FCY4_plm <- addplm(ds=FR_TZ_FCY4, country = "TZ") ## TZ if user current yield is level 1
FR_TZ_FCY5_plm <- addplm(ds=FR_TZ_FCY5, country = "TZ") ## TZ if user current yield is level 1
FR_GH_FCY1_plm <- addplm(ds=FR_GH_FCY1, country = "GH") ## GH if user current yield is level 1
FR_GH_FCY2_plm <- addplm(ds=FR_GH_FCY2, country = "GH") ## GH if user current yield is level 2
FR_GH_FCY3_plm <- addplm(ds=FR_GH_FCY3, country = "GH") ## GH if user current yield is level 3
FR_GH_FCY4_plm <- addplm(ds=FR_GH_FCY4, country = "GH") ## GH if user current yield is level 4
FR_GH_FCY5_plm <- addplm(ds=FR_GH_FCY5, country = "GH") ## GH if user current yield is level 5
FR_RW_FCY1_plm <- addplm(ds=FR_RW_FCY1, country = "RW") ## RW if user current yield is level 1
FR_RW_FCY2_plm <- addplm(ds=FR_RW_FCY2, country = "RW") ## RW if user current yield is level 2
FR_RW_FCY3_plm <- addplm(ds=FR_RW_FCY3, country = "RW") ## RW if user current yield is level 3
FR_RW_FCY4_plm <- addplm(ds=FR_RW_FCY4, country = "RW") ## RW if user current yield is level 4
FR_RW_FCY5_plm <- addplm(ds=FR_RW_FCY5, country = "RW") ## RW if user current yield is level 5
FR_Bu_FCY1_plm <- addplm(ds=FR_Bu_FCY1, country = "Bu") ## Bu if user current yield is level 1
FR_Bu_FCY2_plm <- addplm(ds=FR_Bu_FCY2, country = "Bu")
FR_Bu_FCY3_plm <- addplm(ds=FR_Bu_FCY3, country = "Bu")
FR_Bu_FCY4_plm <- addplm(ds=FR_Bu_FCY4, country = "Bu")
FR_Bu_FCY5_plm <- addplm(ds=FR_Bu_FCY5, country = "Bu")
FR_Bu_FCY2_plm[FR_Bu_FCY2_plm$plw == 42 & FR_Bu_FCY2_plm$Commune == "Mugina" & FR_Bu_FCY2_plm$FCY == "level2", ]
###########################################################################
## select FCY and read the corresponding file
## NG: Subsetting for the user defined Region and selecting a coordinate to put the state name in the map
###########################################################################
ds <- FR_NG_FCY2_plm ## ds will be defined based on the current yield. e.g. if user idicate that thier current yield is yield level 2 ds = FR_NG_FCY2_plm
Oyo <- droplevels(ds[ds$STATE == "Oyo", ])
Oyolabel <- data.frame(state= c("Oyo"), lon=c(3.3), lat=c(9))
Ogun <- droplevels(ds[ds$STATE == "Ogun", ])
Ogunlabel <- data.frame(state= c("Ogun"), lon=c(3.4), lat=c(7.65))
Kogi <- droplevels(ds[ds$STATE == "Kogi", ])
Kogilabel <- data.frame(state= c("Kogi"), lon=c(6.63), lat=c(8.56))
Kwara <- droplevels(ds[ds$STATE %in% c("Kwara"), ])
Kwaralabel <- data.frame(state= c( "Kwara"), lon=c(4.9), lat=c(9.5))
Taraba <- droplevels(ds[ds$STATE %in% c("Taraba"), ])
Tarabalabel <- data.frame(state= c( "Taraba"), lon=c(10.2), lat=c(9.05))
Benue_CR <- droplevels(ds[ds$STATE %in% c("Benue","Cross River"), ])
Benue_CRlabel <- data.frame(state= c("Benue", "Cross River"), lon=c(8, 9.5), lat=c(8.2, 5.8))
Edo <- droplevels(ds[ds$STATE %in% c("Edo"), ])
Edolabel <- data.frame(state= c("Edo"), lon=c(5.3), lat=c(7))
Delta_Edo <- droplevels(ds[ds$STATE %in% c("Delta","Edo"), ])
Delta_Edolabel <- data.frame(state= c( "Delta","Edo"), lon=c(6, 5.3), lat=c(5,7))
Akwa_Ibom <- droplevels(ds[ds$STATE %in% c("Akwa Ibom"), ])
Akwa_Ibomlabel <- data.frame(state= c( "Akwa Ibom"), lon=c(8), lat=c(5.45))
Imo <- droplevels(ds[ds$STATE %in% c("Imo"), ])
Imolabel <- data.frame(state= c( "Imo"), lon=c(6.9), lat=c(5.9))
Abia <- droplevels(ds[ds$STATE %in% c("Abia"), ])
Abialabel <- data.frame(state= c( "Abia"), lon=c(7.7), lat=c(5.9))
AkwaIbom_Imo_Abia <- droplevels(ds[ds$STATE %in% c("Akwa Ibom", "Imo", "Abia"), ])
AkwaIbom_Imo_AbiAlabel <- data.frame(state= c( "Akwa Ibom", "Imo", "Abia"), lon=c(7.3, 7, 7.8), lat=c(4.4, 6, 6))
Ondo <- droplevels(ds[ds$STATE %in% c("Ondo"), ])
Ondolabel <- data.frame(state= c( "Ondo"), lon=c(5.3), lat=c(6.6))
Ekiti <- droplevels(ds[ds$STATE %in% c("Ekiti"), ])
Ekitilabel <- data.frame(state= c( "Ekiti"), lon=c(5.3), lat=c(8.1))
Osun <- droplevels(ds[ds$STATE == "Osun", ])
Osunlabel <- data.frame(state= c("Osun"), lon=c(4.2), lat=c(8.05))
Ekiti_Ondo_Osun <- droplevels(ds[ds$STATE %in% c("Ekiti", "Ondo", "Osun"), ])
Ekitil_Ondo_Osunabel <- data.frame(state= c( "Ekiti", "Ondo", "Osun"), lon=c(5.3, 5.3, 4.2), lat=c(8.1, 6.6, 8.05))
Anambra <- droplevels(ds[ds$STATE %in% c("Anambra"), ])
Anambralabel <- data.frame(state= c( "Anambra"), lon=c(7.15), lat=c(6.45))
Ebonyi <- droplevels(ds[ds$STATE %in% c("Ebonyi"), ])
Ebonyilabel <- data.frame(state= c( "Ebonyi"), lon=c(7.83), lat=c(6.67))
Enugu <- droplevels(ds[ds$STATE %in% c("Enugu"), ])
Enugulabel <- data.frame(state= c( "Enugu"), lon=c(7.1), lat=c(6.95))
Anambra_Enugu_Ebonyi <- droplevels(ds[ds$STATE %in% c("Anambra", "Enugu", "Ebonyi"), ])
Anambra_Enugu_Ebonyilabel <- data.frame(state= c( "Anambra", "Enugu", "Ebonyi"), lon=c(6.7, 7, 8.25), lat=c(5.9, 7.1, 6.9))
##############################################################################################################
## NG: mapping: for every State, maps will be made per planting month and based on user selection for ha or acre
## the LGAMaps function produces a pdf file with three maps and csn files and it saves both in the directory as set before running the function
##############################################################################################################
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/BenueCrossRiver_Acre")
for(m in month.name){
LGAMaps(plantMonth="January", cities = c("Calabar", "Makurdi"), lgaGroups = "Benue_Cross River",
LGApoints = Benue_CR, stateLabel = Benue_CRlabel, textangle=0, unit="acre", couple = "Two")
}
LGAMaps <- function(plantMonth, cities, lgaGroups, LGApoints, stateLabel, textangle, unit, couple){
plotData <- droplevels(LGApoints[LGApoints$plm == plantMonth, ])
if(couple == "Two"){
lgaGroups <- c(strsplit(lgaGroups, "_")[[1]][1], strsplit(lgaGroups, "_")[[1]][2])
}
if(couple == "Three"){
lgaGroups <- c(strsplit(lgaGroups, "_")[[1]][1], strsplit(lgaGroups, "_")[[1]][2], strsplit(lgaGroups, "_")[[1]][3])
}
plotData <- droplevels(plotData[plotData$STATE %in% lgaGroups, ])
AOI <- lgaGroups
AOIMapS <- subset(boundaryNG, NAME_1 %in% AOI )
AOIMap <- subset(ngstate, NAME_1 %in% AOI )
AOIMap <- AOIMap[,c("NAME_1", "NAME_2")]
LGAnames <- as.data.frame(AOIMap)
LGAnames <- cbind(LGAnames, coordinates(AOIMap))
colnames(LGAnames) <- c("STATE","LGA","long","lat" )
LGAnames <- LGAnames[!LGAnames$LGA %in% c("IbadanNorth-West","IbadanNorth-East","IbadanSouth-West", "IbadanSouth-East"),]
LGAnames$LGA <- gsub("Egbado /", "", LGAnames$LGA )
crop_ngstate <- subset(ngstate, NAME_1 %in% AOI )
towns <- as.data.frame(TownsNG)
towns <- towns[towns$name %in% cities & towns$fclass %in% c("town", "city"),]
crop_RiversNG <- crop(RiversNG, extent(crop_ngstate))
crop_RiversNG <- crop_RiversNG[crop_RiversNG$fclass == "river", ]
LGAaverage <- ddply(plotData, .(LGA, STATE), summarize,
LGAUrea = round(mean(rateUrea), digits=0),
LGANPK151515 = round(mean(rateNPK151515), digits=0),
LGAdY = round(mean(respY), digits=0))
dss <- LGAaverage
dss$LGAUrea <- dss$LGAUrea / 2.47105
dss$LGANPK151515 <- dss$LGANPK151515 / 2.47105
dss$LGAdY <- dss$LGAdY / 2.47105
if(unit == 'acre'){
LGAaverage <- dss
}
plotData <- merge(plotData, LGAaverage, by=c("LGA", "STATE"))
if(unit == "ha"){
plotData$Urea <- round(plotData$LGAUrea/25)*25
plotData$NPK15_15_15 <- round(plotData$LGANPK151515/50)*50
plotData$dY <- round(plotData$LGAdY/2)*2
}else{
plotData$Urea <- round(plotData$LGAUrea/10)*10
plotData$NPK15_15_15 <- round(plotData$LGANPK151515/20)*20
plotData$dY <- round(plotData$LGAdY/1)*1
}
fileNameCsv <- paste(plantMonth, "_", paste(lgaGroups, collapse="_"), ".csv", sep="")
AOIMap2 <- merge(AOIMap, unique(plotData[, c("LGA", "Urea", "NPK15_15_15","dY", "LGAdY")]),by.x="NAME_2" ,by.y="LGA")
AOIMap2$month <- plantMonth
AOIMap2 <- AOIMap2[!is.na(AOIMap2$Urea), ]
plotData$month <- plantMonth
tt <- unique(as.data.frame(plotData[, c("STATE","LGA", "Urea", "NPK15_15_15", "LGAdY", "month")]))
tt <- tt[order(tt$STATE, tt$LGA), ]
write.csv(tt, fileNameCsv, row.names = FALSE)
AOIMap3 <- st_as_sf(AOIMap2)
# Ureapalette <- brewer.pal(9,"Greens")
# colpallets <- c(mypalette[c((9-length(unique(plotData$Urea))): length(mypalette))])
if(unit == "ha"){
ureacols <- c("0" = "#FFFFFF", "25"= "#E5F5E0", "50"= "#C7E9C0", "75"= "#A1D99B", "100"= "#74C476",
"125"= "#41AB5D", "150"= "#238B45", "175"="#006D2C", "200"= "#00441B")
tt <- "Urea (kg/ha)"
}else {
ureacols <- c("0" = "#FFFFFF", "10"= "#E5F5E0", "20"= "#C7E9C0", "30"= "#A1D99B", "40"= "#74C476",
"50"= "#41AB5D", "60"= "#238B45", "70"="#006D2C", "80"= "#00441B")
tt <- "Urea (kg/acre)"
}
ureasclae <- unique(AOIMap3$Urea)
keU <- as.character(ureasclae[order(ureasclae)])
AOIMap3$Urea <- factor(AOIMap3$Urea)
levels(AOIMap3$Urea) <- keU
require(ggrepel)
ggUrea <- ggplot(AOIMap3) +
geom_sf(aes(fill=Urea), col="grey30") +
scale_fill_manual(values = ureacols, guide = guide_legend(reverse=TRUE))+
geom_path(data=crop_ngstate, aes(x=long, y=lat, group=group), size=0.5) +
geom_path(data=AOIMapS, aes(x=long, y=lat, group=group), size=1, col="darkgrey") +
#geom_text(data=LGAnames, aes(long, lat, label=LGA, fontface=1, angle=textangle), size=3) +
geom_text_repel(data=LGAnames, aes(long, lat, label=LGA, fontface=1, angle=textangle), size=3, segment.size = NA) +
geom_text(data=stateLabel, aes(lon, lat, label=state, fontface=2), col='black', size=6)+
geom_path(data=crop_RiversNG, aes(x=long, y=lat, group=group), color="dodgerblue1", size=0.3) +
geom_point(data=towns, aes(x=coords.x1, y=coords.x2), shape=16, size=3) +
annotation_scale(location = "br", width_hint = 0.3, line_width = 0.4) +
annotation_north_arrow(location = "br", which_north = "true", pad_x = unit(0.2, "in"), pad_y = unit(0.2, "in"),
style = north_arrow_fancy_orienteering) +
# annotation_north_arrow(location = "tr", which_north = "true", pad_x = unit(0.3, "in"), pad_y = unit(0.3, "in"),
# style = north_arrow_fancy_orienteering) +
# annotation_scale(location = "tr", width_hint = 0.2, line_width = 0.4) +
xlab("") + ylab("") +
ggtitle(tt) +
theme_bw() +
theme(legend.position="right", legend.title=element_blank(),
plot.title = element_text(hjust = 0.5, size=16, face ='bold'),
axis.text = element_text(size=8))
### NPK 151515 palette <- brewer.pal(9,"YlOrBr")
if(unit == "ha"){
NPKcols <- c("0"="#FFFFFF","50"= "#FFF7BC", "100"= "#FEE391", "150"= "#FEC44F", "200"= "#FE9929",
"250"= "#EC7014", "300"= "#CC4C02","350" = "#993404", "400"= "#662506")
tt <- "NPK 15-15-15 (kg/ha)"
}else{
NPKcols <- c("0"="#FFFFFF","20"= "#FFF7BC", "40"= "#FEE391", "60"= "#FEC44F", "80"= "#FE9929",
"100"= "#EC7014", "120"= "#CC4C02", "140" ="#993404","160" = "#662506")
tt <- "NPK 15-15-15 (kg/acre)"
}
mopsclae <- unique(AOIMap3$NPK15_15_15)
kev <- as.character(mopsclae[order(mopsclae)])
AOIMap3$NPK15_15_15 <- factor(AOIMap3$NPK15_15_15)
levels(AOIMap3$NPK15_15_15) <- kev
require(plotly)
ggNPK <- ggplot(AOIMap3) +
geom_sf(aes(fill=NPK15_15_15), col="grey30") +
scale_fill_manual(values = NPKcols, guide = guide_legend(reverse=TRUE))+
geom_path(data=crop_ngstate, aes(x=long, y=lat, group=group), size=0.5) +
geom_path(data=AOIMapS, aes(x=long, y=lat, group=group), size=1, col="darkgrey") +
geom_text_repel(data=LGAnames, aes(long, lat, label=LGA, fontface=1, angle=textangle), size=3, segment.size = NA) +
# geom_text(data=LGAnames, aes(long, lat, label=LGA, fontface=1, angle=textangle), size=2.5)+
#geom_text_repel(data=LGAnames, aes(long, lat, label=LGA, fontface=1, angle=textangle), size=3) +
geom_path(data=crop_RiversNG, aes(x=long, y=lat, group=group), color="dodgerblue1", size=0.3) +
geom_point(data=towns, aes(x=coords.x1, y=coords.x2), shape=16, size=3) +
xlab("") + ylab("") +
ggtitle(tt) +
theme_bw() +
theme(legend.position="right", legend.title=element_blank(),
plot.title = element_text(hjust = 0.5, size=16, face ='bold'),
axis.text = element_text(size=8))
if(unit == "ha"){
tt <- "Yield increase (t/ha)"
Ydcols <- c("21"="#FF0000FF", "20"= "#FF8B00FF", "19"= "#E8FF00FF",
"18"= "#5DFF00FF", "17"= "#00FF2EFF", "16"="#00FFB9FF", "15"= "#00B9FFFF", "14"= "#002EFFFF",
"12"= "#5D00FFFF", "11"= "#E800FFFF", "10"= "#FF008BFF", "9"= "#FFFFFF")
}else{
tt <- "Yield increase (t/acre)"
Ydcols <- c("9"="#FF0000FF", "8"= "#FF8B00FF", "7"= "#E8FF00FF",
"6"= "#5DFF00FF", "5"= "#00FF2EFF", "4"="#00FFB9FF", "3"= "#00B9FFFF", "4"= "#002EFFFF",
"3"= "#5D00FFFF", "2"= "#E800FFFF", "1"= "#FF008BFF", "0"= "#FFFFFF")
}
Ysclae <- unique(AOIMap3$dY)
keY <- as.factor(Ysclae[order(Ysclae)])
AOIMap3$dY <- factor(AOIMap3$dY)
levels(AOIMap3$dY) <- keY
ggYield <- ggplot(AOIMap3) +
geom_sf(aes(fill=dY), col="grey30") +
scale_fill_manual(values = Ydcols, guide = guide_legend(reverse=TRUE))+
geom_path(data=crop_ngstate, aes(x=long, y=lat, group=group), size=0.5) +
geom_path(data=AOIMapS, aes(x=long, y=lat, group=group), size=1, col="darkgrey") +
geom_text_repel(data=LGAnames, aes(long, lat, label=LGA, fontface=1, angle=textangle), size=3, segment.size = NA) +
#geom_text(data=LGAnames, aes(long, lat, label=LGA, fontface=1, angle=textangle), size=2.5)+
#geom_text_repel(data=LGAnames, aes(long, lat, label=LGA, fontface=1, angle=textangle), size=3) +
geom_path(data=crop_RiversNG, aes(x=long, y=lat, group=group), color="dodgerblue1", size=0.3) +
geom_point(data=towns, aes(x=coords.x1, y=coords.x2), shape=16, size=3) +
xlab("") + ylab("") +
ggtitle(tt) +
theme_bw() +
theme(legend.position="right", legend.title=element_blank(),
plot.title = element_text(hjust = 0.5, size=16, face ='bold'),
axis.text = element_text(size=8))
fileName <- paste(plantMonth, "_", paste(lgaGroups, collapse="_"), ".pdf", sep="")
pdf(fileName, onefile = TRUE, height = 14, width=12)
#pdf.options(paper = "a4")
grid.newpage()
pushViewport(viewport(layout = grid.layout(3, 2, heights = unit(c(0.8, 5, 5,0.8), "null"))))
grid.text(paste("Planting in", plantMonth, sep=" "), vp = viewport(layout.pos.row = 1, layout.pos.col = 1:2))
print(ggUrea, vp = viewport(layout.pos.row = 2, layout.pos.col = 1))
print(ggNPK, vp = viewport(layout.pos.row = 2, layout.pos.col = 2))
#print(ggMOP, vp = viewport(layout.pos.row = 3, layout.pos.col = 1))
print(ggYield, vp = viewport(layout.pos.row = 3, layout.pos.col = 1))
dev.off()
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/BenueCrossRiver_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Calabar", "Makurdi"), lgaGroups = "Benue_Cross River",
LGApoints = Benue_CR, stateLabel = Benue_CRlabel, textangle=0, unit="acre", couple = "Two")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/BenueCrossRiver")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Calabar", "Makurdi"), lgaGroups = "Benue_Cross River",
LGApoints = Benue_CR, stateLabel = Benue_CRlabel, textangle=0, unit="ha", couple = "Two")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Delta")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Asaba"), lgaGroups = "Delta",
LGApoints = Delta, stateLabel = Deltalabel, textangle=0, unit="ha", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Delta_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Asaba"), lgaGroups = "Delta",
LGApoints = Delta, stateLabel = Deltalabel, textangle=0, unit="acre", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Edo")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Benin City"), lgaGroups = "Edo",
LGApoints = Edo, stateLabel = Edolabel, textangle=0, unit="ha", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Edo_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Benin City"), lgaGroups = "Edo",
LGApoints = Edo, stateLabel = Edolabel, textangle=0, unit="acre", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Imo")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Owerri"), lgaGroups = "Imo",
LGApoints = Imo, stateLabel = Imolabel, textangle=0, unit="ha", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Imo_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Owerri"), lgaGroups = "Imo",
LGApoints = Imo, stateLabel = Imolabel, textangle=0, unit="acre", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Abia")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Umuahia"), lgaGroups = "Abia",
LGApoints = Abia, stateLabel = Abialabel, textangle=0, unit="ha", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Abia_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Umuahia"), lgaGroups = "Abia",
LGApoints = Abia, stateLabel = Abialabel, textangle=0, unit="acre", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/AkwaIbom")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Uyo"), lgaGroups = "Akwa Ibom",
LGApoints = Akwa_Ibom, stateLabel = Akwa_Ibomlabel, textangle=0, unit="ha", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/AkwaIbom_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Uyo"), lgaGroups = "Akwa Ibom",
LGApoints = Akwa_Ibom, stateLabel = Akwa_Ibomlabel, textangle=0, unit="acre", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Ekiti")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Ado Ekiti"), lgaGroups = "Ekiti",
LGApoints = Ekiti, stateLabel = Ekitilabel, textangle=0, unit="ha", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Ekiti_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Ado Ekiti"), lgaGroups = "Ekiti",
LGApoints = Ekiti, stateLabel = Ekitilabel, textangle=0, unit="acre", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Ondo")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Akure"), lgaGroups = "Ondo",
LGApoints = Ondo, stateLabel = Ondolabel, textangle=0, unit="ha", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Ondo_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Akure"), lgaGroups = "Ondo",
LGApoints = Ondo, stateLabel = Ondolabel, textangle=0, unit="acre", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Osun")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Osogbo"), lgaGroups = "Osun",
LGApoints = Osun, stateLabel = Osunlabel, textangle=0, unit="ha", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Osun_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Osogbo"), lgaGroups = "Osun",
LGApoints = Osun, stateLabel = Osunlabel, textangle=0, unit="acre", couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Anambra")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Awka"), lgaGroups = "Anambra",
LGApoints = Anambra, stateLabel = Anambralabel, textangle=0, unit="ha",couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Anambra_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Awka"), lgaGroups = "Anambra",
LGApoints = Anambra, stateLabel = Anambralabel, textangle=0, unit="acre",couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Enugu")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Enugu"), lgaGroups = "Enugu",
LGApoints = Enugu, stateLabel = Enugulabel, textangle=0, unit="ha",couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Enugu_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Enugu"), lgaGroups = "Enugu",
LGApoints = Enugu, stateLabel = Enugulabel, textangle=0, unit="acre",couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Ebonyi")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Ebonyi"), lgaGroups = "Ebonyi",
LGApoints = Ebonyi, stateLabel = Ebonyilabel, textangle=0, unit="ha",couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Ebonyi_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = c("Ebonyi"), lgaGroups = "Ebonyi",
LGApoints = Ebonyi, stateLabel = Ebonyilabel, textangle=0, unit="acre",couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Taraba")
for(m in month.name){
LGAMaps(plantMonth=m, cities = "Taraba", lgaGroups = "Taraba", LGApoints = Taraba,
stateLabel = Tarabalabel, textangle=0, unit="ha",couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Taraba_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = "Taraba", lgaGroups = "Taraba", LGApoints = Taraba,
stateLabel = Tarabalabel, textangle=0, unit="acre",couple = "One")
}
("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Kogi")
for(m in month.name){
LGAMaps(plantMonth=m, cities = "Kogi", lgaGroups = "Kogi", LGApoints = Kogi, stateLabel = Kogilabel,
textangle=0, unit="ha",couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Kogi_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = "Kogi", lgaGroups = "Kogi", LGApoints = Kogi, stateLabel = Kogilabel,
textangle=0, unit="acre",couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Kwara_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = "Kwara", lgaGroups = "Kwara", LGApoints = Kwara,
stateLabel = Kwaralabel, textangle=0, unit="acre",couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Kwara")
for(m in month.name){
LGAMaps(plantMonth=m, cities = "Kwara", lgaGroups = "Kwara", LGApoints = Kwara,
stateLabel = Kwaralabel, textangle=0, unit="ha" ,couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Oyo_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = "Oyo", lgaGroups = "Oyo", LGApoints = Oyo,
stateLabel = Oyolabel, textangle=0, unit="acre" ,couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Oyo")
for(m in month.name){
LGAMaps(plantMonth=m, cities = "Oyo", lgaGroups = "Oyo", LGApoints = Oyo,
stateLabel = Oyolabel, textangle=0, unit="ha" ,couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Ogun")
for(m in month.name){
LGAMaps(plantMonth=m, cities = "Abeokuta", lgaGroups = "Ogun", LGApoints = Ogun,
stateLabel = Ogunlabel, textangle=0, unit="ha" ,couple = "One")
}
setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/Ogun_Acre")
for(m in month.name){
LGAMaps(plantMonth=m, cities = "Abeokuta", lgaGroups = "Ogun", LGApoints = Ogun,
stateLabel = Ogunlabel, textangle=0, unit="acre" ,couple = "One")
}
##############################################################################################################
## NG: The two functions are used to convert the csv files to pdf files
##############################################################################################################
pdfTables <- function(FERTtABLE, plantMonth, unit, state){
row.names(FERTtABLE) = NULL
FERTtABLE <- subset(FERTtABLE, select=-c(month))
FERTtABLE$LGAdY <- round(FERTtABLE$LGAdY, digits=0)
# if(unit=="acre" & state == "CrossRiver_Benue"){
# colnames(FERTtABLE) <- c("LGA", "STATE","Urea \n (kg/acre)","MOP \n (kg/acre)","DAP \n (kg/acre)", "Yield increase \n (t/acre)")
# }else{
# colnames(FERTtABLE) <- c("LGA","STATE", "Urea \n (kg/ha)","MOP \n (kg/ha)","DAP \n (kg/ha)", "Yield increase \n (t/ha)")
# }
# if(unit=="acre" & state != "CrossRiver_Benue"){
# colnames(FERTtABLE) <- c("STATE","LGA", "Urea \n (kg/acre)","MOP \n (kg/acre)","DAP \n (kg/acre)", "Yield increase \n (t/acre)")
# }else if (unit=="ha" & state != "CrossRiver_Benue"){
# colnames(FERTtABLE) <- c("STATE", "LGA", "Urea \n (kg/ha)","MOP \n (kg/ha)","DAP \n (kg/ha)", "Yield increase \n (t/ha)")
# }
#
if(unit=="acre"){
colnames(FERTtABLE) <- c("STATE","LGA", "Urea \n (kg/acre)", "NPK 15-15-15 \n (kg/acre)", "Yield increase \n (t/acre)")
}else if (unit=="ha"){
colnames(FERTtABLE) <- c("STATE", "LGA", "Urea \n (kg/ha)", "NPK 15-15-15 \n (kg/ha)", "Yield increase \n (t/ha)")
}
FERTtABLE <- FERTtABLE[order(FERTtABLE$STATE, FERTtABLE$LGA), ]
if(state=="CrossRiver_Benue"){
fileNameR <- paste("Table","_", plantMonth, "_", "Benue_CrossRiver", ".pdf", sep="")
}else{
fileNameR <- paste("Table","_", plantMonth, "_", state, ".pdf", sep="")
}
pdf(fileNameR, width = 8, height = 12)
pdf.options(paper = "a4")
# if(state %in% c("Oyo", "Benue_Cross River", "Osun", "Akwa Ibom", "Imo")){
# pdf.options(paper = "a4")
# }else{
# pdf.options(paper = "a4r")
# }
#
hj <- matrix(c(0, 0, -0.5,-0.5, -0.5, -0.5), ncol=6, nrow=nrow(FERTtABLE), byrow=TRUE)
if(state %in% c("Oyo", "Benue_Cross River", "Osun")){
tt1 <- ttheme_default(core=list(fg_params=list(hjust= as.vector(hj), x=0.05, cex = 0.7)),
colhead=list(fg_params=list(hjust=0, x=0.1, cex = 0.8)),
rowhead = list(fg_params=list(cex = 0.7)))
}else{
tt1 <- ttheme_default(core=list(fg_params=list(hjust= as.vector(hj), x=0.05, cex = 0.9)),
colhead=list(fg_params=list(hjust=0, x=0.1, cex = 0.9)),
rowhead = list(fg_params=list(cex = 0.8)))
}
# hj <- matrix(c(0, 0, -0.6,-0.6, -0.9, -2.0), ncol=6, nrow=nrow(FERTtABLE), byrow=TRUE)
# tt1 <- ttheme_default(core=list(fg_params=list(hjust= as.vector(hj), x=0.05, cex = 0.9)),
# colhead=list(fg_params=list(hjust=0, x=0.1, cex = 0.9)),
# rowhead = list(fg_params=list(cex = 0.9)))
table <- tableGrob(FERTtABLE, rows = NULL, theme = tt1)
title <- textGrob(paste("Planting in ", plantMonth, sep=""), gp = gpar(fontsize = 14))
padding <- unit(0.4,"line")
table <- gtable_add_rows(
table, heights = grobHeight(title) + padding, pos = 0
)
table <- gtable_add_grob(
table, list(title),
t = 1, l = 1, r = ncol(table)
)
grid.newpage()
grid.draw(table)
dev.off()
}
tablepdf <- function(unit, fname, state){
setwd(paste("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard/FR/NG/", fname, sep=""))
listcsv <- list.files(getwd(), "csv")
library(gtable)
for(files in c(listcsv, listcsv[1])){
plantMonth <- strsplit(files, '_')[[1]][1]
csvtables <- unique(read.csv(files))
pdfTables(FERTtABLE = csvtables, plantMonth, unit=unit, state=state)
}
}
tablepdf(unit="acre", fname="BenueCrossRiver_Acre", state="Benue_Cross River")
tablepdf(unit="ha", fname="BenueCrossRiver", state="Benue_Cross River")
tablepdf(unit="acre", fname="Abia_Acre", state="Abia")
tablepdf(unit="ha", fname="Abia", state="Abia")
tablepdf(unit="acre", fname="AkwaIbom_Acre", state="Akwa Ibom")
tablepdf(unit="ha", fname="AkwaIbom", state="Akwa Ibom")
tablepdf(unit="acre", fname="Anambra_Acre", state="Anambra")
tablepdf(unit="ha", fname="Anambra", state="Anambra")
tablepdf(unit="acre", fname="Delta_Acre", state="Delta")
tablepdf(unit="ha", fname="Delta", state="Delta")
tablepdf(unit="acre", fname="Ebonyi_Acre", state="Ebonyi")
tablepdf(unit="ha", fname="Ebonyi", state="Ebonyi")
tablepdf(unit="acre", fname="Edo_Acre", state="Edo")
tablepdf(unit="ha", fname="Edo", state="Edo")
tablepdf(unit="acre", fname="Ekiti_Acre", state="Ekiti")
tablepdf(unit="ha", fname="Ekiti", state="Ekiti")
tablepdf(unit="acre", fname="Enugu_Acre", state="Enugu")
tablepdf(unit="ha", fname="Enugu", state="Enugu")
tablepdf(unit="acre", fname="Imo_Acre", state="Imo")
tablepdf(unit="ha", fname="Imo", state="Imo")
tablepdf(unit="acre", fname="Ondo_Acre", state="Ondo")
tablepdf(unit="ha", fname="Ondo", state="Ondo")
tablepdf(unit="acre", fname="Osun_Acre", state="Osun")
tablepdf(unit="ha", fname="Osun", state="Osun")
tablepdf(unit="acre", fname="Ogun_Acre", state="Ogun")
tablepdf(unit="ha", fname="Ogun", state="Ogun")
tablepdf(unit="acre", fname="Oyo_Acre", state="Oyo")
tablepdf(unit="ha", fname="Oyo", state="Oyo")
tablepdf(unit="acre", fname="Kwara_Acre", state="Kwara")
tablepdf(unit="ha", fname="Kwara", state="Kwara")
tablepdf(unit="acre", fname="Kogi_Acre", state="Kogi")
tablepdf(unit="ha", fname="Kogi", state="Kogi")
tablepdf(unit="acre", fname="Taraba_Acre", state="Taraba")
tablepdf(unit="ha", fname="Taraba", state="Taraba")
############################################################################################################################################################################################################################
############################################################################################################################################################################################################################
############################################################################################################################################################################################################################
## ## select FCY and read the corresponding file
## TZ: Subsetting for the user defined Region and selecting a coordinate to put the state name in the map
##############################################################################################################
ds_TZ <- FR_TZ_FCY2_plm ## ds will be defined based on the current yield. e.g. if user idicate that thier current yield is yield level 2 ds = FR_NG_FCY2_plm
Mara <- droplevels(ds[ds$REGION %in% c("Mara", "Simiyu"), ])
Maralabel <- data.frame(REGION= c("Mara", "Simiyu"), lon=c(34.7, 33.7), lat=c(-1.2, -3.7))
Kagera <- droplevels(ds[ds$REGION %in% c("Kagera", "Geita", "Kigoma"), ])
Kageralabel <- data.frame(REGION= c("Kagera", "Geita", "Kigoma"), lon=c(30.25, 32.4, 31), lat=c(-2.1, -4, -6.1))
Mwanza <- droplevels(ds[ds$REGION %in% c("Mwanza","Shinyanga"), ])
Mwanzalabel <- data.frame(REGION= c("Mwanza","Shinyanga"), lon=c(33.65, 33.2), lat=c(-2.1, -4.1))
Pwani <- droplevels(ds[ds$REGION %in% c("Tanga","Pwani"), ])
Pwanilabel <- data.frame(REGION= c("Tanga","Pwani"), lon=c(37.6, 37.9), lat=c(-4.8, -7.3))
Mtwara <- droplevels(ds[ds$REGION %in% c("Mtwara", "Lindi"), ])
Mtwaralabel <- data.frame(REGION= c("Mtwara", "Lindi"), lon=c(37.5, 38.7), lat=c(-11.2,-8.1))
Zanzibar <- droplevels(ds[ds$REGION %in% c("Zanzibar South and Central", "Zanzibar West", "Zanzibar North"), ])
Zanzibarlabel <- data.frame(REGION= c("Zanzibar"), lon=c(39.5), lat=c(-5.95))
Maracity <- data.frame(REGION = c("Mara", "Simiyu"),name=c("Musoma","Bariadi"), lat=c(-1.5,-2.8), lon = c(33.8, 33.98))
Kageracity <- data.frame(REGION = c("Kagera", "Geita", "Kigoma"), name=c("Bukoba","Geita","Kigoma"),
lat=c(-1.33, -2.87, -4.88), lon = c(31.82, 32.23,29.63))
Pwaniacity <- data.frame(REGION = c("Pwani", "Tanga"),name=c("Kibaha","Tanga"),
lat=c(-6.77, -5.07), lon = c(38.92, 39.01))
Mwanzacity <- data.frame(REGION = c("Mwanza", "Shinyanga"),name=c("Mwanza", "Shinyanga"),
lat=c(-2.52, -3.66), lon = c(32.9, 33.42))
Mtwaraacity <- data.frame(REGION = c("Mtwara","Lindi"),name=c("Mtwara","Lindi"),
lat=c(-10.27, -9.99), lon = c(40.18, 39.71))
Zanzibarcity <- data.frame(REGION = "Zanzibar",name="Zanzibar", lat=-6.17, lon = 39.2)
##############################################################################################################
## TZ: mapping: for every Region, maps will be made per planting month and based on user selection for ha or acre
##############################################################################################################
setwd("E:/QUEFTS/mtcGISData/Tanzania")
boundaryTZ <- readOGR(dsn=getwd(), layer="gadm36_TZA_1")
tzRegion <- readOGR(dsn=getwd(), layer="gadm36_TZA_2")
LGAMaps_TZ <- function(plantMonth, cities, lgaGroups, LGApoints, stateLabel, textangle, unit, couple){
plotData <- droplevels(LGApoints[LGApoints$plm == plantMonth, ])
if(couple == "Two"){
lgaGroups <- c(strsplit(lgaGroups, "_")[[1]][1], strsplit(lgaGroups, "_")[[1]][2])
}
if(couple == "Three"){
lgaGroups <- c(strsplit(lgaGroups, "_")[[1]][1], strsplit(lgaGroups, "_")[[1]][2], strsplit(lgaGroups, "_")[[1]][3])
}
plotData <- droplevels(plotData[plotData$REGION %in% lgaGroups, ])
AOI <- lgaGroups
AOIMapS <- subset(boundaryTZ, NAME_1 %in% AOI )
AOIMap <- subset(tzRegion, NAME_1 %in% AOI )
AOIMap <- AOIMap[,c("NAME_1", "NAME_2")]
LGAnames <- as.data.frame(AOIMap)
LGAnames <- cbind(LGAnames, coordinates(AOIMap))
colnames(LGAnames) <- c("REGION","DISTRICT","long","lat" )
crop_ngstate <- subset(tzRegion, NAME_1 %in% AOI )
## take REGION average
LGAaverage <- ddply(plotData, .(DISTRICT, REGION), summarize,
LGAUrea = round(mean(rateUrea), digits=0),
LGANPK171717 = round(mean(rateNPK171717), digits=0),
LGADAP = round(mean(rateDAP), digits=0),
LGAdY = round(mean(respY), digits=0))
dss <- LGAaverage
dss$LGAUrea <- dss$LGAUrea / 2.47105
dss$LGANPK171717 <- dss$LGANPK171717 / 2.47105
dss$LGADAP <- dss$LGADAP / 2.47105
dss$LGAdY <- dss$LGAdY / 2.47105
if(unit == 'acre'){
LGAaverage <- dss
}
plotData <- merge(plotData, LGAaverage, by=c("DISTRICT", "REGION"))
if(unit == "ha"){
plotData$Urea <- round(plotData$LGAUrea/25)*25
plotData$NPK17_17_17 <- round(plotData$LGANPK171717/50)*50
plotData$DAP <- round(plotData$LGADAP/25)*25
plotData$dY <- round(plotData$LGAdY/2)*2
}else{
plotData$Urea <- round(plotData$LGAUrea/10)*10
plotData$NPK17_17_17 <- round(plotData$LGANPK171717/20)*20
plotData$DAP <- round(plotData$LGADAP/10)*10
plotData$dY <- round(plotData$LGAdY/1)*1
}
fileNameCsv <- paste(plantMonth, "_", paste(lgaGroups, collapse="_"), ".csv", sep="")
AOIMap2 <- merge(AOIMap, unique(plotData[, c("REGION","DISTRICT", "Urea", "NPK17_17_17","DAP","dY", "LGAdY")]),
by.x=c("NAME_1","NAME_2") ,by.y=c("REGION","DISTRICT"))
AOIMap2$month <- plantMonth
AOIMap2 <- AOIMap2[!is.na(AOIMap2$Urea), ]
plotData$month <- plantMonth
tt <- unique(as.data.frame(plotData[, c("REGION","DISTRICT", "Urea", "NPK17_17_17","DAP", "LGAdY", "month")]))
tt <- tt[order(tt$REGION, tt$DISTRICT), ]
write.csv(tt, fileNameCsv, row.names = FALSE)
AOIMap3 <- st_as_sf(AOIMap2)
if(unit == "ha"){
ureacols <- c("0" = "#FFFFFF", "25"= "#E5F5E0", "50"= "#C7E9C0", "75"= "#A1D99B", "100"= "#74C476",
"125"= "#41AB5D", "150"= "#238B45", "175"="#006D2C", "200"= "#00441B")
ttz <- "Urea (kg/ha)"
}else {
ureacols <- c("0" = "#FFFFFF", "10"= "#E5F5E0", "20"= "#C7E9C0", "30"= "#A1D99B", "40"= "#74C476",
"50"= "#41AB5D", "60"= "#238B45", "70"="#006D2C", "80"= "#00441B")
ttz <- "Urea (kg/acre)"
}
ureasclae <- unique(AOIMap3$Urea)
keU <- as.character(ureasclae[order(ureasclae)])
AOIMap3$Urea <- factor(AOIMap3$Urea)
levels(AOIMap3$Urea) <- keU
require(ggrepel)
ggUrea <- ggplot(AOIMap3) +
geom_sf(aes(fill=Urea), col="darkgrey") +
scale_fill_manual(values = ureacols, guide = guide_legend(reverse=TRUE))+
geom_path(data=crop_ngstate, aes(x=long, y=lat, group=group), size=0.5) +
geom_path(data=AOIMapS, aes(x=long, y=lat, group=group), size=1, col="darkgrey") +
geom_text_repel(data=LGAnames, aes(long, lat, label=DISTRICT, fontface=1, angle=textangle), size=4, segment.size = NA) +
geom_text(data=stateLabel, aes(lon, lat, label=REGION, fontface=2), col='black', size=6)+
geom_point(data=cities, aes(x=lon, y=lat), shape=16, size=3) +
annotation_scale(location = "bl", width_hint = 0.3, line_width = 0.4) +
annotation_north_arrow(location = "bl", which_north = "true", pad_x = unit(0.2, "in"), pad_y = unit(0.2, "in"),
style = north_arrow_fancy_orienteering) +