topic Re: Skewness of values from 10 raster images in ArcGIS Spatial Analyst Questions

Skewness of values from 10 raster images

Deepa — Tue, 26 Jan 2021 16:24:25 GMT

Hi,

I am using ArcMap 10.8 version. I have 10 raster files with different data ranging from 0 to 1 for the same study area. I am interested to study how the data from 10 raster files are distributed in each pixel.

I want to calculate the skewness of the data in each pixels.

How can this be done in ArcMap?

Thank you!

Re: Skewness of values from 10 raster images

DanPatterson — Tue, 26 Jan 2021 17:37:08 GMT

Local statistics Cell Statistics (Spatial Analyst)—ArcGIS Pro | Documentation

can easily give you mean, median and standard deviation.

How difficult the next step would be would depend on which measure of skewness you wanted

Skewness - Wikipedia

Pearson's second skewness coefficient might suffice

Re: Skewness of values from 10 raster images

DanPatterson — Tue, 26 Jan 2021 18:43:45 GMT

better solution,

get your multilayer raster out to a numpy array (RasterToNumPyArray), then use scipy's skew function

a = np.random.random_sample((10, 4, 3)) # 10 layer/band raster with 4 cols 3 rows from scipy.stats import skew sk_a = skew(a, axis=0) # Calculate skewness over axis 0 ie local statistic a0 = a[:, 0, 0] # upper left corner over 10 layers sk_a0 = skew(a0) # check the skewness for the upper left over the 10 layers sk_a array([[-0.55202903, 0.9026473 , -0.22097936], [ 0.05148204, -0.6512716 , 0.16846484], [ 0.93081464, 0.00802005, 0.04495503], [-0.37445255, 0.18772049, -0.10078703]]) sk_a0 # confirm axis 0 calculation -0.5520290295549968

Re: Skewness of values from 10 raster images

DanPatterson — Tue, 26 Jan 2021 23:30:13 GMT

@Deepa

FYI

You can also bring the results back in. In this example, I created a 10 "band" raster in NumPy and brought it back into ArcGIS Pro

And you can bring it back to numpy

b = arcpy.RasterToNumPyArray(pth) b.shape (10, 10, 10) (a == b).all(-1) # ---- equality check, to make sure input and outputs are equal array([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]])

Re: Skewness of values from 10 raster images

NawajishNoman — Wed, 31 Mar 2021 23:34:47 GMT

Hi Deepa,
If I understand your inputs and analysis objective correctly, you can do this easily using the following workflow. You don't need to create numpy arrays or use any other python package.
Please make sure to use the correct formula for calculating skewness in the map algebra expression below.
Thanks
Noman
Nawajish Noman, PhD
Sr. Principal Product Engineer, Product Engineering Lead
Esri, Redlands, CA.

Calculating Pearson's second skewness coefficient (median skewness)

Input: 10 single band rasters or 1 multiband raster with 10 bands

Steps (using Spatial Analyst tools and operators)

Run CellStatistics 3 times to create mean, median, and standard deviation outputs as cs_mean, cs_median, cs_stddev respectively.
Execute the following map algebra expression in Raster Calculator or in Python using arcpy.sa molule.

out_skewness = 3 * (cs_mean – cs_median) / cs_stddev