Extracting the central strip from LANDSAT 7 imagery

Extracting the central strip from LANDSAT 7 imagery

February 8, 2016

Here is a simple Python code to extract the central strip from Landsat 7 imagery (SLC-off),  that is not affected by the SLC failure. The algorithm shrinks the striping zones through a morphological filter (erosion) and creates a new shapefile AOI that extracts the desired raster extent without striping effects. The code is based on Python for ArcGIS (arcpy) – so you require a ArcGIS license.

General steps:

  1. Loop through all Landsat 7 data folders
  2. Stack bands for each image
  3. Create a mask
  4. Erode the mask by 20 pixels
  5. Convert the mask to polygon
  6. Create a minimum bounding box
  7. Clip the original raster through the bbox

 

import arcpy
from arcpy.sa import *

import sys,os

#  Environment settings (Activate Spatial Analyst, Overwrite Outputs allowed and TIFF compression is LZW)
arcpy.CheckOutExtension("spatial")
arcpy.env.overwriteOutput = True
arcpy.env.compression = 'LZW'

# this is your main directory with all unzipped Landsat datasets
 rootdir = "D:\\DATA\\Landsat7\\"

# create scratch folder "temp" 
temp = "D:\\DATA\\temp\\"

# loop through directory with all unzipped Landsat 7 folders
 for files in os.listdir(rootdir):   
    files = os.path.join(rootdir, files)   
    
    # for each loop the subdir "files" is now the current workspace 
    # (e.g. LE71520322015157-SC20160224113319) that contains the Landsat bands
    arcpy.env.workspace = files  
    rasters = arcpy.ListRasters("*", "TIF")  
    
    # create empty array
    stack_liste = []  
    # loop through all rasters in subdir
    for raster in rasters:   

        image = arcpy.Raster(raster) 
        name  = image.name 
        index = name.split("_")[0]  

        # fill up the array only with the actual spectral bands        
        sr = "_sr_band"  
        if sr in raster:   
            stack_liste.append(raster)             

    # now stack all bands within the array
    stack_name = files + "\\" + index + "_stack.tif"    
    arcpy.CompositeBands_management(stack_liste, stack_name)  

    # convert the image stack to a mask by logical operation with an absurd value that will result in an output "0"
    con = EqualTo(stack_name, 123456789)  

    # now shrink the raster mask with value "0" by 20 pixels
    shrink = temp + "shrink"  
    shrinking = Shrink(con, 20, 0) 
    shrinking.save(shrink)  

    zone = temp + "zone.shp" 
    bbox = temp + "bbox.shp"  

    # conver the shrunk mask to polygon and create a minimum bounding box
    arcpy.RasterToPolygon_conversion(shrink, zone, "NO_SIMPLIFY", "VALUE") 
    arcpy.MinimumBoundingGeometry_management(zone, bbox, "RECTANGLE_BY_WIDTH", "NONE")  

    # now use that bounding box as a mask to cut out the central nadir strip from the original stack
    # Final result 
    extract = files + "\\" + index + "_aoi.tif"  
    ExtractByMask = arcpy.sa.ExtractByMask(stack_name, bbox) 
    ExtractByMask.save(extract)

 

you may also like:

Our research site and project covered by BR

Our research site and project covered by BR

The University forest at Sailershausen is a unique forest owned by the University of Wuerzburg. It comes with a high diversity of trees and most important is part of various research projects. We conducted various UAS/UAV/drone flights with Lidar, multispectral and...

Meeting of the FluBig Project Team

Meeting of the FluBig Project Team

During the last two days, the team of the FluBig project (remote-sensing.org/new-dfg-project-on-fluvial-research/) met at the EORC for discussing the ongoing work on fluvial biogeomorphology. After returning from a successful field expedition to Kyrgyzstan a couple of...

‘Super Test Site Würzburg’ project meeting

‘Super Test Site Würzburg’ project meeting

After the successful "Super Test Site Würzburg" measurement campaign in June (please see here: https://remote-sensing.org/super-test-site-wurzburg-from-the-idea-to-realization/ ), the core team from the University of Würzburg, the Karlsruhe Institute of Technology,...

EORC Talk: Geolingual Studies: A New Research Direction

EORC Talk: Geolingual Studies: A New Research Direction

On July 19th, Lisa Lehnen and Richard Lemoine Rodríguez, two postdoctoral researchers of the Geolingual Studies project, gave an inspiring presentation at the EORC talk series.   In the talk titled "Geolingual Studies – a new research direction", they...

EO support for UrbanPArt field work

EO support for UrbanPArt field work

From May to September, Karla Wenner, a PhD student at the Juniorprofessorship for Applied Biodiversity Science, will be sampling urban green spaces and semi-natural grasslands in Würzburg as part of the UrbanPArt project. Our cargo bikes support the research project...

Cinematic drone shots

Cinematic drone shots

We spend quite some time in the field conducting field work, from lidar measurements to vegetation samples in order to correlate it with remote sensing data to answer various research questions concerning global change. Field work is always a 24/7 work load and...