Location:
Project Number: 3012-21000-015-022-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Jul 2, 2018
End Date: Jun 28, 2019
Objective:
All aspects of this cooperative agreement will be conducted based on sustained communication between the research team and the ARS. The research team will facilitate a series of NASA DEVELOP feasibility projects throughout the agreement period. The NASA DEVELOP teams will work to devise Remote Sensing methodologies and modeling techniques, employing NASA Earth Observations, to optimize the USDA ARS NLGRP current species distribution modeling approach.
This cooperative agreement consists of multiple objects. First, these projects will generate novel approaches for implementing both spectral and species detection models of Crop Wild Relative (CWR) focal species. These generated products will enable future targeted conservation efforts as a means to bolster and preserve national genetic diversity as well as global food security. Next, these projects look to conduct a field surveying effort to acquire in situ field data, oriented for remote sensing application. This data will be implemented as a validation dataset for the sampling protocol and generated models. Lastly through the partnership, the teams will look to produce both a final performance report outlining the methodologies, future questions, and approaches as well as a peer-reviewed journal article that highlights the application of integrating remotely sensed data within species distribution modeling for CWR. The paper will highlight the collaborative endeavors between the research group and the ARS.
Approach:
To address the primary goals of the study several projects will be undertaken by the research group. To begin, a methodology will be created via a NASA DEVELOP feasibility study that will investigate the ability to detect the focal species Northern wild rice (Zizania palustris L.) in Minnesota. The methodology to detect wild rice will primarily employ remotely sensed imagery using spectral and radar based Earth Observation sensors and systems.
From these methods presences absences detection maps will be generated, wherein field crews will work throughout the region to acquire field data as means to obtain a validation dataset. Multiple validation techniques including the collection of species presence points and percent cover of area estimations will be completed across a wide range of diverse habitat types. Due to the availability of the field collected validation dataset, a second NASA DEVELOP term will be devoted to the evaluation and improvement of the detection models. The end result of this term project will be a product that can predict the presence of wild rice at a given accuracy across the species’ known geographic extent. The results of this process will display the potential application of remote sensing techniques for detecting CWR that grows in large monotypic stands.
Expanding on the first two NASA DEVELOP projects, a third project will be set forth to investigate the application of remote sensing techniques to focal species that do not grow in monotypic patches. This project will employ a species distribution modeling approach in tandem with spectral detection model for the focal species. This process will look to determine the practicality of current methods used by ARS and hopes to offer a myriad of detection and predictive methods for future CWR research.
