Accuracy, Bias, and Improvements in Mapping Crops and Cropland across the United States Using the USDA Cropland Data Layer

Lark, Tyler J.; Schelly, Ian H.; Gibbs, Holly K.

doi:10.3390/rs13050968

Accuracy, Bias, and Improvements in Mapping Crops and Cropland across the United States Using the USDA Cropland Data Layer

Journal Article · Wed Mar 03 23:00:00 EST 2021 · Remote Sensing

DOI:https://doi.org/10.3390/rs13050968· OSTI ID:1776846

^[1]; Schelly, Ian H. ^[2]; Gibbs, Holly K. ^[2]

Univ. of Wisconsin, Madison, WI (United States); University of Wisconsin-Madison Nelson Institute Center for Sustainability and the Global Environment (SAGE)
Univ. of Wisconsin, Madison, WI (United States)

The U.S. Department of Agriculture’s (USDA) Cropland Data Layer (CDL) is a 30 m resolution crop-specific land cover map produced annually to assess crops and cropland area across the conterminous United States. Despite its prominent use and value for monitoring agricultural land use/land cover (LULC), there remains substantial uncertainty surrounding the CDLs’ performance, particularly in applications measuring LULC at national scales, within aggregated classes, or changes across years. To fill this gap, we used state- and land cover class-specific accuracy statistics from the USDA from 2008 to 2016 to comprehensively characterize the performance of the CDL across space and time. We estimated nationwide area-weighted accuracies for the CDL for specific crops as well as for the aggregated classes of cropland and non-cropland. We also derived and reported new metrics of superclass accuracy and within-domain error rates, which help to quantify and differentiate the efficacy of mapping aggregated land use classes (e.g., cropland) among constituent subclasses (i.e., specific crops). We show that aggregate classes embody drastically higher accuracies, such that the CDL correctly identifies cropland from the user’s perspective 97% of the time or greater for all years since nationwide coverage began in 2008. We also quantified the mapping biases of specific crops throughout time and used these data to generate independent bias-adjusted crop area estimates, which may complement other USDA survey- and census-based crop statistics. Our overall findings demonstrate that the CDLs provide highly accurate annual measures of crops and cropland areas, and when used appropriately, are an indispensable tool for monitoring changes to agricultural landscapes.

View Accepted Manuscript (DOE)

Research Organization:: Great Lakes Bioenergy Research Center (GLBRC), Madison, WI (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF)

Grant/Contract Number:: SC0018409

OSTI ID:: 1776846

Journal Information:: Remote Sensing, Journal Name: Remote Sensing Journal Issue: 5 Vol. 13; ISSN 2072-4292

Publisher:: MDPICopyright Statement

Country of Publication:: United States

Language:: English

References (46)

Measured extent of agricultural expansion depends on analysis technique Dunn, Jennifer B.; Merz, Dylan; Copenhaver, Ken L. Biofuels, Bioproducts and Biorefining, Vol. 11, Issue 2 https://doi.org/10.1002/bbb.1750	journal	January 2017
Agricultural expansion: land use shell game in the U.S. Northern Plains Johnston, Carol A. Landscape Ecology, Vol. 29, Issue 1 https://doi.org/10.1007/s10980-013-9947-0	journal	October 2013
Wetland Losses Due to Row Crop Expansion in the Dakota Prairie Pothole Region Johnston, Carol A. Wetlands, Vol. 33, Issue 1 https://doi.org/10.1007/s13157-012-0365-x	journal	January 2013
Evidence for increased monoculture cropping in the Central United States Plourde, James D.; Pijanowski, Bryan C.; Pekin, Burak K. Agriculture, Ecosystems & Environment, Vol. 165 https://doi.org/10.1016/j.agee.2012.11.011	journal	January 2013
A 2010 map estimate of annually tilled cropland within the conterminous United States Johnson, David M. Agricultural Systems, Vol. 114 https://doi.org/10.1016/j.agsy.2012.08.004	journal	January 2013
Taken as a given: Evaluating the accuracy of remotely sensed crop data in the USA Larsen, Ashley E.; Hendrickson, Brandon T.; Dedeic, Nicholas Agricultural Systems, Vol. 141 https://doi.org/10.1016/j.agsy.2015.10.008	journal	December 2015
Biofuel impact on food prices index and land use change Shrestha, D. S.; Staab, B. D.; Duffield, J. A. Biomass and Bioenergy, Vol. 124 https://doi.org/10.1016/j.biombioe.2019.03.003	journal	May 2019
CropScape: A Web service based application for exploring and disseminating US conterminous geospatial cropland data products for decision support Han, Weiguo; Yang, Zhengwei; Di, Liping Computers and Electronics in Agriculture, Vol. 84 https://doi.org/10.1016/j.compag.2012.03.005	journal	June 2012
Identifying representative crop rotation patterns and grassland loss in the US Western Corn Belt Sahajpal, Ritvik; Zhang, Xuesong; Izaurralde, Roberto C. Computers and Electronics in Agriculture, Vol. 108 https://doi.org/10.1016/j.compag.2014.08.005	journal	October 2014
Valuing map validation: The need for rigorous land cover map accuracy assessment in economic valuations of ecosystem services Foody, G. M. Ecological Economics, Vol. 111 https://doi.org/10.1016/j.ecolecon.2015.01.003	journal	March 2015
Evaluating forest conservation policies in developing countries using remote sensing data: An introduction and practical guide Blackman, Allen Forest Policy and Economics, Vol. 34 https://doi.org/10.1016/j.forpol.2013.04.006	journal	September 2013
Measuring land-use and land-cover change using the U.S. department of agriculture’s cropland data layer: Cautions and recommendations Lark, Tyler J.; Mueller, Richard M.; Johnson, David M. International Journal of Applied Earth Observation and Geoinformation, Vol. 62 https://doi.org/10.1016/j.jag.2017.06.007	journal	October 2017
The environmental effects of crop price increases: Nitrogen losses in the U.S. Corn Belt Hendricks, Nathan P.; Sinnathamby, Sumathy; Douglas-Mankin, Kyle Journal of Environmental Economics and Management, Vol. 68, Issue 3 https://doi.org/10.1016/j.jeem.2014.09.002	journal	November 2014
Protecting our prairies: Research and policy actions for conserving America’s grasslands Lark, Tyler J. Land Use Policy, Vol. 97 https://doi.org/10.1016/j.landusepol.2020.104727	journal	September 2020
Thematic accuracy of the NLCD 2001 land cover for the conterminous United States Wickham, J. D.; Stehman, S. V.; Fry, J. A. Remote Sensing of Environment, Vol. 114, Issue 6 https://doi.org/10.1016/j.rse.2010.01.018	journal	June 2010
Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation Olofsson, Pontus; Foody, Giles M.; Stehman, Stephen V. Remote Sensing of Environment, Vol. 129 https://doi.org/10.1016/j.rse.2012.10.031	journal	February 2013
Estimating area from an accuracy assessment error matrix Stehman, Stephen V. Remote Sensing of Environment, Vol. 132 https://doi.org/10.1016/j.rse.2013.01.016	journal	May 2013
Good practices for estimating area and assessing accuracy of land change Olofsson, Pontus; Foody, Giles M.; Herold, Martin Remote Sensing of Environment, Vol. 148 https://doi.org/10.1016/j.rse.2014.02.015	journal	May 2014
National-scale soybean mapping and area estimation in the United States using medium resolution satellite imagery and field survey Song, Xiao-Peng; Potapov, Peter V.; Krylov, Alexander Remote Sensing of Environment, Vol. 190 https://doi.org/10.1016/j.rse.2017.01.008	journal	March 2017
Key issues in rigorous accuracy assessment of land cover products Stehman, Stephen V.; Foody, Giles M. Remote Sensing of Environment, Vol. 231 https://doi.org/10.1016/j.rse.2019.05.018	journal	September 2019
Accelerated Conversion of Native Prairie to Cropland in Minnesota Lark, Tyler J.; Larson, Ben; Schelly, Ian Environmental Conservation, Vol. 46, Issue 2 https://doi.org/10.1017/S0376892918000437	journal	December 2018
Cropland expansion in the United States produces marginal yields at high costs to wildlife Lark, Tyler J.; Spawn, Seth A.; Bougie, Matthew Nature Communications, Vol. 11, Issue 1 https://doi.org/10.1038/s41467-020-18045-z	journal	September 2020
The emergence of land change science for global environmental change and sustainability Turner, B. L.; Lambin, E. F.; Reenberg, A. Proceedings of the National Academy of Sciences, Vol. 104, Issue 52 https://doi.org/10.1073/pnas.0704119104	journal	December 2007
Cultivated hay and fallow/idle cropland confound analysis of grassland conversion in the Western Corn Belt Kline, K. L.; Singh, N.; Dale, V. H. Proceedings of the National Academy of Sciences, Vol. 110, Issue 31 https://doi.org/10.1073/pnas.1306646110	journal	June 2013
Reply to Kline et al.: Cropland data layer provides a valid assessment of recent grassland conversion in the Western Corn Belt Wright, C. K.; Wimberly, M. C. Proceedings of the National Academy of Sciences, Vol. 110, Issue 31 https://doi.org/10.1073/pnas.1307594110	journal	June 2013
Perennial grasslands enhance biodiversity and multiple ecosystem services in bioenergy landscapes Werling, B. P.; Dickson, T. L.; Isaacs, R. Proceedings of the National Academy of Sciences, Vol. 111, Issue 4 https://doi.org/10.1073/pnas.1309492111	journal	January 2014
Crop classification modelling using remote sensing and environmental data in the Greater Platte River Basin, USA Howard, Daniel M.; Wylie, Bruce K.; Tieszen, Larry L. International Journal of Remote Sensing, Vol. 33, Issue 19 https://doi.org/10.1080/01431161.2012.680617	journal	April 2012
Monitoring US agriculture: the US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program Boryan, Claire; Yang, Zhengwei; Mueller, Rick Geocarto International, Vol. 26, Issue 5 https://doi.org/10.1080/10106049.2011.562309	journal	August 2011
Measuring Cropland Change: A Cautionary Tale Laingen, Chris Papers in Applied Geography, Vol. 1, Issue 1 https://doi.org/10.1080/23754931.2015.1009305	journal	January 2015
Cropland expansion outpaces agricultural and biofuel policies in the United States Lark, Tyler J.; Meghan Salmon, J.; Gibbs, Holly K. Environmental Research Letters, Vol. 10, Issue 4 https://doi.org/10.1088/1748-9326/10/4/044003	journal	April 2015
Grasslands, wetlands, and agriculture: the fate of land expiring from the Conservation Reserve Program in the Midwestern United States Morefield, Philip E.; LeDuc, Stephen D.; Clark, Christopher M. Environmental Research Letters, Vol. 11, Issue 9 https://doi.org/10.1088/1748-9326/11/9/094005	journal	August 2016
Complying with conservation compliance? An assessment of recent evidence in the US Corn Belt Holland, Austin; Bennett, David; Secchi, Silvia Environmental Research Letters, Vol. 15, Issue 8 https://doi.org/10.1088/1748-9326/ab8f60	journal	August 2020
Modeling Grassland Conversion: Challenges of Using Satellite Imagery Data Rashford, Benjamin S.; Albeke, Shannon E.; Lewis, David J. American Journal of Agricultural Economics, Vol. 95, Issue 2 https://doi.org/10.1093/ajae/aas110	journal	December 2012
Crop Supply Dynamics and the Illusion of Partial Adjustment Hendricks, Nathan P.; Smith, Aaron; Sumner, Daniel A. American Journal of Agricultural Economics, Vol. 96, Issue 5 https://doi.org/10.1093/ajae/aau024	journal	May 2014
Change Vector Analysis in Posterior Probability Space: A New Method for Land Cover Change Detection Chen, Jin; Chen, Xuehong; Cui, Xihong IEEE Geoscience and Remote Sensing Letters, Vol. 8, Issue 2 https://doi.org/10.1109/LGRS.2010.2068537	journal	March 2011
Changes of crop rotation in Iowa determined from the United States Department of Agriculture, National Agricultural Statistics Service cropland data layer product Stern, Alan J.; Doraiswamy, Paul C.; Raymond Hunt, E. Journal of Applied Remote Sensing, Vol. 6, Issue 1 https://doi.org/10.1117/1.JRS.6.063590	journal	January 2012
Assessing the Accuracy of Remotely Sensed Data Congalton, Russell G.; Green, Kass CRC Press https://doi.org/10.1201/9781420055139	book	December 2008
Plowprint: Tracking Cumulative Cropland Expansion to Target Grassland Conservation Gage, Anne M.; Olimb, Sarah K.; Nelson, Jeff Great Plains Research, Vol. 26, Issue 2 https://doi.org/10.1353/gpr.2016.0019	journal	January 2016
Ecosystem-Service Tradeoffs Associated with Switching from Annual to Perennial Energy Crops in Riparian Zones of the US Midwest Meehan, Timothy D.; Gratton, Claudio; Diehl, Erica PLoS ONE, Vol. 8, Issue 11 https://doi.org/10.1371/journal.pone.0080093	journal	November 2013
Development and Applications of a Comprehensive Land Use Classification and Map for the US Theobald, David M. PLoS ONE, Vol. 9, Issue 4 https://doi.org/10.1371/journal.pone.0094628	journal	April 2014
Recent Land Use Change to Agriculture in the U.S. Lake States: Impacts on Cellulosic Biomass Potential and Natural Lands Mladenoff, David J.; Sahajpal, Ritvik; Johnson, Christopher P. PLOS ONE, Vol. 11, Issue 2 https://doi.org/10.1371/journal.pone.0148566	journal	February 2016
Uncertainty and Confidence in Land Cover Classification Using a Hybrid Classifier Approach Liu, Weiguo; Gopal, Sucharita; Woodcock, Curtis E. Photogrammetric Engineering & Remote Sensing, Vol. 70, Issue 8 https://doi.org/10.14358/PERS.70.8.963	journal	August 2004
Does the U.S. Cropland Data Layer Provide an Accurate Benchmark for Land-Use Change Estimates? Reitsma, Kurtis D.; Clay, David E.; Clay, Sharon A. Agronomy Journal, Vol. 108, Issue 1 https://doi.org/10.2134/agronj2015.0288	journal	January 2016
Trends in Remote Sensing Accuracy Assessment Approaches in the Context of Natural Resources Morales-Barquero, Lucia; Lyons, Mitchell; Phinn, Stuart Remote Sensing, Vol. 11, Issue 19 https://doi.org/10.3390/rs11192305	journal	October 2019
U.S. Conterminous Wall-to-Wall Anthropogenic Land Use Trends (NWALT), 1974-2012 Survey, U. S. Geological U.S. Geological Survey https://doi.org/10.5066/p9xjkkc3	dataset	January 2023
Accuracy, bias, and improvements in mapping crops and cropland across the United States using the USDA Cropland Data Layer; Data associated with Lark et al. 2021 Lark, Tyler; Schelly, Ian; Gibbs, Holly Zenodo https://doi.org/10.5281/zenodo.4579864	dataset	January 2021

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Accuracy, Bias, and Improvements in Mapping Crops and Cropland across the United States Using the USDA Cropland Data Layer

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