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Comment appliquer le modèle kriging sur des données sans autocorrélation

RosialineMarques_Roedel

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Donc, je viens de terminer ma formation sur la réalisation d'une interpolation spatiale en utilisant Arcgis, mais lorsque j'ai commencé à travailler avec mes propres données, j'ai des problèmes, car mes données ne remplissent pas les bonnes hypothèses pour appliquer le modèle kriging.....<\/P>

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Je viens de lire dans mes livres que ce type de données nécessite l'application du modèle kriging, que puis-je faire ? Les données que je souhaite interpoler sont jointes.<\/P><\/BODY><\/HTML>

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Accepted answers

JorgeRuiz-Valdepena

Dear Rosialine,

I was able to download your Excel spreadsheet; then, converted into a Geodatabase table. When I opened the table in ArcMap, I noticed that the spatial component is missing.

All of these records need to be associated with a point stored in the SHAPE field; as you can see the SHAPE field is missing. Normally, the standard approach when storing your spatial data in an Excel Spreadsheet, you will add two fields "Latitude" and "Longitude" or "X" and "Y' coordinates from which you can create the points. Once that you have the points you can explore them with Kriging.

Let me know if you need more assistance.

Cheers

Chao

Jorge

Jorge Ruiz-Valdepeña | ArcGIS Professional Instructor, CTT+

Esri | 380 New York St | Redlands, CA 92373 | USA

T 909 793 2853 x1708 | M 951 313 8116 | jruiz-valdepena@esri.com | esri.com

THE SCIENCE OF WHERE

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DanPatterson_Retired

can you elaborate on your data? Do note, that not all data can be interpolated and have meaning. There is nothing wrong with that. There is something wrong, however, if an inappropriate technique is applied to data that it shouldn't

JorgeRuiz-Valdepena

Dear Rosialine,

I was able to download your Excel spreadsheet; then, converted into a Geodatabase table. When I opened the table in ArcMap, I noticed that the spatial component is missing.

Let me know if you need more assistance.

Cheers

Chao

Jorge

Jorge Ruiz-Valdepeña | ArcGIS Professional Instructor, CTT+

Esri | 380 New York St | Redlands, CA 92373 | USA

T 909 793 2853 x1708 | M 951 313 8116 | jruiz-valdepena@esri.com | esri.com

THE SCIENCE OF WHERE

JorgeRuiz-Valdepena

Dear Rosialine,

Based on your question, here is a workflow to run Kriging with not autocorrelationated data.

Using Kriging

A quick tour of Using Kriging http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=Using kriging

The Excel Spreadsheet does not have point locations, just attributes. You mentioned that your data is not autocorrelated.

Without points, it will be impossible to run Kriging on this data; however, if you create a Feature Class of random points and join your attributes, you could execute Kriging to interpolate a surface using your attributes.

Do not forget that Krigings first check is to look if there is a correlation in the input data

Missing information: The point features, the Projected Coordinate System, and the Spatial Extent of the study area.

Step 1: Create a geodatabase table from your Excel file.

Create a File Geodatabase and make it the default.

Open ArcMap.

Open the Search Window; then, click on Tools tab.

In the input field, enter Excel and select excel to table (Data Management) tool.

Click on the tool blue link.

In the Input Excel File browse to the location of your Excel file and add it.

For Output Table Browse to your default geodatabase and name it Tetracloreto_TAB.

Click OK.

Open your new Tetracloreto_TAB table to verify that all the attributes are there.

Step 2: Create a point Feature Class with random points.

Open the Search Window and clear previous search.

Enter create random and select create random points (Data Management).

Click on tool blue link.

For Output Location verify that your default geodatabase is selected.

Enter Tetracloreto_FC as the name of your new Output Point Feature Class.

Skip the next two parameters.

For Number of Points [value or field] (optional) enter 142 (number of records in your table).

For Minimum Allowed Distance [value or field] (optional) enter 5.

Click OK.

Open the Tetracloreto_FC attribute table and verify that contains 142 records.

Step3: Join the Point attribute table with our new data table from Excel.

In the TOC right click on the new layer; hover the pointer over Join and Relates; then, select â€˜Join.

In the Join Data pane for Choose the field in this layer that the join will based on: pull-down select OID.

Verify that on Choose the table the Tetracloreto_TAB table is selected.

Verify that on Choose the field the field OBJECTID is selected.

Click OK.

Open the Tetracloreto_FC table and verify the join. Notice that the attributes of your excel table now are joined with the Tetracloreto_FC attribute table.

Close the table.

Step 4: Verify that the points are not autocorrelated.

Now you are ready to validate your point data. Run the Spatial Autocorrelation tool to verify that the points are not autocorrelated.

In the Search Window search for the Spatial Autocorrelation(Morans I) (Spatial statistics).

Open the tool, click on the tool blue link.

For Input Feature Class select Tetracloreto_FC

For the Input Field from the pulldown select Tetracloreto_FC.report_r_1.

Check Generate Report.

Click OK.

From the Geoprocessing menu open the Results Window.

Expand (+) Spatial Autocorrelation (Morans I) tool results.

Double click on the .html report file to open it.

Verify that the pattern does not appear to be significantly different than random.

Close the window.

Step 5: Create the interpolated surface using Kriging.

Click the Customize menu, hover your pointer over Toolbars and select the Geostatistical Analyst extension.

Click on Customize menu; then, click on Extensions.

Verify that the extension is available and if necessary check the box.

Close the Extension pane.

On the Geostatistical Analyst toolbar, click on Geostatistical Wizard icon to launch it.

This will open the Geostatistical Wizard: Kriging/CoKriging pane.

For Methods under Geostatistical methods, click on Kriging/CoKriging.

For input data, under Dataset verify that for Source Dataset Tetracloreto_FC is selected.

For Data Field from the pulldown menu select Tetracloreto_FC.report_r_1.

Click Next.

For Kriging Type click on Ordinary.

Verify that for Output Surface Type Prediction is selected.

Click Next.

Explore the Semivariogram/Covariance Modeling pane; then, click Next. (Optional)

Explore the Searching Neighborhood pane; then, click Next. (Optional)

Explore the Cross Validation pane; then, click Finish.

Review the Method Report summary; then, click on OK.

The Kriging layer with Prediction Map is displayed with its corresponding color ramp.

Click on List By Drawing Order and move the point layer to the top.

In case you would like to try the Kriging tool from the Spatial Analyst Toolbox.

In the Search Window search for the kriging (Spatial Analyst).

Open the tool, click on the tool blue link.

In the Kriging pane for Input point features select your points Tetracloreto_FC.

For Z value field from the pulldown select Tetracloreto_FC.report_r_1.

For Output surface raster enter Tetracloreto_FC_OK.

For Semivariogram properties, verify that the Ordinary Kriging method is selected.

For Output variance of prediction raster(optional) browse to your default geodatabase enter Tetracloreto_FC_VAR.

Click OK.

Review the results.

For more information about Geostatistical Analyst: http://desktop.arcgis.com/en/arcmap/latest/extensions/geostatistical-analyst/a-quick-tour-of-geostatistical-analyst.htm

I believe we are done here :0)

Cheers

Chao

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