Skip to contents

Download Land Cover or NDVI Data from ESA WorldCover or Sentinel-2 10m Land Use/Land Cover Time Series

Source: R/core.R
get_esa_wc.Rd

Download 11-class land cover or 3-band NDVI data from the ESA WorldCover 10m Annual Dataset (NDVI p90, NDVI p50, NDVI p10), or 9-class annual land use/land cover (LULC) maps from the Sentinel-2 10m Land Use/Land Cover Time Series produced by Impact Observatory, accessed via Microsoft Planetary Computer. Users can define an area of interest using a bounding box or place name.

Usage

get_esa_wc(
  bbox = NULL,
  place = NULL,
  datatype = "landcover",
  year = 2021,
  mask = TRUE,
  quiet = TRUE
)

Arguments

bbox

sf, sfc, or a numeric vector (xmin, ymin, xmax, ymax) defining the area of interest. Optional if place is provided.

place

character or vector. (optional) A single line address, e.g. ("1600 Pennsylvania Ave NW, Washington") or a vector of addresses (c("Madrid", "Barcelona")).

datatype

character. One of "landcover", "ndvi", or "lulc". "landcover" and "ndvi" retrieve ESA WorldCover data (years 2020–2021). "lulc" retrieves the Sentinel-2 10m LULC Time Series (years 2017–2024).

year

numeric. The year of interest. For "landcover" and "ndvi": 2020 or 2021 (default 2021). For "lulc": an integer from 2017 to 2024.

mask

logical (optional). Default is TRUE. If TRUE, masks the raster data using the given bbox or place.

quiet

logical. Whether show progress bars for some process.

Value

A SpatRaster object. For "landcover": 11-class ESA WorldCover land cover map. For "ndvi": NDVI yearly percentile composite (NDVI p90, NDVI p50, NDVI p10). For "lulc": 9-class Sentinel-2 annual land use/land cover classification (layer named "LULC").

Details

The "lulc" datatype retrieves the Impact Observatory Sentinel-2 10m Land Use/Land Cover Time Series from the public AWS open data bucket (s3://io-10m-annual-lulc, no authentication required). New annual maps are released each January, so coverage currently extends to 2024. The 9 classes are: 1 = Water, 2 = Trees, 4 = Flooded vegetation, 5 = Crops, 7 = Built area, 8 = Bare ground, 9 = Snow/ice, 10 = Clouds, 11 = Rangeland.

References

Zanaga, D., Van De Kerchove, R., De Keersmaecker, W., Souverijns, N., Brockmann, C., Quast, R., Wevers, J., Grosu, A., Paccini, A., Vergnaud, S., Cartus, O., Santoro, M., Fritz, S., Georgieva, I., Lesiv, M., Carter, S., Herold, M., Li, L., Tsendbazar, N.-E., … Arino, O. (2021). ESA WorldCover 10 m 2020 v100 (Version v100). Zenodo. https://doi.org/10.5281/zenodo.5571936

Zanaga, D., Van De Kerchove, R., Daems, D., De Keersmaecker, W., Brockmann, C., Kirches, G., Wevers, J., Cartus, O., Santoro, M., Fritz, S., Lesiv, M., Herold, M., Tsendbazar, N.-E., Xu, P., Ramoino, F., & Arino, O. (2022). ESA WorldCover 10 m 2021 v200 (Version v200). Zenodo. https://doi.org/10.5281/zenodo.7254221

Karra, K., Kontgis, C., Statman-Weil, Z., Mazzariello, J. C., Mathis, M., & Brumby, S. P. (2021). Global land use / land cover with Sentinel-2 and deep learning. IGARSS 2021. https://doi.org/10.1109/IGARSS47720.2021.9553499

Examples

# \donttest{
# ESA WorldCover land cover
result <- get_esa_wc(
  place = 'New York',
  datatype = 'landcover',
  year = 2021
)
#> ℹ Start downloading land cover data ...
#> ✔ Finished downloading data
#> ℹ Masking and cropping data ...
#> 
|---------|---------|---------|---------|
=========================================
                                          

|---------|---------|---------|---------|
=========================================
                                          

#> ✔ Data successfully processed.
#> ✔ Completed. Time taken: 34 seconds.

# Sentinel-2 10m LULC Time Series
result <- get_esa_wc(
  place = 'New York',
  datatype = 'lulc',
  year = 2022
)
#> ℹ Searching for Sentinel-2 LULC tiles ...
#> ℹ Downloading 1 Sentinel-2 LULC tile(s) ...
#> ✔ Finished downloading data
#> 
|---------|---------|---------|---------|
=========================================
                                          

#> ℹ Masking and cropping data ...
#> 
|---------|---------|---------|---------|
=========================================
                                          

|---------|---------|---------|---------|
=========================================
                                          

#> ✔ Data successfully processed.
#> ✔ Completed. Time taken: 22 minutes.
# }