วีดีโอ

it would be great without background music.

This Master of such beutiful creations deserves a lot of coffees, please consider to donate!

thanks for the great tutorial Milos I'm 100% new to R While testing some 3d cover map R code, I notice my C: HD filling up with large tiff files ([subst] Estimated disk space needed without compression: 181GB. Available: 89 GB.) What would be the process to "move" all generated files to a different drive or Dropbox?

Hello Sir how can we have your book

Great tutorial 💯

Based 🤑

Unfortunately, rgeoboundaries was removed from CRAN at the end of November. Please run this chunk to install it from the GitHub repo instead: install.packages("remotes") remotes::install_github("wmgeolab/rgeoboundaries")

Hi guys, does anyone here had problems to install rgeoboundaries? It get the "ERROR: lazy loading failed". I tried different ways and couldn't.

Where did the option of setting working directory go?

can i do it in python?

Hi Milos, can you help me with this error? rgee::ee_check() Error en strsplit(a, "[.-]"): argumento de tipo no-carácter I can not pass from here and I do not find the solution. i already updated reticulate and rgee packages. Thanks for your time!

Thank you for sharing your knowledge Milos, do you think it would be possible to do this analysis for land use and land cover data in Brazil? like TerraClass data.

Absolutely loved this

I am new with R, can you suggest platforms to run R? I try setup on colab notebook but it isn't work

Wow, rgeoboundaries was removed from CRAN after I published this tutorial. You can still download it from the GitHub repo using this code: install.packages("remotes") remotes::install_github("wmgeolab/rgeoboundaries")

Please share the way how to install rgeoboundaries

hello pls help! i cant get the terminal to work, when i click r terminal it gives me ...\bin .exe does not exist TT how do i make it exist (im completely new to coding and stuff)

Hi i am new to this, please i am having problems with installing "rgeoboundaries" as it's saying it's not available for the version of R (4.4.1), any help would be greatly appreciated

Great Milos

how did you add your libraries as mine is not coming up. thanks

Hay no 2024!!!

Add the coordinates

Thank you so much for sharing this valuable knowlege with us, if I end up using this in my research paper I'll send you the map I'll come up with

here in windows, I solved the issue with languageserversetup::languageserver_install() by adding WMIC. Error in languageserversetup::languageserver_install() : The command ‘wmic process where processid=16780 get commandline’ cannot run successfully. You can do to same so solve it by this guide: Open Settings: Press Windows + I to open the Settings app. Navigate to Optional Features: Go to System > Optional features. Add an Optional Feature: Click on Add an optional feature. Search for WMIC: In the search box, type WMIC and check the box next to it. Install: Click Next and then Install Once done, get back Rgui / open Rgui again and try to run it languageserversetup::languageserver_install()

Hi Milos. Thanks for your work, it's awesome. All ok until i run ee_check, then this appears: rgee::ee_check() ◉ Python version ✔ [Ok] C:/.........example............... Error en strsplit(a, "[.-]"): argumento de tipo no-carácter

Can this do a Lake basin area that covers several countries?

> country_land_cover <- terra::crop( + land_cover_raster, + country_sf, + snap = "in", + mask = TRUE, + overwrite=TRUE + ) Error: [crop] cannot create dataset

Thanks! :)

Thank you

best tutorial on youtube!! thanks so much, had wasted time on like 3 other videos

Ireland be like ⬜️->⬛️

Using your code at line 82 I get error - Error: unable to find an inherited method for function ‘varnames’ for signature ‘x = "NULL"’ I cant figure out why. Thanks for the videos

👏👏👏👏

104M RAM is a lot. What is your recommended approach to ovecome this limit?

Luxembourg :🗿

Thank you for video. When i calculate covariates_ls, I get a error below "Error: ! unable to find an inherited method for function 'varnames' for signature 'x = "NULL"' Hide Traceback x 1. \-KrigR::CovariateSetup(...) 2. \-terra::varnames(Covariates) 3. \-methods (local) `<fn>`(`<list>`, `<stndrdGn>`, `<env>`) How can i solve the problem?

Is there any way of obtaining a free API key for the ggmap r package?

Great job!! And useful! About the data source, I am working on municipalities of Catalonia (Spain) and, by empirical observation, I have the impression that forest data coming from Landsat are more accurate than those from Sentinel 2 (you made a tutorial on it one year ago)... May be?

great video! as a agriculture background I want to see you creating some remote sensed based map which related to agriculture. There is lot of data on CDS. But sometime the data bot fetched. Hope you can provide a solution and a great video on like vegetation index, leaf area index and more.

Great stuff as usual! Can you suggest which resources are being most used by R and rayshader? I checked, and they don’t have GPU support, so should I get more RAM or CPU power for faster output? As always, I love watching your videos. You’re making things accessible to people, and the impact you’re having is amazing. I always appreciate people who make things easier for others.

Awesome video! thanks a lot for it. As a suggestion for a new video/project: I'd be super interested in calculating the urban heat island effect from remote sensing data :)

Great one!

Thank u for this insightful tutorial! Im having an issue with rayrender when adding roads to the 3d map, it says that the attribute "render_path" doesn't exist, do u have any idea how to solve this or if there s any alternative to use ?

Hi, thanks for the video. i'm new to mapping using R thanks to you, i tried replicating with your processes but i am stuck somewhere. here is my code # libraries we need libs <- c( "tidyverse", "stringr", "httr", "sf", "giscoR", "scales", "ggrepel", "rnaturalearth", "rnaturalearthdata" ) # install missing libraries installed_libs <- libs %in% rownames(installed.packages()) if (any(installed_libs == F)) { install.packages(libs[!installed_libs]) } # load libraries invisible(lapply(libs, library, character.only = T)) ### 1) DATA WRANGLING ### ----------------- file_name <- "geonames-population-1000.csv" ### get Geonames table on places with population >= 1000 get_geonames_data <- function() { table_link <- "public.opendatasoft.com/api/explore/v2.1/catalog/datasets/geonames-all-cities-with-a-population-1000/exports/csv?lang=en&timezone=Africa%2FLagos&use_labels=true&delimiter=%3B" res <- httr::GET( table_link, write_disk(file_name), progress() ) } get_geonames_data() ### load the table load_geonames_data <- function() { places_df <- read.csv(file_name, sep = ";") return(places_df) } places_df <- load_geonames_data() # Inspect data head(places_df) names(places_df) places_modified_df <- places_df[, c(2, 7, 14, 20)] # select town name, country code, population and coordinates names(places_modified_df) <- c("name", "country_code", "pop", "coords") # rename columns places_modified_df[c("lat", "long")] <- stringr::str_split_fixed( places_modified_df$coords, ",", 2 ) places_clean_df <- places_modified_df |> dplyr::select(-coords) # define longlat projection crsLONGLAT <- "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0" # transform data frame into sf object places_sf <- places_clean_df |> sf::st_as_sf( coords = c("long", "lat"), crs = crsLONGLAT ) ### 2) GET NIGERIA SHAPEFILE ### ----------------------- # Try primary method using giscoR tryCatch({ ng <- giscoR::gisco_get_countries( resolution = "1", country = "NGA" ) |> sf::st_transform(crsLONGLAT) print("Successfully retrieved Nigeria shapefile using giscoR") }, error = function(e) { # Fallback to rnaturalearth if giscoR fails print(paste("giscoR error:", e$message)) print("Trying alternate method with rnaturalearth...") ng <- ne_countries(scale = "medium", country = "Nigeria", returnclass = "sf") |> sf::st_transform(crsLONGLAT) }) ### 3) POINTS WITHIN POLYGON ### ----------------------- # points within polygon with sf ng_places <- sf::st_intersection(places_sf, ng) ### 4) PREPARE LABELED PLACES ### ------------------------ ng_labeled_places <- ng_places |> dplyr::mutate( long = unlist(map(geometry, 1)), lat = unlist(map(geometry, 2)) ) |> dplyr::select( name, long, lat, pop ) |> sf::st_drop_geometry() |> as.data.frame() |> dplyr::arrange(desc(pop)) ### 5) CREATE FINAL MAP ### ------------------ final_map <- ggplot() + # Add country boundary geom_sf( data = ng, color = "grey20", fill = "transparent" ) + # Add population points geom_sf( data = ng_places, aes(size = pop), color = "#7d1d53", fill = "#7d1d53", alpha = .5 ) + # Scale point sizes scale_size( range = c(1, 15), breaks = scales::pretty_breaks(n = 6) ) + # Add labels for top 10 cities ggrepel::geom_text_repel( data = ng_labeled_places[1:10, ], mapping = aes(x = long, y = lat, label = name), colour = "grey20", fontface = "bold", size = 4 ) + # Theme customization theme_minimal() + theme( axis.line = element_blank(), axis.text.x = element_blank(), axis.text.y = element_blank(), axis.ticks = element_blank(), axis.title.x = element_blank(), axis.title.y = element_blank(), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), plot.margin = unit( c(t = 0, r = 0, b = 0, l = 0), "lines" ), plot.background = element_rect(fill = "white", color = NA), panel.background = element_rect(fill = "white", color = NA), legend.background = element_rect(fill = "white", color = NA), panel.border = element_blank() ) # Display the final map print(final_map) # Optionally save the map ggsave("nigeria_population_map.png", final_map, width = 12, height = 10, dpi = 300)

Can it be done for small area

great videos as always Milos, anyway I have a question, what if I had a very big area of scope (e.g.: Indonesia) with multiple tiles, is there a way to save/render/process such a big map? I always encounter the memory allocation problem :(

Thanks a lot for this tutorial Milos, very helpful! I have just a small question about an information I may have missed: how can I remove the shadow in the final image?