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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: 10.17226/24892.
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Improving Crop Estimates by
Integrating Multiple Data Sources

Panel on Methods for Integrating Multiple Data Sources
to Improve Crop Estimates

Mary Ellen Bock and Nancy J. Kirkendall, Editors

Committee on National Statistics

Division of Behavioral and Social Sciences and Education

A Consensus Study Report of

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THE NATIONAL ACADEMIES PRESS
Washington, DC
www.nap.edu

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: 10.17226/24892.
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This activity was supported by a cooperative agreement between the National Academy of Sciences Committee on National Statistics and the U.S. Department of Agriculture, National Agricultural Statistics Service (agreement number 58-3AEU-4-0068). Support for the work of the Committee on National Statistics is provided by a consortium of federal agencies through a grant from the National Science Foundation, a National Agricultural Statistics Service cooperative agreement, and several individual contracts. Any opinions, findings, conclusions, or recommendations expressed in this publication do not necessarily reflect the views of the organization or agency that provided support for the project.

International Standard Book Number-13: 978-0-309-46529-8
International Standard Book Number-10: 0-309-46529-X
Digital Object Identifier: https://doi.org/10.17226/24892

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Suggested citation: National Academies of Sciences, Engineering, and Medicine. (2017). Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: https://doi.org/10.17226/24892.

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: 10.17226/24892.
×

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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: 10.17226/24892.
×

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Consensus Study Reports published by the National Academies of Sciences, Engineering, and Medicine document the evidence-based consensus on the study’s statement of task by an authoring committee of experts. Reports typically include findings, conclusions, and recommendations based on information gathered by the committee and the committee’s deliberations. Each report has been subjected to a rigorous and independent peer-review process and it represents the position of the National Academies on the statement of task.

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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: 10.17226/24892.
×

PANEL ON METHODS FOR INTEGRATING MULTIPLE DATA SOURCES TO IMPROVE CROP ESTIMATES

MARY ELLEN BOCK (Chair), Department of Statistics (emerita), Purdue University

JULIE GERSHUNSKAYA, Bureau of Labor Statistics, U.S. Department of Labor

MALAY GHOSH, Department of Statistics, University of Florida

MICHAEL GOODCHILD, Department of Geography (emeritus), University of California, Santa Barbara

CHAD HART, Department of Economics, Iowa State University (through October 2016)

OLGA ISENGILDINA MASSA, Department of Agricultural and Applied Economics, Virginia Polytechnic Institute and State University

SUSAN OFFUTT, Department of Economics (retired), U.S. Government Accountability Office

S. LYNNE STOKES, Department of Statistical Sciences, Southern Methodist University

JON WAKEFIELD, Department of Statistics, University of Washington

ROBERT YOUNG, Department of Public Policy, American Farm Bureau Federation

NANCY J. KIRKENDALL, Study Director

BRIAN HARRIS-KOJETIN, Director, Committee on National Statistics

CONSTANCE F. CITRO, Senior Scholar

GLENN D. WHITE, Jr., Senior Program Officer

MARY ANN KASPER, Senior Program Assistant

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: 10.17226/24892.
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COMMITTEE ON NATIONAL STATISTICS

ROBERT M. GROVES (Chair), Office of the Provost, Department of Mathematics and Statistics and Department of Sociology, Georgetown University

FRANCINE BLAU, Department of Economics, Cornell University

MARY ELLEN BOCK, Department of Statistics (emerita), Purdue University

ANNE C. CASE, Woodrow Wilson School of Public and International Affairs, Princeton University

MICHAEL E. CHERNEW, Department of Health Care Policy, Harvard Medical School

JANET CURRIE, Woodrow Wilson School of Public and International Affairs, Princeton University

DONALD A. DILLMAN, Department of Sociology, Washington State University

CONSTANTINE GATSONIS, Center for Statistical Sciences, Brown University

JAMES S. HOUSE, Survey Research Center, Institute for Social Research, University of Michigan

THOMAS L. MESENBOURG, U.S. Census Bureau (retired)

SARAH M. NUSSER, Department of Statistics, Iowa State University

COLM O’MUIRCHEARTAIGH, Harris School of Public Policy Studies, University of Chicago

JEROME P. REITER, Department of Statistical Science, Duke University

ROBERTO RIGOBON, Sloan School of Management, Massachusetts Institute of Technology

JUDITH A. SELZTER, Department of Sociology, University of California, Los Angeles

EDWARD H. SHORTLIFFE, Department of Biomedical Informatics, Columbia University and Arizona State University

BRIAN HARRIS-KOJETIN, Director

CONSTANCE F. CITRO, Senior Scholar

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: 10.17226/24892.
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Acknowledgments

This report is the product of contributions from many colleagues, whom I thank for their time, generosity, and expert guidance. The report also benefited strongly from the skillful guidance of the study director, whom I wish to acknowledge and thank.

As chair, I first acknowledge with great appreciation the efforts of my fellow panel members. Despite their many professional commitments, every panel member donated countless hours and shared extensive expertise to make this report possible. The report reflects the collective expertise, varied perspectives, diverse backgrounds, and commitment of all panel members: Julie Gershunskaya, Bureau of Labor Statistics, U.S. Department of Labor; Malay Ghosh, Department of Statistics, University of Florida; Michael Goodchild, Department of Geography (emeritus), University of California, Santa Barbara; Chad Hart, Department of Economics, Iowa State University; Olga Isengildina Massa, Department of Agricultural and Applied Economics, Virginia Polytechnic Institute and State University; Susan Offutt, Department of Economics (retired), U.S. Government Accountability Office; S. Lynne Stokes, Department of Statistical Sciences, Southern Methodist University; Jon Wakefield, Department of Statistics, University of Washington; and Robert Young, Department of Public Policy, American Farm Bureau Federation.

The project was sponsored by the National Agricultural Statistics Service (NASS), U.S. Department of Agriculture (USDA). The bulk of the panel’s first four meetings were open meetings consisting of many presentations and discussions as noted in more detail below. The meetings were well attended by NASS staff, who actively engaged in discussions with the

Page viii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: 10.17226/24892.
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panel, helping us to appreciate the work NASS does. I would especially like to acknowledge Nathan Cruze, the panel’s primary contact person with NASS. He orchestrated and organized the many presentations to the panel by NASS staff, prepared or collected background material needed by the panel, and shared his deep knowledge about NASS and especially its modeling activities.

The panel would like to express their thanks to NASS senior management, first Joe Riley (former administrator) then Hubert Hamer (current administrator) for their encouragement and support and Linda Young (director of research) who helped to make this effort possible. The panel thanks the following NASS staff and contractors for their detailed presentations (often more than one), helping the panel to learn about NASS surveys, systems, and models: Edwin Anderson (cash rents); Mark Apodaca (NASS list frame building and maintenance); Jeff Bailey (cash rents survey and model results); Wendy Barboza (linking NASS and FSA data); Dan Beckler (linking NASS and FSA data); Nathan Cruze (model-based research in general and specific, cash rents and crops); Lindsay Drunasky (crops surveys); Andreea Erciulescu (NASS/NISS) (model-based research in general and specific, cash rents and crops); Noemi Guindin (a potential decision support system linking yield to weather changes); Lance Honig (crops, publication standards, setting estimates, data timelines); David Johnson (remote sensing yield estimates); Troy Joshua (cash rents survey); Rick Mueller (remote sensing); Balgobin Nandram (Worcester Polytechnic Institute) (crops modeling); Gerald Tillman (crops and cash rents surveys); and Linda Young (modeling and direction)

The panel would like to express special thanks to representatives of the Farm Service Agency (FSA) and Risk Management Agency (RMA) for their help in understanding their use of NASS data and features of the administrative data provided by their agencies. Speakers included Michael Alston, RMA; Joy Harwood, FSA; Terry Hickenbotham, FSA; Rich Iovanna, FSA; John Jinkins, FSA; Phil Sronce, FSA; and David Zanoni, RMA.

The panel would also like to thank Vince Breneman and Roger Glassen representatives of the Economic Research Service and Patrick Flanagan, Natural Resources Conservation Service for presentations that helped the panel understand some of the USDA geospatial data and their use. The panel would also like to thank representatives of other federal statistical agencies for their advice, especially on modeling issues; Wes Basel and William Bell with the U.S. Census Bureau and Alan Dorfman with the National Center for Health Statistics. Special thanks to Mary Kay Thatcher with the Farm Bureau for her presentation about precision agriculture; to David Marker with Westat for his presentation concerning sample survey publication standards used by statistical agencies; to Gordon Reichert with Statistics Canada for his presentation about their new remote sensing model-based estimates

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: 10.17226/24892.
×

for yield during the growing season. To Keith Coble, Mississippi State for his insights on yield modeling; Noel Cressie, University of Wollongong, Australia, for advice on spatiotemporal data fusion for satellite remote sensing; and to Christian Frankenberg, Environmental Science and Engineering, California Institute of Technology, for a discussion of solar-induced chlorophyll fluorescense as measured by a new satellite and to Jerry Hatfield with Agricultural Research Service for his presentation about crop productivity and potential for modeling with new SIF measurements. These individuals attended open meetings and generously gave their time to present material to inform the panel’s deliberations. These presentations stimulated extensive discussion of the issues covered in this report.

The panel could not have conducted its work efficiently without the capable staff of the National Academies of Sciences, Engineering, and Medicine. The panel was fortunate to have as its study director Nancy Kirkendall. She brought to the panel her extensive experience in government agencies, including the former directorship of the Statistics and Methods Group of the U.S. Energy Information Administration as well as an outstanding history of directing National Academies studies. Our work could not have been completed without her extraordinary dedication and many contributions. She provided technical and substantive insights; drafted and revised almost all the sections of our report, pulling together the wide range of panel expertise; and kept the project on track, also serving as the hub for communication. We were also fortunate to have the counsel of Connie Citro, senior scholar with the Committee on National Statistics (CNSTAT). We also want to thank CNSTAT senior program officers Glenn White, who gave an extra ear and eye to our deliberations, and Carol House, who provided extra insights; Mary Ann Kasper, who provided excellent administrative and logistical support to the panel; and Kirsten Sampson-Snyder, Division of Behavioral and Social Sciences and Education, for expertly coordinating the review process.

The panel also recognizes the many federal agencies that support CNSTAT directly and through a grant from the National Science Foundation. Without their support and their commitment to improving the national statistical system, the panel’s work that is the basis of this report would not have been possible.

This Consensus Study Report was reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise. The purpose of this independent review is to provide candid and critical comments that will assist the National Academies in making each published report as sound as possible and to ensure that it meets the institutional standards for quality, objectivity, evidence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process.

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2017. Improving Crop Estimates by Integrating Multiple Data Sources. Washington, DC: The National Academies Press. doi: 10.17226/24892.
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We thank the following individuals for their review of this report: Zachary S. Brown, Department of Agricultural and Resource Economics, North Carolina State University; Cynthia Z.F. Clark, independent consultant, McLean, VA; Keith Coble, Department of Agricultural Economics, Mississippi State University; Joseph W. Glauber, Markets, Trade and Institutions Division, International Food Policy Research Institute, Washington, D.C.; Barry Goodwin, Department of Agricultural and Resource Economics, North Carolina State University; Scott H. Holan, Department of Statistics, University of Missouri; Xiaofei Li, Department of Agricultural Economics, Mississippi State University; Prabhu L. Pingali, Tata-Cornell Institute for Agricultural and Nutrition, Cornell University; and Eric V. Slud, Statistics Program, University of Maryland, College Park, and Mathematical Statistics, Center for Statistical Research and Methodology, U.S. Census Bureau.

Although the reviewers listed above provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations of this report nor did they see the final draft before its release. The review of this report was overseen by Sarah M. Nusser, Center for Survey Statistics and Methodology, Iowa State University, and Christopher A. Sims, Department of Economics, Princeton University. They were responsible for making certain that an independent examination of this report was carried out in accordance with the standards of the National Academies and that all review comments were carefully considered. Responsibility for the final content rests entirely with the authoring committee and the National Academies.

Mary Ellen Bock, Chair

Panel on Methods for Integrating Multiple Data Sources to Improve Crop Estimates

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The National Agricultural Statistics Service (NASS) is the primary statistical data collection agency within the U.S. Department of Agriculture (USDA). NASS conducts hundreds of surveys each year and prepares reports covering virtually every aspect of U.S. agriculture. Among the small-area estimates produced by NASS are county-level estimates for crops (planted acres, harvested acres, production, and yield by commodity) and for cash rental rates for irrigated cropland, nonirrigated cropland, and permanent pastureland. Key users of these county-level estimates include USDA's Farm Services Agency (FSA) and Risk Management Agency (RMA), which use the estimates as part of their processes for distributing farm subsidies and providing farm insurance, respectively.

Improving Crop Estimates by Integrating Multiple Data Sources assesses county-level crop and cash rents estimates, and offers recommendations on methods for integrating data sources to provide more precise county-level estimates of acreage and yield for major crops and of cash rents by land use. This report considers technical issues involved in using the available data sources, such as methods for integrating the data, the assumptions underpinning the use of each source, the robustness of the resulting estimates, and the properties of desirable estimates of uncertainty.

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