Get Landsat 8 Data from AWS public data sets. Includes functions for listing images and fetching them.
Dev version
devtools::install_github(c("ropensci/getlandsat"))
library("getlandsat")
(res <- lsat_scenes(n_max = 10))
#> # A tibble: 10 x 11
#> entityId acquisitionDate cloudCover processingLevel
#> <chr> <time> <dbl> <chr>
#> 1 LC80101172015002LGN00 2015-01-02 15:49:05 80.81 L1GT
#> 2 LC80260392015002LGN00 2015-01-02 16:56:51 90.84 L1GT
#> 3 LC82270742015002LGN00 2015-01-02 13:53:02 83.44 L1GT
#> 4 LC82270732015002LGN00 2015-01-02 13:52:38 52.29 L1T
#> 5 LC82270622015002LGN00 2015-01-02 13:48:14 38.85 L1T
#> 6 LC82111152015002LGN00 2015-01-02 12:30:31 22.93 L1GT
#> 7 LC81791202015002LGN00 2015-01-02 09:14:45 7.67 L1GT
#> 8 LC82111112015002LGN00 2015-01-02 12:28:55 43.43 L1GT
#> 9 LC81950292015002LGN00 2015-01-02 10:17:20 21.02 L1T
#> 10 LC81790452015002LGN00 2015-01-02 08:44:49 1.92 L1T
#> # ... with 7 more variables: path <int>, row <int>, min_lat <dbl>,
#> # min_lon <dbl>, max_lat <dbl>, max_lon <dbl>, download_url <chr>
lsat_scene_files(x = res$download_url[1])
#> file size
#> 1 LC80101172015002LGN00_B4.TIF.ovr 7.7MB
#> 2 LC80101172015002LGN00_B11.TIF.ovr 17.0KB
#> 3 LC80101172015002LGN00_B5.TIF 56.8MB
#> 4 LC80101172015002LGN00_BQA.TIF 2.7MB
#> 5 LC80101172015002LGN00_MTL.txt 7.5KB
#> 6 LC80101172015002LGN00_B5.TIF.ovr 7.8MB
#> 7 LC80101172015002LGN00_B2.TIF.ovr 7.5MB
#> 8 LC80101172015002LGN00_B1.TIF.ovr 7.5MB
#> 9 LC80101172015002LGN00_B7.TIF.ovr 7.9MB
#> 10 LC80101172015002LGN00_B4.TIF 55.4MB
#> 11 LC80101172015002LGN00_B8.TIF 212.3MB
#> 12 LC80101172015002LGN00_B3.TIF.ovr 7.6MB
#> 13 LC80101172015002LGN00_B3.TIF 54.4MB
#> 14 LC80101172015002LGN00_B2.TIF 54.0MB
#> 15 LC80101172015002LGN00_B10.TIF.ovr 17.0KB
#> 16 LC80101172015002LGN00_B6.TIF.ovr 7.9MB
#> 17 LC80101172015002LGN00_B9.TIF.ovr 7.0MB
#> 18 LC80101172015002LGN00_B11.TIF 0.1MB
#> 19 LC80101172015002LGN00_B8.TIF.ovr 29.0MB
#> 20 LC80101172015002LGN00_B1.TIF 54.2MB
#> 21 LC80101172015002LGN00_B10.TIF 0.1MB
#> 22 LC80101172015002LGN00_B6.TIF 58.0MB
#> 23 LC80101172015002LGN00_BQA.TIF.ovr 0.6MB
#> 24 LC80101172015002LGN00_B7.TIF 58.0MB
#> 25 LC80101172015002LGN00_B9.TIF 49.6MB
Returns path to the image
lsat_image(x = "LC80101172015002LGN00_B5.TIF")
#> [1] "/Users/sacmac/Library/Caches/landsat-pds/L8/010/117/LC80101172015002LGN00/LC80101172015002LGN00_B5.TIF"
Another one
lsat_image("LC80010032014272LGN00_B10.TIF")
#> [1] "/Users/sacmac/Library/Caches/landsat-pds/L8/001/003/LC80010032014272LGN00/LC80010032014272LGN00_B10.TIF"
When requesting an image, we first check if you already have that image. If you do, we return the path to the file. If not, we get the image, and return the file path.
lsat_image(x = "LC80101172015002LGN00_B5.TIF")
#> File in cache
#> [1] "/Users/sacmac/Library/Caches/landsat-pds/L8/010/117/LC80101172015002LGN00/LC80101172015002LGN00_B5.TIF"
Note the message given.
See ?lsat_cache for cache management functions.
library("raster")
x <- lsat_cache_details()
img <- raster(x[[1]]$file)
plot(img)