Location: Hydrology and Remote Sensing Laboratory2013 Annual Report
1a. Objectives (from AD-416):
1. To develop and implement tools to routinely measure winter cover crop productivity and nutrient uptake at the landscape or statewide scale, providing timely data output that can used by conservation program managers to more effectively manage winter cover crop programs for water quality protection. 2. To expand the use of adaptive management toolkits within two important physiographic regions of the Chesapeake Bay watershed (Coastal Plain and Piedmont) which will include work in the Monocacy watershed (MD), Smith Creek watershed (VA) and, Conewago Creek watershed (PA), with appropriate coordination through local partners and local soil conservation districts. 3. To create a web-based framework to provide geospatial reporting of cover crop performance, along with additional useful geospatial data sets, to Chesapeake Bay partners, thereby increasing the amount of useful, accessible knowledge and supporting the promotion of sustainable agricultural management practices.
1b. Approach (from AD-416):
Using existing methodologies recently developed by HRSL, we will combine remote sensing estimates of vegetation biomass with farm records for fields enrolled in the MACS cover crop program, deriving estimated nitrogen sequestration totals for each field. Additional on-farm sampling will be conducted to calibrate image interpretation and to work out issues with image pixel size. This project centers on the use of satellite remote sensing data and GIS analysis to monitor cover crop performance and provide adaptive management feedback for improved conservation program implementation. It will also involve development of software to automate aggregation of privacy protected conservation implementation data so that the aggregated product can pass through privacy firewalls for use by watershed managers.
3. Progress Report:
Efforts to refine the satellite calibration for nutrient uptake by winter cover crops continued under this project. This effort involved collection of cover crop samples during the winter and spring and related biomass measurements to spectral information in satellite images. Additional effort involved determining the utility of atmospheric corrections for improving calibrations. State wide implementation of satellite monitoring of cover crop performance requires development of software tools for capturing of geospatial data and for data analyses within the geospatial context. Substantial progress was made towards development and refinement of these tools.