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Improving workflow at CNDDB

This project aims to enhance the workflow at the California Natural Diversity Database (CNDDB) by automating data processing tasks using Python scripts. Key tasks include selecting unbuffered new records, appending buffer results, and marking records as processed with updated field values. By creating a new field for tracking buffer status, the workflow is streamlined when incorporating new data. This automation alleviates time-consuming manual processes, thus improving efficiency in mapping rare plants and animals for California's natural heritage program.

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Improving workflow at CNDDB

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  1. Annie Chang Improving workflow at CNDDB

  2. California Natural Diversity Database • Natural heritage program • Map rare plants and animals • http://www.dfg.ca.gov/biogeodata/cnddb/

  3. Work is time-consuming

  4. Purpose • Automate part of the workflow using python script

  5. Select by attributes • Needed to select new records that are not yet buffered (Source_Feature = N)

  6. Buffer selected records

  7. Append • Each time the script runs, the buffer feature class would be deleted and recreated • Save the results of the buffer in the feature class SOURCE_FEATURE through append

  8. Calculate Field • Needed to mark the records as processed • Values of Source_Feature were changed from “N” to “Y”

  9. Dissolve • Occurrences are summaries of detection areas for particular species

  10. Obstacles • When to put single, double, or no quotes around variables • Text values for the CalculateField operation needed double quotes

  11. Obstacles (continued) • Originally, the buffer was done on the entire source layer. Then, I realized if I were to add additional records to the source layer (like when we receive new data at CNDDB), there is no way to only buffer the new data. I added a new field “Source_Feature” that had values “Y” or “N” to indicate whether this record has already been buffered and saved in the SOURCE_FEATURE feature class.

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