Welcome to the pest control “Living Database” (PCLD)! Thank you for your interest in using this USDA-funded resource that combines agricultural pest data and Earth observation resources into an interactive database tool.
The Living Database integrates three distinct data sources (insect observations, biological traits, and satellite/airborne Earth observations) into one novel framework, automating data processing and analysis. This analytical engine empowers researchers and growers to understand pest control and environmental conditions.
This slideshow offers a deeper dive into the vision and capabilities and a "how to use" of the PCLD.
We are an interdisciplinary team building a Living Database for pest control analysis that integrates scientists’ datasets with remote sensing and data science to predict pest dynamics across the globe. This USDA-funded project (#1023888) enables new science and decision-support tools to guide land managers and growers in agricultural stewardship.
This project is managed by Richard Sharp and Becky Chaplin-Kramer of Spring. For more information, or if you have questions, contact the project PIs:
On the main page, use multiple filters to query the database by variables of interest, spatial constraints, time spans, or sample size. Dropdown controls allow you to select filters, and upon submission, you’ll see a summary of your query results.
For a complete dataset, click on the “FULL - database dump” link.
After submitting your query, a new page displays the results, including study locations pinned on a map, metadata tables, and a subset of data. For full data access, click on ‘download full set’ at the top of the page.
To view remote-sensed datasets, click the ‘Visualize’ button, select data types to compare, and explore study sites of interest. After viewing potential datasets, use the ‘Extract’ button to upload your points of interest, choose EO datasets, and download the data.
We seek datasets covering pest or natural enemy abundance, parasitism/predation rates, or pest damage data. Ideal datasets cover >100 farm-years. Minimum data requirements include:
Submit completed templates to Richard Sharp.