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Cover Crop Remotely Observed Performance (CCROP): The Maryland Department of Agriculture (MDA) is interested in verifying winter cover crop implementation and analyzing cover crop productivity using satellite imagery. As they do not have the expertise on-site to automate the process, we used a combination of scripting using JavaScript in Google Earth Engine (GEE) and ArcGIS to identify suitable Landsat and Sentinel images, extract individual farm field characters (such as values for various bands, NDVI, and red-edge) to a table, and export this table. Subsequently, this table will be incorporated in the MDA agronomic database where crop and farm productivity reports can be created as needed.

ccrop's Introduction

CCROP

Cover Crop Remotely Observed Performance (CCROP): The Maryland Department of Agriculture (MDA) is interested in verifying winter cover crop implementation and analyzing cover crop productivity using satellite imagery. As they do not have the expertise on-site to automate the process, we used a combination of scripting using JavaScript in Google Earth Engine (GEE) and ArcGIS to identify suitable Landsat and Sentinel images, extract individual farm field characters (such as values for various bands, NDVI, and red-edge) to a table, and export this table. Subsequently, this table will be incorporated in the MDA agronomic database where crop and farm productivity reports can be created as needed.

This work was part of the NASA DEVELOP Chesapeake Bay Agriculture project at NASA Goddard Space Flight Center in Spring 2017.

For more information about the project: https://develop.larc.nasa.gov/2017/spring/ChesapeakeBayAg.html

For a video about the project and the applications of these scripts: https://www.youtube.com/watch?v=42bDUCT1QBg

Scripts' Primary Author: Alison Thieme, [email protected]

Team Members: John Fitz, Sean McCartney, Perry Oddo, Alison Thieme, Sunita Yadav (Team Leader)

Most Recent Update: April 10, 2018

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Contributors

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