many thanks Guillaume , 
see my code below ...
The number of the channels are good ? if yes , i don't see my error
see you 
Michel 

otbcli_ConcatenateImages.bat -il LAND*.TIF -out 
alldates2014_avignon_landsat.TIF uint16

for f in LAND*.TIF; do  otbcli_RadiometricIndices.bat -channels.blue 2 
-channels.green 3 -channels.red 4 -channels.nir 5 -in "$f" -out "NDVI_$f" 
-list Vegetation:NDVI; done

*(good number ???) *
otbcli_ConcatenateImages.bat -il NDVI*.TIF  -out 
alldates2014_avignon_landsat_nvdi.TIF uint16
otbcli_ConcatenateImages.bat -il alldates2014_avignon_landsat.TIF 
alldates2014_avignon_landsat_nvdi.TIF  -out 
alldates2014_avignon_landsat_bandes_et_nvdi.TIF uint16 

otbcli_PolygonClassStatistics.bat -in alldates2014_avignon_landsat.tif -vec 
training_range_rpg.shp -field "code" -out test.xml


otbcli_SampleSelection.bat -in alldates2014_avignon_landsat.tif -field code 
-vec training_range_rpg.shp  -out training_samples.sqlite -instats test.xml 
-strategy smallest

otbcli_SampleExtraction.bat -in alldates2014_avignon_landsat.tif  -vec 
training_samples.sqlite -outfield prefix -outfield.prefix.name band_ -field 
code

otbcli_SampleExtraction.bat -in alldates2014_avignon_landsat_nvdi.TIF  -vec 
training_samples.sqlite -outfield prefix -outfield.prefix.name ndvi_ -field 
code

for i in $(seq 1 7); do var=date$i; otbcli_TrainVectorClassifier.bat -io.vd 
training_samples.sqlite -cfield code -classifier rf -classifier.rf.max 20 
-io.out model.rf -feat ${bands}  | grep Kappa; done OK  

for i in $(seq 1 7); do var=date$i; otbcli_TrainVectorClassifier.bat -io.vd 
training_samples.sqlite -cfield code -classifier rf -classifier.rf.max 20 
-io.out model.rf -feat ${bands} ${ndvi} | grep Kappa; done --* pas de NDVI  
!!!!*
pas de ndvi 





Le mercredi 9 novembre 2016 15:17:40 UTC+1, Guillaume Pasero a écrit :
>
> Hi,
>
> When you want to perform the training, the "feat" parameter should be fed 
> with field names from training_samples.sqlite on which you want to train.
>
> In your pipeline, you should concatenate your NDVI images into one stack ( 
> otbcli_ConcatenateImages) then use this stack to extract the samples values 
> (otbcli_SampleExtraction).
>
> Regards,
>
> Guillaume
>
> On 11/09/2016 11:08 AM, michel M wrote:
>
>
> hello , 
>
> I have a little question I have 7 images (7 months) Landsat 8 (for a year)
>
> i use this fonction 
> for f in LAND*.TIF; do  otbcli_RadiometricIndices.bat -channels.blue 2 
> -channels.green 3 -channels.red 4 -channels.nir 5 -in "$f" -out "NDVI_$f" 
> -list Vegetation:NDVI; done 
> after i do 
>
> ndvi=`for i in $(seq 0 6); do printf "ndvi_$i "; done` 
> and 
>
>
> otbcli_TrainVectorClassifier.bat -io.vd training_samples.sqlite -cfield 
> code -classifier rf -classifier.rf.max 20 -io.out model.rf -feat ${ndvi} 
> and i have
>
> 2016 Nov 09 11:04:36  :  Application.logger  (INFO) Precision of class 
> [28] vs all: 0.0697674
> 2016 Nov 09 11:04:36  :  Application.logger  (INFO) Recall of class    
> [28] vs all: 1
> 2016 Nov 09 11:04:36  :  Application.logger  (INFO) F-score of class   
> [28] vs all: 0.130435
> 2016 Nov 09 11:04:36  :  Application.logger  (INFO) Global performance, 
> Kappa index: 0
>
> there is no vegetation very strange ????
>
> is there the good numbers of channels ?
>
> many thanks
>
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