Mapping the current extent and suitability of agroforestry in the US Midwest

Project Overview

Project Type: Graduate Student
Funds awarded in 2022: $14,938.00
Projected End Date: 08/31/2024
Grant Recipient: University of Illinois Urbana-Champaign
Region: North Central
State: Illinois
Graduate Student:
Faculty Advisor:
Richard Brazee
University of Illinois Urbana-Champaign
Faculty Advisor:
Daniel Miller
University of Notre Dame


No commodities identified


No practices identified

Proposal abstract:

Title: Mapping the current extent and suitability of agroforestry in the US Midwest

Sustainable agricultural practices like agroforestry are necessary to ensure global food security, mitigate climate change, conserve biodiversity, and provide ecosystem services. Such practices can also boost economic profitability, protect human health, and enhance well-being. Agroforestry, defined as the integration of trees into crop and livestock systems, is widely promoted as a sustainable land use practice. The United States lacks a national assessment of agroforestry. Consequently, we miss a critical opportunity to advance both environmental and social sustainability goals.

The need for a national agroforestry assessment has been identified in national statements like the USDA Agroforestry Strategic Framework. We have also identified this need through preliminary field work in Southern Illinois interviewing extension agents, NRCS agents, farm service agents, and producers as well as in Missouri at the University of Missouri Center for Agroforestry. Other stakeholders were identified at agroforestry conferences where both researchers and practitioners called for the need of a national inventory of agroforestry. This research will address this knowledge gap through comprehensive mapping of the current extent and suitability of agroforestry practices using remotely sensed imagery and machine learning for the US Midwest.

As higher resolution satellite imagery allows for finer resolution imaging of landscapes, machine learning-based prediction methods can help map the existing extent of agroforestry. This research will rely on machine learning, including deep convolution neural network techniques, to process high-resolution aerial imagery and detect the current extent of agroforestry practices. Additionally, high-performance geospatial computing methods can help identify priority areas where interventions may be most effective. Using our agroforestry land cover data and other biophysical and social datasets, this work will generate a social-ecological suitability map of agroforestry in the US to determine the potential for expanding these practices.

High-resolution mapping of agroforestry practices in the US landscape is essential for monitoring and assessing the contributions of agroforestry to supporting environmental and economic objectives. Such land use mapping can also help track the permanence of practices supported by US agri-environmental programs. Additionally, maps showing the potential suitability of agroforestry based on social, economic, and biophysical factors (“suitability maps”) can be powerful resources for decision-makers to design and target agri-environmental programs effectively. The results of this work will help inform agricultural policies promoted by governments and organizations, improve targeting of programs, and inform farmers’ decisions based on environmental and economic suitability models.

Project objectives from proposal:

The overarching goal of this research project is to inform Midwest agroforestry policy through assessing existing agroforestry practices and mapping the suitability of agroforestry. The methods and tools developed through this project will lay the foundation to evaluate the political and economic feasibility of agroforestry across the US.

To achieve this goal, the project includes two interlinked objectives: (1) develop a classification tool and map the extent of agroforestry practices in the US Midwest, and (2) map the suitability of agroforestry practices and predict priority areas for agroforestry development across the US Midwest. The results of these objectives will contribute towards the US agroforestry agenda.

The expected outcomes of the first objective include reaching researchers and policymakers to illustrate the current contributions of agroforestry and enable future research quantifying the impacts of agroforestry. We will track this outcome through the citations and downloads of our publications and policy briefs. This work will also improve monitoring of land use change and permanence of conservation practices like agroforestry to better understand the effectiveness US agri-environmental policies and investments.

The expected outcomes of the second objective include creating and disseminating the suitability map as an interactive tool for policymakers, agencies, and producers. With limited funding for conservation initiatives, improved methods for rapid, evidence-based targeting of suitable areas and estimates of the potential ecosystem contributions are needed. Continued conversations with policymakers and agencies will help us track all the above outcomes. Repository accesses will also be an indicator of the impacts of this work.

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.