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Remote Sensing: Georeferencing

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Remote Sensing: Georeferencing

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Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data.
Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link.
Finally, the georeferenced raster file can be exported for further usage.

THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.

Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data.
Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link.
Finally, the georeferenced raster file can be exported for further usage.

THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.

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Remote Sensing: Georeferencing

  1. 1. KAMLESH KUMAR
  2. 2. Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data. Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link. Finally, the georeferenced raster file can be exported for further usage. Source: ArcMap
  3. 3. 1. Run the app. Right click on the image list on the content tab to add an image. Go to Open Raster Layer. (Ctrl+O) 2. Browse the file and load it. Load both the images adjacent to each other. STEPS
  4. 4. As you can see the resolution (1;1) of panchromatic image on the right is better and crispier than the multi-spectral left one.
  5. 5. Notice that the first image has no resolution and has not been georeferenced.
  6. 6. 3. Go to Multispectral after the image has been loaded and click on Control Points. 4. Select Polynomial in Set Geometric Model dialogue box.
  7. 7. 5. Another window of Multipoint Geometric Correction would appear with a dialog box of techniques to choose from for the process, select Image layer and click OKAY. 6. Set an image layer as reference layer for the process. In this Case which would be the georeferenced LANDSAT Image.
  8. 8. 7. Set the Polynomial Model Properties to 1 in this case. And minimize it for the time being.
  9. 9. 8. Mark the GCP points and rectify them by clicking/ moving on the generate GCP icon. Resample Icon
  10. 10. 9. After all the required points have been marked (at least 4 for Polynomial 1), click on the Resample icon to the second last of the icon row on the top. Tick on the Ignore Zero in Stats. And export the image.
  11. 11. 10. Load the new image on the Landsat image which was georeferenced within the same 2D view panel. Go to Home and click Swipe. NOTE: You could save the reference point and export the polynomial settings for further usage.
  12. 12. Move along the Swipe Transition Extent bar to view the accuracy.
  13. 13. The swift transition shows the accuracy of the georeferencing.
  14. 14. Similarly, Polynomial 2 can be set by increasing the GCPs to at least 6 and changing the polynomial settings to 2.
  15. 15. The difference in the colour shading and representation is due to the different sensors.
  16. 16. Signing off..

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