Dear Nikos.
After a long time I'm trying to reproduce a routine I have for doing
intercallibratrion of DMSP 1992-2012 but for some reason It doesn't work to
me. I think is because the problem between the region of the layers 30 arc
sec should resolution be from 0.008333333300000 to 0.008333333333333, i.e.
exactly 30 arc-seconds? and the computational region be the same ? I got
stuck on how to set it to work... from the side of the region setting.
However in addition my routing also has a for loop which does not work ok
as well.
I would appreciate a lot of you can give it a look and tell me how to make
it work...
Thanks a lot in advance
Kind regards,
Gabriel
#####-----------------------------------------------------------------------------------------
# complete routine for intercalliration of DSMP/OLS light stable product
import grass.script as gscript
import os
import os,glob
# get working directory
print os.getcwd()
# change working directory where raster files are
os.chdir('C:\\Users\\Gabriel\\Documents\\grassdata\\lights')
# see files in directory
ls
# import all raster files to grass --- here is a kind of problem...???
for tif_file in glob.glob("*.tif"):
new_rast = os.path.splitext(tif_file)[0]
grass.run_command("r.in.gdal", flags="a", input=tif_file,
output=new_rast)
# get info of one of the imported raster
r.info map=F121996
# run intercalliration algorithm
i.nightlights.intercalibration
image=F101992,F101993,F101994,F121994,F121995,F121996,F121997,F121998,F121999,F141997,F141998,F141999,F142000,F142001,F142002,F142003,F152000,F152001,F152002,F152003,F152004,F152005,F152006,F152007,F162004,F162005,F162006,F162007,F162008,F162009,F182010,F182011,F182012,F182013
suffix=c model=elvidge2014 -t
# correct general region adjust to raster file --- here the region is
exactly 30 arc for the raster as I could see....
g.region raster=F121996
# cerate a list of rasters in the mapset
# rastlist=grass.read_command("g.list",type="rast").split()
rasters = grass.read_command('g.list', type='raster').splitlines()
# change working directory
os.chdir('C:\\Users\\Gabriel\\Desktop\\out')
# save rasters in mapset to file
for raster in rasters:
grass.run_command('r.out.gdal', input=raster, output=raster + '.tiff',
format='GTiff')
On Wed, Aug 22, 2018 at 10:06 AM Gabriel Cotlier <gabikl...@gmail.com>
wrote:
> Dear Nikos,
>
> Thanks a lot for your answer and the orientation.
> The information and the link are very useful.
> Kind regards,
> Gabriel
>
>
> On Wed, Aug 22, 2018 at 5:19 AM Nikos Alexandris <n...@nikosalexandris.net>
> wrote:
>
>> * Gabriel Cotlier <gabikl...@gmail.com> [2018-08-21 12:00:24 -0300]:
>>
>> >Dear Nikos and GRASS users,
>> >
>> >I would like to ask if nonetheless the effect due to "stray light" the
>> >*i.landsat8.swlst* code for split window is still applicable to Landsat 8
>> >data and whether these error is specially visible on water bodies? and
>> >whether band 10 is better than band 11 in terms of correction processing
>> >for Level -1 data products?
>> >
>> >Thanks a lot.
>> >
>> >Kind regards,
>> >Gabriel
>>
>> Dear Gabriel,
>>
>> for details and references, refer to
>>
>>
>> https://landsat.gsfc.nasa.gov/landsat-8-thermal-data-ghost-free-after-stray-light-exorcism/
>>
>> Make sure you use the newest Level-1 Collection 1 Landsat 8 products.
>>
>> I use `i.landsat8.swlst` and plan to improve it further.
>>
>> However, whether to prefer a Split-Window based approach, or another
>> Single-Channel one, depends on what you want to do. Think of spatial
>> extent and coverage of various land (cover) types, temporal extent
>> and more.
>>
>> Thermal remote sensing is hard(er) also because it's hard to get
>> ground-truth data sets so as to validate LST estimations.
>>
>> Nikos
>>
>
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