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Computer code for the study "An Automated Method for Mapping Geomorphological Expressions of Former Subglacial Meltwater Pathways (Hummock Corridors) From High Resolution Digital Elevation Data
Geomorphology"
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This archive contains the MATLAB code and a test digital elevation model (DEM) tile associated with the numerical method put forward in the following article:

Lewington, E.L.M. Livingstone, S.J. Sole, A.J. Clark, C.D. Ng, F.S. (2019) An Automated Method for Mapping Geomorphological Expressions of Former Subglacial Meltwater Pathways (Hummock Corridors) From High Resolution Digital Elevation Data. Geomorphology. 

The archive includes:
- Identify_and_Map_HCs.m: script for the automatic identification and mapping method identified in section 3 of the paper
- filt2.m: MATLAB script for filt2 (written by Chad A. Greene of the University of Texas Institute for Geophysics) 
- Example_DEM.tif: an example DEM geotiff file for testing the code (a single 5m resolution ArcticDEM tile freely available at: https://www.pgc.umn.edu/data/arcticdem - tile used here: "25_14_1_2_5m_v2.0_reg_dem.tif")

Note that Identify_and_Map_HCs.m also includes parts of https://uk.mathworks.com/matlabcentral/answers/uploaded_files/35626/farthest_points.m contributed by Image Analyst to MATLAB central file exchange. 

See the paper for more detail.

License for the data: ArcticDEM data is an unlicensed product and may be used, distributed, and modified without permission.
License for the code: MIT open source license (https://opensource.org/licenses/MIT)


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Quick-start guide
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PREPARE AND INPUT DATA

Ensure that the following files are all stored together in the same folder:

- "Identify_and_Map_HCs.m"
- "filt2.m"
- "Example_DEM.tif"




To run the default code in MATLAB using our example DEM tile, simply double click on “Identify_and_Map_HCs.m” in the file directory to open the code and press the 'Run' button



Alternatively, to check that the data has been loaded correctly, run the first section (delineated by %%) of the code and type:

			

					>> figure; imagesc(dem)



While the code will run automatically using the default parameter values, there are some variables in each section which can be altered depending on the desired use of the code (and may need updating if using on a different dataset):

(A) FILTER TO ISOLATE HUMMOCKS BY SIZE 

res = x; 							 	x sets the resolution of the dataset being processed
lamda = [x1 x2]; 	 					 	x1 and x2 set the size range of features to be retained (40 - 150 m for individual hummocks) 
dilated_Im = imdilate(NaN_Mask, strel('disk', x));			x controls the size of the NaN patches to remove any edge effects 
NaN_Buffer = imdilate(dilated_Im, strel('disk', x));			x controls the width of the buffer extracted from around the NaN patches used to calculate the local mean 

dem_scaled = imresize(input2, x);					x determines the resolution of the data 

(B) FILTER TO REMOVE MISALIGNED FEATURES

dAngle =((Width)/x);						 	x determines the width of the wedge shape filter (i.e. how much variation is acceptable)


(C) IMAGE SEGMENTATION 

smoothing_filter = fspecial('average', x); 			 	x controls the degree of smoothing prior to segmentation

Segmented_Image = bwareafilt(Segmented_Image, [x inf]); 		x sets the minimum area of pixels allowed 

Hummock_Corridors = Final_Mask > x; 				 	x sets the minimum elongation ratio allowed 



SAVE THE OUTPUT

Outputs (figures 1, 2 and 3 and a geotiff of the mapped hummock corridors) are saved automatically in the same folder as the code
Each tile is saved as a geotiff(.tiff) with the same original file name, but with '_Identified_HCs' added to the end
The geotiff files can be imported and directly opened in a GIS
We recommend mosaic-ing multiple tiles into one raster to map landforms over a continuous area (the test sites in the paper contain 12, 12 and 9 tiles respectively mosaic-ed into a single geotiff for further analysis).