Nothing
R/landsat_search.R
In rLandsat: Landsat Data Complete Download Process
# landsat search
#' Search for Landsat8 Products IDs
#' @description Search for landsat8 product IDs for a geography (country name or row/path) and a specific time duration.
#' @param min_date the start date of the products. Format should be \%Y-\%m-\%d
#' @param max_date the end date of the products. Format should be \%Y-\%m-\%d
#' @param country the country for which product ids is required. NULL if search is not on country. List of available countries are available at data(world_rowpath)
#' @param path_master vector of path numbers
#' @param row_master vector of row numbers corresponding to the path number. Check details
#' @param source search source. Default and recommended is sat-api. Available options: "sat-api", "aws", "usgs". For AWS it will return the Pre-Collection Scene IDs pre March 2017.
#'
#' @return dataframe with the product ids and the meta information (cloud cover, path/row) along with it.
#' If source is sat-api then raw value download links from all the sources (AWS, Google, ESPA) are also outputted
#'
#' @details for path_master and row_master input is in a pair. For example: If we want path/row of : (147,47) , (147,48) then path_master = c(147, 147), row_master = c(47,48)
#'
#' @export
#' @import "httr" "jsonlite" "dplyr" "readr" "stringr"
#' @examples
#' # define the start and end dates
#' start = "2017-03-11"
#' end = "2017-03-12"
#'
#' # Get for specific row and path
#' result = landsat_search(min_date=start, max_date=end, path_master=147, row_master=48)
#' \donttest{
#' # Get for entire country
#' result = landsat_search(min_date=start, max_date=end, country = "India")
#' }
#'
landsat_search <- function(min_date = "2017-03-01", max_date = Sys.Date(),
country = NULL, path_master = NULL,
row_master = NULL,source = "sat-api"){
if(source == "sat-api"){
if(!is.null(country)){
#data("world_rowpath", envir = environment(landsat_search))
country_rp = world_rowpath
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
# if country not found
if(length(c_row) == 0){
# cleaning country
country_rp$ctry_name = gsub("^Federal\\sRepublic\\sof\\s|^Republic\\sof\\s","", country_rp$ctry_name)
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
}
# if still no country found
if(length(c_row) == 0){
if(country == "All" | country == "all"){
c_row = 1:nrow(country_rp)
} else{
stop("Error: Country not found")
}
}
# final aws subset for the c
country_rp = country_rp[c_row,]
country_rp = StandardColnames(country_rp)
output = list()
k = 1
# for each path and row run the api
for(path in unique(country_rp$path)){
for(row in unique(country_rp$row[country_rp$path == path])){
result = satapilsat8(date_from = min_date, date_to = max_date, path = path, row = row)
result = GEToutput(result)
if(nrow(result)>0){
output[[k]] = result
k = k+1
}
}
}
df = bind_rows(output)
colnames(df) = gsub("results\\.","", colnames(df))
} else if(!is.null(path_master)){
# if no country, but row and path mentioned ============
row_path = data.frame(path_master, row_master)
output = list()
k = 1
# for each path and row run the api
for(path in unique(row_path$path_master)){
for(row in unique(row_path$row_master[row_path$path_master == path])){
result = satapilsat8(date_from = min_date, date_to = max_date, path = path, row = row)
result = GEToutput(result)
if(nrow(result)>0){
output[[k]] = result
k = k+1
}
}
}
df = bind_rows(output)
colnames(df) = gsub("results\\.","", colnames(df))
} else{
# if nothing mmentioned =======
all_yn = readline("Run for entire entire world? [y/n]")
if(all_yn == "y"){
result = satapilsat8(date_from = min_date, date_to = max_date, path = NULL, row = NULL)
df = GEToutput(result)
} else{
print("Please narrow your search")
}
}
return(df)
} else if(source == "usgs"){
temp = list.files(path = tempdir(), pattern = "LANDSAT_8_C1*", full.names = T)
if(length(temp) == 1){
cat("getting pre-downloaded data from usgs\n")
usgs_list <- readr::read_csv(gzfile(temp))
} else{
temp <- tempfile(pattern = "LANDSAT_8_C1")
cat("getting meta data from USGS\n")
download.file("https://landsat.usgs.gov/landsat/metadata_service/bulk_metadata_files/LANDSAT_8_C1.csv.gz", destfile = temp)
usgs_list <- readr::read_csv(gzfile(temp))
}
usgs_list$date = as.Date(usgs_list$acquisitionDate)
usgs_list = usgs_list[which(usgs_list$date >= as.Date(min_date) & usgs_list$date <= as.Date(max_date)),]
usgs_list = StandardColnames(usgs_list)
usgs_list$location_id = paste(usgs_list$path,usgs_list$row, sep = "-")
# ====== subsetting for country selected, if any ======
if(!is.null(country)){
# read file with country and row-path combination
#data("world_rowpath", envir = environment(landsat_search))
country_rp = world_rowpath
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
# if country not found
if(length(c_row) == 0){
# cleaning country
country_rp$ctry_name = gsub("^Federal\\sRepublic\\sof\\s|^Republic\\sof\\s","", country_rp$ctry_name)
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
}
# if still no country found
if(length(c_row) == 0){
if(country == "All" | country == "all"){
c_row = 1:nrow(country_rp)
} else{
stop("Error: Country not found")
}
}
# final aws subset for the c
country_rp = country_rp[c_row,]
country_rp = StandardColnames(country_rp)
country_rp$location_id = paste(country_rp$path,country_rp$row, sep = "-")
country_rp$location_id = paste(country_rp$path,country_rp$row, sep = "-")
usgs_row = which(usgs_list$location_id %in% country_rp$location_id)
if(length(usgs_row)>0){
usgs_list = usgs_list[usgs_row,]
} else {
stop("Error: No rows found")
}
} else if(!is.null(path_master) & length(row_master)>0){
row_path = paste0(path_master,"-",row_master)
# if no country selected and row_path combination input
usgs_row = which(usgs_list$location_id %in% row_path)
if(length(usgs_row)>0){
usgs_list = usgs_list[usgs_row,]
} else {
stop("Error: No rows found for given row path combination")
}
}
cat(paste("Total rows :",nrow(usgs_list), "\n"))
return(usgs_list)
}else{
if((as.Date(min_date) < as.Date("2017-03-01")) & (as.Date(max_date) < as.Date("2017-03-01"))){
# If entire data before Collection
temp = list.files(path = gsub("(.*\\/)(.*)","\\1",tempfile()), pattern = "preaws*", full.names = T)
if(length(temp) == 1){
cat("getting pre-downloaded data from aws\n")
aws_list_old <- readr::read_csv(gzfile(temp))
} else{
temp <- tempfile(pattern = "preaws")
cat("getting meta data from AWS\n")
download.file("https://landsat-pds.s3.amazonaws.com/scene_list.gz", destfile = temp)
aws_list_old <- readr::read_csv(gzfile(temp))
}
aws_list_old = aws_list_old[!duplicated(aws_list_old[,-which(names(aws_list_old) == "cloudCover")]),]
aws_list_old$date = as.Date(substr(aws_list_old$acquisitionDate, 1, 10))
aws_list = aws_list_old[which(aws_list_old$date >= as.Date(min_date) & aws_list_old$date <= as.Date(max_date)),]
aws_list = StandardColnames(aws_list)
} else if(as.Date(min_date) >= as.Date("2017-03-01")){
# If entire data after Collection
temp = list.files(path = gsub("(.*\\/)(.*)","\\1",tempfile()), pattern = "aws_c1*", full.names = T)
if(length(temp) == 1){
cat("getting pre-downloaded data from aws\n")
aws_list <- readr::read_csv(gzfile(temp))
} else{
temp <- tempfile(pattern = "aws_c1")
cat("getting meta data from AWS\n")
download.file("https://landsat-pds.s3.amazonaws.com/c1/L8/scene_list.gz", destfile = temp)
aws_list <- readr::read_csv(gzfile(temp))
}
aws_list = aws_list[!duplicated(aws_list[,-which(names(aws_list) == "cloudCover")]),]
aws_list$date = as.Date(substr(aws_list$acquisitionDate, 1, 10))
aws_list = aws_list[which(aws_list$date >= as.Date(min_date) & aws_list$date <= as.Date(max_date)),]
# ====== including tier type ======
aws_list$tier = substr(aws_list$productId, (nchar(aws_list$productId)-1) , nchar(aws_list$productId))
aws_list = StandardColnames(aws_list)
} else {
# If data both pre and post Collection
temp = list.files(path = gsub("(.*\\/)(.*)","\\1",tempfile()), pattern = "preaws*", full.names = T)
if(length(temp) == 1){
cat("getting pre-downloaded data from aws \n")
aws_list_old <- readr::read_csv(gzfile(temp))
} else{
temp <- tempfile(pattern = "preaws")
cat("getting meta data from AWS \n")
download.file("https://landsat-pds.s3.amazonaws.com/scene_list.gz", destfile = temp)
aws_list_old <- readr::read_csv(gzfile(temp))
}
aws_list_old = aws_list_old[!duplicated(aws_list_old[,-which(names(aws_list_old) == "cloudCover")]),]
aws_list_old$date = as.Date(substr(aws_list_old$acquisitionDate, 1, 10))
aws_list_old = aws_list_old[which(aws_list_old$date >= as.Date(min_date) & aws_list_old$date <= as.Date(max_date)),]
aws_list_old = StandardColnames(aws_list_old)
temp = list.files(path = gsub("(.*\\/)(.*)","\\1",tempfile()), pattern = "aws_c1*", full.names = T)
if(length(temp) == 1){
cat("getting pre-downloaded data from aws\n")
aws_list <- readr::read_csv(gzfile(temp))
} else{
temp <- tempfile(pattern = "aws_c1")
cat("getting meta data from AWS\n")
download.file("https://landsat-pds.s3.amazonaws.com/c1/L8/scene_list.gz", destfile = temp)
aws_list <- readr::read_csv(gzfile(temp))
}
aws_list = aws_list[!duplicated(aws_list[,-which(names(aws_list) == "cloudCover")]),]
aws_list$date = as.Date(substr(aws_list$acquisitionDate, 1, 10))
aws_list = aws_list[which(aws_list$date >= as.Date(min_date) & aws_list$date <= as.Date(max_date)),]
# ====== including tier type ======
aws_list$tier = substr(aws_list$productId, (nchar(aws_list$productId)-1) , nchar(aws_list$productId))
aws_list = StandardColnames(aws_list)
# ===== merging old and new data =======
aws_list = bind_rows(aws_list, aws_list_old)
}
aws_list$location_id = paste(aws_list$path,aws_list$row, sep = "-")
# ====== subsetting for country selected, if any ======
if(!is.null(country)){
# read file with country and row-path combination
#data("world_rowpath", envir = environment(landsat_search))
country_rp = world_rowpath
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
# if country not found
if(length(c_row) == 0){
# cleaning country
country_rp$ctry_name = gsub("^Federal\\sRepublic\\sof\\s|^Republic\\sof\\s","", country_rp$ctry_name)
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
}
# if still no country found
if(length(c_row) == 0){
if(country == "All" | country == "all"){
c_row = 1:nrow(country_rp)
} else{
stop("Error: Country not found")
}
}
# final aws subset for the c
country_rp = country_rp[c_row,]
country_rp = StandardColnames(country_rp)
country_rp$location_id = paste(country_rp$path,country_rp$row, sep = "-")
aws_row = which(aws_list$location_id %in% country_rp$location_id)
if(length(aws_row)>0){
aws_list = aws_list[aws_row,]
} else {
stop("Error: No rows found")
}
} else if(!is.null(path_master) & length(row_master)>0){
row_path = paste0(path_master,"-",row_master)
# if no country selected and row_path combination input
aws_row = which(aws_list$location_id %in% row_path)
if(length(aws_row)>0){
aws_list = aws_list[aws_row,]
} else {
stop("Error: No rows found for given row path combination")
}
}
cat(paste("Total rows :",nrow(aws_list), "\n"))
return(aws_list)
}
}
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# landsat search
#' Search for Landsat8 Products IDs
#' @description Search for landsat8 product IDs for a geography (country name or row/path) and a specific time duration.
#' @param min_date the start date of the products. Format should be \%Y-\%m-\%d
#' @param max_date the end date of the products. Format should be \%Y-\%m-\%d
#' @param country the country for which product ids is required. NULL if search is not on country. List of available countries are available at data(world_rowpath)
#' @param path_master vector of path numbers
#' @param row_master vector of row numbers corresponding to the path number. Check details
#' @param source search source. Default and recommended is sat-api. Available options: "sat-api", "aws", "usgs". For AWS it will return the Pre-Collection Scene IDs pre March 2017.
#'
#' @return dataframe with the product ids and the meta information (cloud cover, path/row) along with it.
#' If source is sat-api then raw value download links from all the sources (AWS, Google, ESPA) are also outputted
#'
#' @details for path_master and row_master input is in a pair. For example: If we want path/row of : (147,47) , (147,48) then path_master = c(147, 147), row_master = c(47,48)
#'
#' @export
#' @import "httr" "jsonlite" "dplyr" "readr" "stringr"
#' @examples
#' # define the start and end dates
#' start = "2017-03-11"
#' end = "2017-03-12"
#'
#' # Get for specific row and path
#' result = landsat_search(min_date=start, max_date=end, path_master=147, row_master=48)
#' \donttest{
#' # Get for entire country
#' result = landsat_search(min_date=start, max_date=end, country = "India")
#' }
#'
landsat_search <- function(min_date = "2017-03-01", max_date = Sys.Date(),
country = NULL, path_master = NULL,
row_master = NULL,source = "sat-api"){
if(source == "sat-api"){
if(!is.null(country)){
#data("world_rowpath", envir = environment(landsat_search))
country_rp = world_rowpath
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
# if country not found
if(length(c_row) == 0){
# cleaning country
country_rp$ctry_name = gsub("^Federal\\sRepublic\\sof\\s|^Republic\\sof\\s","", country_rp$ctry_name)
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
}
# if still no country found
if(length(c_row) == 0){
if(country == "All" | country == "all"){
c_row = 1:nrow(country_rp)
} else{
stop("Error: Country not found")
}
}
# final aws subset for the c
country_rp = country_rp[c_row,]
country_rp = StandardColnames(country_rp)
output = list()
k = 1
# for each path and row run the api
for(path in unique(country_rp$path)){
for(row in unique(country_rp$row[country_rp$path == path])){
result = satapilsat8(date_from = min_date, date_to = max_date, path = path, row = row)
result = GEToutput(result)
if(nrow(result)>0){
output[[k]] = result
k = k+1
}
}
}
df = bind_rows(output)
colnames(df) = gsub("results\\.","", colnames(df))
} else if(!is.null(path_master)){
# if no country, but row and path mentioned ============
row_path = data.frame(path_master, row_master)
output = list()
k = 1
# for each path and row run the api
for(path in unique(row_path$path_master)){
for(row in unique(row_path$row_master[row_path$path_master == path])){
result = satapilsat8(date_from = min_date, date_to = max_date, path = path, row = row)
result = GEToutput(result)
if(nrow(result)>0){
output[[k]] = result
k = k+1
}
}
}
df = bind_rows(output)
colnames(df) = gsub("results\\.","", colnames(df))
} else{
# if nothing mmentioned =======
all_yn = readline("Run for entire entire world? [y/n]")
if(all_yn == "y"){
result = satapilsat8(date_from = min_date, date_to = max_date, path = NULL, row = NULL)
df = GEToutput(result)
} else{
print("Please narrow your search")
}
}
return(df)
} else if(source == "usgs"){
temp = list.files(path = tempdir(), pattern = "LANDSAT_8_C1*", full.names = T)
if(length(temp) == 1){
cat("getting pre-downloaded data from usgs\n")
usgs_list <- readr::read_csv(gzfile(temp))
} else{
temp <- tempfile(pattern = "LANDSAT_8_C1")
cat("getting meta data from USGS\n")
download.file("https://landsat.usgs.gov/landsat/metadata_service/bulk_metadata_files/LANDSAT_8_C1.csv.gz", destfile = temp)
usgs_list <- readr::read_csv(gzfile(temp))
}
usgs_list$date = as.Date(usgs_list$acquisitionDate)
usgs_list = usgs_list[which(usgs_list$date >= as.Date(min_date) & usgs_list$date <= as.Date(max_date)),]
usgs_list = StandardColnames(usgs_list)
usgs_list$location_id = paste(usgs_list$path,usgs_list$row, sep = "-")
# ====== subsetting for country selected, if any ======
if(!is.null(country)){
# read file with country and row-path combination
#data("world_rowpath", envir = environment(landsat_search))
country_rp = world_rowpath
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
# if country not found
if(length(c_row) == 0){
# cleaning country
country_rp$ctry_name = gsub("^Federal\\sRepublic\\sof\\s|^Republic\\sof\\s","", country_rp$ctry_name)
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
}
# if still no country found
if(length(c_row) == 0){
if(country == "All" | country == "all"){
c_row = 1:nrow(country_rp)
} else{
stop("Error: Country not found")
}
}
# final aws subset for the c
country_rp = country_rp[c_row,]
country_rp = StandardColnames(country_rp)
country_rp$location_id = paste(country_rp$path,country_rp$row, sep = "-")
country_rp$location_id = paste(country_rp$path,country_rp$row, sep = "-")
usgs_row = which(usgs_list$location_id %in% country_rp$location_id)
if(length(usgs_row)>0){
usgs_list = usgs_list[usgs_row,]
} else {
stop("Error: No rows found")
}
} else if(!is.null(path_master) & length(row_master)>0){
row_path = paste0(path_master,"-",row_master)
# if no country selected and row_path combination input
usgs_row = which(usgs_list$location_id %in% row_path)
if(length(usgs_row)>0){
usgs_list = usgs_list[usgs_row,]
} else {
stop("Error: No rows found for given row path combination")
}
}
cat(paste("Total rows :",nrow(usgs_list), "\n"))
return(usgs_list)
}else{
if((as.Date(min_date) < as.Date("2017-03-01")) & (as.Date(max_date) < as.Date("2017-03-01"))){
# If entire data before Collection
temp = list.files(path = gsub("(.*\\/)(.*)","\\1",tempfile()), pattern = "preaws*", full.names = T)
if(length(temp) == 1){
cat("getting pre-downloaded data from aws\n")
aws_list_old <- readr::read_csv(gzfile(temp))
} else{
temp <- tempfile(pattern = "preaws")
cat("getting meta data from AWS\n")
download.file("https://landsat-pds.s3.amazonaws.com/scene_list.gz", destfile = temp)
aws_list_old <- readr::read_csv(gzfile(temp))
}
aws_list_old = aws_list_old[!duplicated(aws_list_old[,-which(names(aws_list_old) == "cloudCover")]),]
aws_list_old$date = as.Date(substr(aws_list_old$acquisitionDate, 1, 10))
aws_list = aws_list_old[which(aws_list_old$date >= as.Date(min_date) & aws_list_old$date <= as.Date(max_date)),]
aws_list = StandardColnames(aws_list)
} else if(as.Date(min_date) >= as.Date("2017-03-01")){
# If entire data after Collection
temp = list.files(path = gsub("(.*\\/)(.*)","\\1",tempfile()), pattern = "aws_c1*", full.names = T)
if(length(temp) == 1){
cat("getting pre-downloaded data from aws\n")
aws_list <- readr::read_csv(gzfile(temp))
} else{
temp <- tempfile(pattern = "aws_c1")
cat("getting meta data from AWS\n")
download.file("https://landsat-pds.s3.amazonaws.com/c1/L8/scene_list.gz", destfile = temp)
aws_list <- readr::read_csv(gzfile(temp))
}
aws_list = aws_list[!duplicated(aws_list[,-which(names(aws_list) == "cloudCover")]),]
aws_list$date = as.Date(substr(aws_list$acquisitionDate, 1, 10))
aws_list = aws_list[which(aws_list$date >= as.Date(min_date) & aws_list$date <= as.Date(max_date)),]
# ====== including tier type ======
aws_list$tier = substr(aws_list$productId, (nchar(aws_list$productId)-1) , nchar(aws_list$productId))
aws_list = StandardColnames(aws_list)
} else {
# If data both pre and post Collection
temp = list.files(path = gsub("(.*\\/)(.*)","\\1",tempfile()), pattern = "preaws*", full.names = T)
if(length(temp) == 1){
cat("getting pre-downloaded data from aws \n")
aws_list_old <- readr::read_csv(gzfile(temp))
} else{
temp <- tempfile(pattern = "preaws")
cat("getting meta data from AWS \n")
download.file("https://landsat-pds.s3.amazonaws.com/scene_list.gz", destfile = temp)
aws_list_old <- readr::read_csv(gzfile(temp))
}
aws_list_old = aws_list_old[!duplicated(aws_list_old[,-which(names(aws_list_old) == "cloudCover")]),]
aws_list_old$date = as.Date(substr(aws_list_old$acquisitionDate, 1, 10))
aws_list_old = aws_list_old[which(aws_list_old$date >= as.Date(min_date) & aws_list_old$date <= as.Date(max_date)),]
aws_list_old = StandardColnames(aws_list_old)
temp = list.files(path = gsub("(.*\\/)(.*)","\\1",tempfile()), pattern = "aws_c1*", full.names = T)
if(length(temp) == 1){
cat("getting pre-downloaded data from aws\n")
aws_list <- readr::read_csv(gzfile(temp))
} else{
temp <- tempfile(pattern = "aws_c1")
cat("getting meta data from AWS\n")
download.file("https://landsat-pds.s3.amazonaws.com/c1/L8/scene_list.gz", destfile = temp)
aws_list <- readr::read_csv(gzfile(temp))
}
aws_list = aws_list[!duplicated(aws_list[,-which(names(aws_list) == "cloudCover")]),]
aws_list$date = as.Date(substr(aws_list$acquisitionDate, 1, 10))
aws_list = aws_list[which(aws_list$date >= as.Date(min_date) & aws_list$date <= as.Date(max_date)),]
# ====== including tier type ======
aws_list$tier = substr(aws_list$productId, (nchar(aws_list$productId)-1) , nchar(aws_list$productId))
aws_list = StandardColnames(aws_list)
# ===== merging old and new data =======
aws_list = bind_rows(aws_list, aws_list_old)
}
aws_list$location_id = paste(aws_list$path,aws_list$row, sep = "-")
# ====== subsetting for country selected, if any ======
if(!is.null(country)){
# read file with country and row-path combination
#data("world_rowpath", envir = environment(landsat_search))
country_rp = world_rowpath
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
# if country not found
if(length(c_row) == 0){
# cleaning country
country_rp$ctry_name = gsub("^Federal\\sRepublic\\sof\\s|^Republic\\sof\\s","", country_rp$ctry_name)
c_row = which(stringr::str_to_lower(country_rp$ctry_name) %in% stringr::str_to_lower(country))
}
# if still no country found
if(length(c_row) == 0){
if(country == "All" | country == "all"){
c_row = 1:nrow(country_rp)
} else{
stop("Error: Country not found")
}
}
# final aws subset for the c
country_rp = country_rp[c_row,]
country_rp = StandardColnames(country_rp)
country_rp$location_id = paste(country_rp$path,country_rp$row, sep = "-")
aws_row = which(aws_list$location_id %in% country_rp$location_id)
if(length(aws_row)>0){
aws_list = aws_list[aws_row,]
} else {
stop("Error: No rows found")
}
} else if(!is.null(path_master) & length(row_master)>0){
row_path = paste0(path_master,"-",row_master)
# if no country selected and row_path combination input
aws_row = which(aws_list$location_id %in% row_path)
if(length(aws_row)>0){
aws_list = aws_list[aws_row,]
} else {
stop("Error: No rows found for given row path combination")
}
}
cat(paste("Total rows :",nrow(aws_list), "\n"))
return(aws_list)
}
}
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