IdePix with Landsat8: s3tbx.landsat.readAs=reflectance ignored



I’m trying to perform a classification with IdePix on Landsat 8 OLI L1C data. Using the knowledge from this forum, I adapted the file, to include the line s3tbx.landsat.readAs=reflectance. Furthermore, in my GPT call, I added the parameter -Ds3tbx.landsat.readAs=reflectance.

Unfortunately, after resetting and rebooting several times, I still get the following error message:

Error: [NodeId: IdePix] The landsat source product must provide reflectances. For configuration instructions see Idepix help documentation, Processor description for Landsat-8.

So, for completeness, this is what my file looks like, stored in $USER\.snap\etc$:

#SNAP configuration 's3tbx'
#Wed Mar 28 11:14:10 CEST 2018

And this is the GPT graph I use:

<graph id="2018-03-28 11:23:24">
  <node id="Reader">
<parameters class="com.bc.ceres.binding.dom.XppDomElement">
  <node id="IdePix">
  <sourceProduct refid="Reader"/>
<parameters class="com.bc.ceres.binding.dom.XppDomElement">
  <node id="Writer">
  <sourceProduct refid="IdePix"/>
<parameters class="com.bc.ceres.binding.dom.XppDomElement">

Does anyone have the same experience? Thank you in advance.


The problem is that you use a Landsat product which is already converted to BEAM-DIMAP. The property has only an effect if you use original L8 products.
But you can do the conversion with e.g. the Radiance-to-Reflectance operator. Then it is not exactly what is provided in the original L8 or you need to create the pre-processed product again with this property set.


Thank you for your quick answer. This is clear.
About the Radiance-to-Reflectance operator: I see it only supports OLCI, MERIS and SLSTR, not OLI (Landsat 8), or am I interpreting your suggestion wrong? :slight_smile:

I think my solution will be to perform the IdePix classification first, and then perform the preprocessing chain (which I now performed beforehand, the reason the product was already in BEAM-DIMAP.


Oh, sorry. I forgot that it is not supporting L8.
Your solution overcomes this shortcoming anyway.