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Weight of evidence

paulbonnard

Hello everybody,

I am working on a project where we are using weight of evidence and i have to implement it on python.

I have some question but not about the implementation, maye i am not in the right place, but if someone knows about woe and want to answer to my question it will be very helpful for me.

Thank you !

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JoeBorgione

I'm not a statistician and just now learned how to spell WOE, but I found this:

woe function | R Documentation

paulbonnard

Hi Joe,

To set up quickly my project, i am studying the possibilities of landslide on a given area.

In this area we have several variables like lithology or slope, and in each variable we have several classes, for example for slope we can have in degrees 0-5, 5-15, 15-30 ect wich are 3 different classes of slope

In fact if we read the document you sent me or wikipedia or wathever, if i understood correctly we can have a woe (wich means a posterior probability) only if we have a landslide.

we have

so if (class i inter landslide) = 0 we have post prob = 0 and by definition woe = 0

however :

here there is no landslide but we have a post prob ..

Do you have any idea why ?

cdanielvarons_0-1718753230187.png

DanPatterson_Retired

Showing the code and your reference would be useful if you are wanting to check to see whether your implementation is correct and/or optimized.

paulbonnard

In fact this is not a problem with the implementation but maybe a problem of comprehension.

I dont understand why the posterior probability isnt equal to zero whereas there is not landslide in this area.

Here is my code, in fact i want to get the same array i sent a post ago

import numpy as np
import rasterio
#import math
import csv
import os
from itertools import product

def raster_to_numpy(fileraster):
   with rasterio.open(fileraster) as src:
      if src.meta['nodata'] == None:
         print("Warnings : Attention, valeur nodata non renseignée dans le fichier entrée")
         array = src.read(1, masked=True)
         nodata = np.array(array.fill_value, dtype=array.dtype)
         array = array.filled()
      else:
         array = src.read(1)
         meta = src.meta
         meta = meta.values()
         nodata = meta[-1]
   return array,nodata
def variable(raster,nodata):
   variable = list(np.unique(raster))
      if (nodata in variable):
         variable = np.delete(variable,variable.index(nodata))
   return variable
FileDossierRaster = r"C:\Users\user\Desktop\Boulot\Dossier charge"
fileglissement = r"C:\Users\user\Desktop\Boulot\landslides_tests\ASCII\scarp_rb.asc"
fileout = r"C:\Users\user\Desktop\Boulot\Fichiers_csv\sdmuc1.csv"
def attributes(FileDossierRaster,fileglissement,fileout):
   liste_raster = []
   liste_nodata = []
   liste_var = []
   for i in os.listdir(FileDossierRaster):
      if not os.path.isdir(i):
         new_path = os.path.join(FileDossierRaster,i)
         raster_var,nodata = raster_to_numpy(new_path)
         liste_raster.append(raster_var)
         liste_nodata.append(nodata)

         v_ras = variable(raster_var,nodata)
         liste_var.append(v_ras)

   raster_gli,nodata_gli = raster_to_numpy(fileglissement)

   taille = [len(i) for i in liste_var]
   n = np.prod(taille)
   valeurs = np.zeros((n,11+len(liste_raster)))
   combi = list(product(*liste_var)) ## ici je fais les combinaisons

   for i in range(n):
      valeurs[i,0] = i+1
      valeurs[i,1:len(combi[0])+1] = combi ## ici je les mets dans mon tableau
      t = 1
      for k in range(len(liste_raster)):
         t *= np.where(liste_raster == valeurs[i,k+1],1,0) ## possibilé erreur au dernier
         c = np.count_nonzero(t == 1)
         g = np.where(raster_gli == 1,1,0)
         s = np.count_nonzero(t*g == 1)
      valeurs[i,len(combi[0])+1] = c
      valeurs[i,len(combi[0])+2] = s
###########writing csv file#################
   entete = ['numero']
   for i in range(len(liste_var)):
      v = 'variable' + str(i)
      entete.append(v)

entete = entete + ['intersection','Cellules_affectees','Proba_posteriori','c','d','e','f','g']
   with open(fileout,'w') as f:
      w = csv.writer(f, delimiter = ';')
      w.writerow(entete)
      for line in          zip(valeurs[:,0],valeurs[:,1],valeurs[:,2],valeurs[:,3],valeurs[:,4],valeurs[:,5],valeurs[:,6],valeurs[:,7]):
      w.writerow(line)
#######################################
attributes(FileDossierRaster,fileglissement,fileout)

DanPatterson_Retired

Paul... your column WOE 10**(-15.ish) is about zero. Are you expecting actual 0.0?

AbdelhakEl-fengour1

Hello Paul,

I would appreciate if you could provide me me WofE extension for ArcView, i have been looking for it for a while. my email (elfengourabdo@gmail.com). Thank you in advance.

ParthipanS

Hi Everyone,

I'm working on Landslide susceptibility mapping wherein I've planned to use the Weight of evidence. the independent variables that I am using are slope. aspect, LULC, distance from the road, geology, geomorphology, etc I wanted to know what are the tools that I can use for WofE and how to calculate WofE for the above-mentioned variables. kindly, help me to solve this issue. I deeply appreciate your help and consideration

ParthipanS

Parthipan S‌

can you help me to solve WofE?

paulbonnard

Hello,

If you used to work with python i've made a program that Can calcul wofe or a particular variable (landslide for exemple) with different raster as input.

Pm me and i will send you the code

ParthipanS

His Sir,

Thanks for the response. Yeah, I would like to use landslide

areas as dependent variable and slope, aspect, distance from lineaments,

geology and geomorphology as independent variables. can you send me the

python code it will be very helpful ?

Yours Faithfully,

S. Parthipan,

M.Tech, Geoinformatics,

Department of Geography,

University of Madras, Guindy

Chennai-600025.

Ph: 9585445673

ParthipanS

Hi,

Thanks for the response. Yeah, can you send me the code? I've considered the Landside points as dependent variable and slope, aspect, distance from the road, geology, geomorphology as the independent variable. kindly help me to solve this issue it will be very helpful

paulbonnard

Okay,

Give me your Email and i will send you the code.

Bonnard Paul

NeilFordyce

Sorry it's taken years to reply to this but I am just getting back to WOFE after a break. I was involved in WOFE with ArcVIEW in the mid 1990's and then with ArcMAP in the early 2000's.

To understand WOFE read Graeme Bonham-Carters' book "GIS for Geoscientists". The code examples are very easy to follow. Also Graeme's early papers.

For other easy to understand papers look for papers by Gary L. Raines.

For more recent work than Gary's look for papers by Vesa Nykanen from Geological Survey of Finland (GTK).

Vesa has done a lot of this sort of work and worked with Gary Raines.

Search for Mark Mihalasky and WOFE to find some other papers e.g. WOFE modelling sediment hosted gold deposits. Mark's PhD is a good read for the basics of WOFE.

GTK has released code for WOFE for ArcGIS PRO. See https://github.com/gtkfi/ArcSDM

Older "versions" of the Spatial Data Modeller for ArcGIS 10 can be found at https://www.ige.unicamp.br/sdm/

The logic for WOFE is very robust and it is relatively easy to program. What is difficult is manipulating the and finding appropriate data sets and understanding the contrast curves etc.

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