Read Sentinel-2 bands into R retrieves high values

Question

When I directly read into R the jp2 band files I get unusual high values compared to when I read the files in SNAP (version 9). To read the bands into R I use terra package (you can also use raster package) and the values range from 0 to 18000 more or less. I was wondering if SNAP is doing some conversion that I am not aware of to show values that range from 0 to 0.15 more or less.

> r_10
class       : SpatRaster 
dimensions  : 10980, 10980, 4  (nrow, ncol, nlyr)
resolution  : 10, 10  (x, y)
extent      : 499980, 609780, 6690240, 6800040  (xmin, xmax, ymin, ymax)
coord. ref. : WGS 84 / UTM zone 32N (EPSG:32632) 
sources     : T32VNN_20181018T105031_B02_10m.jp2  
              T32VNN_20181018T105031_B03_10m.jp2  
              T32VNN_20181018T105031_B04_10m.jp2  
              ... and 1 more source(s)
names       : B02_10m_m10_2018, B03_10m_m10_2018, B04_10m_m10_2018, B08_10m_m10_2018 
min values  :                0,                0,                0,                0 
max values  :            18815,            17880,            17023,            15608 
>

I have tried to export the bands from SNAP into TIF to see if it is a problem of format but it takes forever. I was hoping that there is a convesion factor to show the actual values that I need for my analysis.

score 1 · Accepted Answer · answered Sep 09 '22 at 12:34

SNAP applies a scaling factor of 1.0E4 so that values can be stored more efficiently as integers. You will need to either divide the values by this scaling factor in R, or else use the scaled units to benefit from more efficient integer arithmetic. See https://step.esa.int/docs/tutorials/Exporting%20data%20from%20SNAP.pdf for more details

score 0 · Answer 2 · answered Sep 22 '22 at 17:33

0

Legacy formats ([Geo]TIFF, JPEG) have incomplete metadata support. You may lose missing value codes, offset and scale factors, processing history, etc. NetCDF4-CF has good metadata support for applications that actually use what is available. The R terra package can import NetCDF4-CF format, but is selective about what metadata are imported. For the files I have tested, missing data, scale, and offset values are used by the rast() function, but other metadata are lost.

answered Sep 22 '22 at 17:33

George

146
2

Other (relevant) meta-data such as? – Robert Hijmans Sep 22 '22 at 21:51
Units, long and short variable names, georeference data, processing history. When I transfer data to “clients” all this saves time and reduces the number of questions requiring email exchanges. – George Sep 24 '22 at 00:30
I think these are all captured except for processing history. – Robert Hijmans Sep 24 '22 at 01:20

score 0 · Answer 3 · answered Sep 23 '22 at 00:53

With terra you can also set a scale/offset if you want:

library(terra)
#terra 1.6.21
f <- system.file("ex/elev.tif", package="terra")
r <- rast(f)
r
#class       : SpatRaster 
#dimensions  : 90, 95, 1  (nrow, ncol, nlyr)
#resolution  : 0.008333333, 0.008333333  (x, y)
#extent      : 5.741667, 6.533333, 49.44167, 50.19167  (xmin, xmax, ymin, ymax)
#coord. ref. : lon/lat WGS 84 (EPSG:4326) 
#source      : elev.tif 
#name        : elevation 
#min value   :       141 
#max value   :       547 

scoff(r) <- cbind(10, 0)
r
#class       : SpatRaster 
#dimensions  : 90, 95, 1  (nrow, ncol, nlyr)
#resolution  : 0.008333333, 0.008333333  (x, y)
#extent      : 5.741667, 6.533333, 49.44167, 50.19167  (xmin, xmax, ymin, ymax)
#coord. ref. : lon/lat WGS 84 (EPSG:4326) 
#source      : elev.tif 
#name        : elevation 
#min value   :      1410 
#max value   :      5470

Essentially this is way to delay the evaluation of value * scale + offset, but now it may need to be done multiple times (each time that r is used), so it is not something I would generally recommend doing.

Read Sentinel-2 bands into R retrieves high values

3 Answers3