README

getlandsat provides access to Landsat https://landsat.usgs.gov 8 metadata and images hosted on AWS S3 at https://registry.opendata.aws/landsat-8/. The package only fetches data. It does not attempt to aid users in downstream usage, but some additional functionality may be added.

Potential users are probably anyone from scientists asking questions about biodiversity or land use change, to software developers creating tools for users to vizualize their data.

Install

install.packages("getlandsat")

devtools::install_github("ropensci/getlandsat")

library("getlandsat")

List scenes

(res <- lsat_scenes(n_max = 10))
#> # A tibble: 10 x 11
#>    entityId     acquisitionDate     cloudCover processingLevel  path   row
#>    <chr>        <dttm>                   <dbl> <chr>           <int> <int>
#>  1 LC801011720… 2015-01-02 15:49:05      80.8  L1GT               10   117
#>  2 LC802603920… 2015-01-02 16:56:51      90.8  L1GT               26    39
#>  3 LC822707420… 2015-01-02 13:53:02      83.4  L1GT              227    74
#>  4 LC822707320… 2015-01-02 13:52:38      52.3  L1T               227    73
#>  5 LC822706220… 2015-01-02 13:48:14      38.8  L1T               227    62
#>  6 LC821111520… 2015-01-02 12:30:31      22.9  L1GT              211   115
#>  7 LC817912020… 2015-01-02 09:14:45       7.67 L1GT              179   120
#>  8 LC821111120… 2015-01-02 12:28:55      43.4  L1GT              211   111
#>  9 LC819502920… 2015-01-02 10:17:20      21.0  L1T               195    29
#> 10 LC817904520… 2015-01-02 08:44:49       1.92 L1T               179    45
#> # ... with 5 more variables: min_lat <dbl>, min_lon <dbl>, max_lat <dbl>,
#> #   max_lon <dbl>, download_url <chr>

List scene files

lsat_scene_files(x = res$download_url[1])
#>                                 file    size
#> 2   LC80101172015002LGN00_B4.TIF.ovr   7.7MB
#> 26 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

Get an image

lsat_image(x = "LC80101172015002LGN00_B5.TIF")
#> [1] "/Users/sckott/Library/Caches/landsat-pds/L8/010/117/LC80101172015002LGN00/LC80101172015002LGN00_B5.TIF"

Caching

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/sckott/Library/Caches/landsat-pds/L8/010/117/LC80101172015002LGN00/LC80101172015002LGN00_B5.TIF"

Visualize

library("raster")
x <- lsat_cache_details()[[1]]
img <- raster(x$file)
plot(img)