How to draw spatial maps in R using ggmap without Google API key? | IMD | StatswithR | Arnab Hazra скачать в хорошем качестве

How to draw spatial maps in R using ggmap without Google API key? | IMD | StatswithR | Arnab Hazra

Here we explain how to get freely gridded rainfall data from India Meteorological Department and how to generate presentation or publication-quality spatial rainfall map across the study domain (India, here) in R/R-studio using ggmap without using Google API key. The codes for the steps explained in the video are as follows. Copy and paste them into R, run them one-by-one and try to understand what each argument is doing. #datascience #datavisualization #visualization #ggplot2 #tidyverse #terrain #mapping #spatial #statistics #spatial #covariates #India #precipitation #rainfall #rcoding #GoogleAPIkey #IMD #IMDPune #griddedrainfall Data link: https://www.imdpune.gov.in/Clim_Pred_... library(ncdf4) fname = "_Clim_Pred_LRF_New_RF25_IMD0p252020.nc" ncin = nc_open(fname) prec = ncvar_get(ncin) nc_close(ncin) dim(prec) prec.total = apply(prec, 2, rowSums) dim(prec.total) S = as.matrix(expand.grid(ncin$dim$LONGITUDE$vals, ncin$dim$LATITUDE$vals)) Y = c(prec.total) / 10 library(ggmap) keep = which(!is.na(Y)) S = S[keep, ] Y = Y[keep] data = data.frame(lon = S[ , 1], lat = S[ , 2], value = Y) colnames(data) = c("Longitude", "Latitude", "Rainfall") head(data) indbox = make_bbox(lon = c(min(S[ , 1]), max(S[ , 1])), lat = c(max(S[ , 2]), min(S[ , 2])), f = .1) ind = get_map(location = indbox, zoom = 5, maptype = "terrain") p = ggmap(ind) ggsave(p, filename = "ggplot_ind1.pdf", height = 8.5, width = 8) data = data.frame(lon = S[ , 1], lat = S[ , 2], value = Y) p = ggmap(ind) + geom_tile(data, mapping = aes(x = lon, y = lat, fill = value)) ggsave(p, filename = "ggplot_ind2.pdf", height = 8, width = 8) p = ggmap(ind) + geom_tile(data, mapping = aes(x = lon, y = lat, fill = value), width = 0.27, height = 0.27) ggsave(p, filename = "ggplot_ind3.pdf", height = 8, width = 8) p0 = ggmap(ind) + geom_tile(data, mapping = aes(x = lon, y = lat, fill = value), width = 0.27, height = 0.27) + xlab("Longitude") + ylab("Latitude") + ggtitle("Annual precipitation (2020)") + theme(plot.title = element_text(hjust = 0.5, size=25), axis.text=element_text(size=20), axis.title=element_text(size=20)) ggsave(p0, filename = "ggplot_ind4.pdf", height = 8, width = 8) library(grDevices) p = p0 + scale_fill_gradientn(colours = topo.colors(30)) ggsave(p, filename = "ggplot_ind5.pdf", height = 8, width = 8) p1 = p0 + scale_fill_gradientn(colours = topo.colors(30), name = "Rainfall (cm)") + theme(legend.key.size = unit(0.3, "in"), legend.text = element_text(size=15), legend.title = element_text(size=15), legend.position = c(0.8, 0.2)) ggsave(p1, filename = "ggplot_ind6.pdf", height = 8, width = 8) baseData = map_data("world") p = p1 + geom_path(data=baseData, aes(x=long, y=lat, group=group), colour="black") ggsave(p, filename = "ggplot_ind7.pdf", height = 8, width = 8)