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Spring 2012 Edition
By Mike Price, Entrada/San Juan, Inc.[an error occurred while processing this directive]
This article as a PDF.
This exercise models data from a well-known gold and base metals mining area in northern Nevada located near the town of Battle Mountain.
Many organizations keep valuable data in Microsoft Excel and comma-separated values (CSV) files. Learn a methodology for importing data kept in Excel and CSV files into ArcGIS that has been updated for ArcGIS 10 and Microsoft Office 2007/2010.
Excel spreadsheets have been used since the release of ArcGIS 8 to prepare and import tabular data into a GIS. Previous ArcUser articles described the benefits and limitations of spreadsheets in the version of ArcGIS current at that time. In early 2004, ArcUser editor Monica Pratt wrote "Working with Excel in ArcGIS." In 2007, the author wrote another article on the same topic, "Mapping and Modeling Groundwater Geochemistry."
Since these articles were published, Microsoft has released two new versions, Excel 2007 and Excel 2010. With each release, spreadsheet capabilities have improved and the processes for importing data into ArcGIS have changed. This article updates and refines rules and procedures for importing Excel 2003 files into ArcGIS 9.x.
Although the sample data is synthetic, it is true to the underlying geology of Battle Mountain, Nevada.
This exercise reexamines the Excel spreadsheet as a data import tool, focusing on ArcGIS 10 and Excel 2007/2010. The tutorial uses spreadsheets to create and enhance geologic data. Field samples include Hydrogeochemical Stream Sediment Reconnaissance (HSSR) points plus custom soil and rock data. In this exercise, we will model a well-known gold and base metals mining area in northern Nevada, located near the town of Battle Mountain. The custom samples are typical of data that might come from the field, assayed by a modern analytic laboratory.
If you have installed Office 2007, you can read .xls and .xlsx files. If you have Office 2003 or 2010 installed, you can read .xls files, but you will need to install the 2007 Office System Driver to read .xlsx files.
If you do not have Microsoft Excel installed, you must install the 2007 driver before you can use either .xls or .xlsx files. The 2007 Office System Driver can be downloaded from the Microsoft Download Center. Carefully follow the installation instructions before you restart ArcGIS.
Also, if you have previously specified on the File Types tab of the Customize > ArcCatalog Options dialog box that ArcCatalog show you .xls files, you'll need to remove this file type to be able to access Excel files directly.
Before beginning to work the exercise, read the accompanying article, "Best Practices When Using Excel Files with ArcGIS," for valuable tips on working with Excel data
To begin this exercise, download the training data. Unzip the excelmagic.zip data into a project area on your local machine and start ArcCatalog.
Navigate to the Battle_Mountain folder and locate the XLSFiles folder. When ArcCatalog displays an Excel file, it adds a dollar sign ($) to each worksheet name. Inside this folder, expand all files. Locate Sample_Locations.xlsx and preview Rock$. This Excel 2010 spreadsheet contains two worksheets named Rock$ and Soil$. Rock$ and Soil$ contain sample numbers, universal transverse Mercator (UTM) coordinates, and field information that allow this data to be posted on a map. Next, preview HSSR_LonLat83.xlsx and study its only worksheet, HSSR$.
Next, locate and preview two CSV files, Rock_Data and Soil_Data. These files contain companion analytic data for the Rock$ and Soil$ worksheets. The [SAMPLENO] field in both CSV files will support a one-to-one tabular join with the same field in the Soil$ and Rock$ worksheets.
Closely inspect the alignment of data in Soil_Data columns. Notice that [SAMPLENO] and [SB_PPM] are aligned on the left side of the column while [AU_PPB], [AG_PPM], [AS_PPM], and [HG_PPB] are aligned on the right. Scroll down through the table and observe that many fields in the right-aligned columns are empty. In the source CSV file, many of the fields contain nonnumeric strings that do not display properly.
Notice that [SB_PPM], a left-aligned field, contains many fields that begin with a less than (<) character. When a geochemical lab is unable to measure the presence of an element, the analytic posting will include a less than character, followed by the detection limit value. In [SB_PPM], the detection limit for antimony is five parts per million, and many samples contain less than this threshold value.
When ArcGIS reads an Excel worksheet table, it uses the first eight rows to define the field format. If those first eight rows contain mixed data types in a single field, that field will be converted to a string field, and the values contained in that field will be converted to strings. When ArcGIS reads a CSV file, the very first record defines the field type. Consequently, some rather detailed data preparation will be necessary before you can use these files. The next step will be to prepare the spreadsheet and CSV data for import into ArcGIS. Close ArcCatalog.
After field names have been corrected, create a named range in Excel called Rock_Locations_Import_R.
These detailed instructions are specifically for Excel 2007 and Excel 2010. If you want to try this exercise using Excel 2003, open Sample_Locations_2003.xls instead.
HSSR_LonLat83.xlsx contains 96 sample sites collected as part of the HSSR back in the 1970s and 1980s. This data is often used as part of a regional reconnaissance program. Prepare the HSSR data for import.
Now to prepare the Rock and Soil analytic data for proper import—a much more difficult task. First, you will use a text editor to prepare Soil_Data.csv.
Since it is statistically meaningful to recognize that some small amount of each element exists in all samples, it is not appropriate to change all < values to zero. Instead, change them to a smaller absolute value, typically 20 to 50 percent of the detection limit. Take a more conservative approach and use 20 percent. Table 1 lists the current value and smaller absolute value for elements below the minimum detection limit.
|Element||Abbr.||Unit||Detection Limit||Change From||Change To|
When the same file is viewed in WordPad, blank fields contain values preceded by a < or > symbol. These indicate values below the detection limits and will be replaced using values in Table 1.
Now, try a similar approach with Rock_Data.csv, using Excel to replace undesirable values. This approach is much more powerful, but also dangerous.
The danger with using Excel to edit and format analytic data lies in how it uses leading zeros to manage alphanumeric strings when all other characters are numeric. Excel tends to convert leading zero strings to numeric values, which forever changes the data. This can be especially dangerous when working with datasets such as tax parcels and lab samples. However, if the file is saved from Excel back into a CSV file, the leading zeros are gone forever and there are no problems.
Once all tables have been carefully prepared, they are imported into a new file geodatabase called Geochemistry.
As the final step in this exercise, you will create a geochemistry geodatabase and import the Excel named ranges and CSV files.
Because you carefully defined these import datasets, the ArcGIS data geoprocessing function readily uses the assigned names.
Finally, open each table in ArcCatalog and verify field names, formats, and record counts. You successfully outmaneuvered those tricky % characters. Finally, remove the _Import from each geodatabase table name and take a break.
If you preview the Battle Mountain geologic map or open the Battle Mountain MXD, you will see the bedrock geology, geologic structure, and mineral occurrences in the study area. Wouldn't it be interesting to place all these rock, soil, and stream sediment samples in this model and go prospecting? This model is designed to do just that. The geochemical data can be used to analyze favorable ratios between multiple elements, define spatial relationships between rock units and faulting, and compare your data to current mines and past producers.
The data used in this exercise was originally developed as part of an ArcView GIS 3 mining training program. While the sample data is synthetic, it is true to the underlying geology. While landownership is imaginary, it reflects exploration trends around Battle Mountain, Nevada, in the early 1990s. Bedrock geology was derived from the Nevada Bureau of Mines and Geology County mapping series. HSSR data was developed through the US Department of Energy National Uranium Resource Evaluation (NURE) program. All data has been transformed from UTM North American Datum 1927 (NAD27) into the current NAD83 datum.