Examining the Characteristics of the Cropland Data Layer in the Context of Estimating Land Cover Change

Copenhaver, Ken; Hamada, Yuki; Mueller, Steffen; Dunn, Jennifer B.

doi:10.3390/ijgi10050281

Examining the Characteristics of the Cropland Data Layer in the Context of Estimating Land Cover Change

Journal Article · Thu Apr 29 00:00:00 EDT 2021 · ISPRS international journal of geo-information

DOI:https://doi.org/10.3390/ijgi10050281· OSTI ID:1785964

^[1]; Hamada, Yuki ^[2]; Mueller, Steffen ^[3]; ^[4]

CropGrower LLC, Tampa, FL (United States)
Argonne National Lab. (ANL), Argonne, IL (United States). Environmental Science Division
Univ. of Chicago, IL (United States). College of Engineering, Energy Resources Center, Bio-Fuels and Bio-Energy Program
Northwestern Univ., Evanston, IL (United States). Dept. of Chemical and Biological Engineering

The United States Department of Agriculture (USDA) Cropland Data Layer (CDL) provides spatially explicit information about crop production area and has served as a prevalent data source for characterizing cropland change in the U.S. in the last decade. Understanding the accuracy of the CDL is paramount because of the reliance on it for management and policy making. This study examined the characteristics of the CDL from 2007 to 2017 using comparisons to other USDA datasets. The results showed when examining the cropland area for the same year, the CDL produced comparable trends with other datasets (R² > 0.95), but absolute area differed. The estimated area of cropland changes from 2007 to 2012, 2008 to 2012 and 2012 to 2017 varied from weak to moderate correlation between the CDL and the tabular data (R² = 0.005~0.63). Differences in area of cropland change varied widely between data sources with the CDL estimating much larger change area. A series of image processing techniques designed to improve the confidence in cropland change estimated using the CDL reduced the area of estimated cropland change. The techniques also, unexpectedly, lowered the correlation in change estimated between the CDL and the tabular datasets. Estimated land cover change area varied widely based on analyses applied and could reverse from increasing to declining area in cropland. Further analyses showed unlikely change scenarios when comparing different year combinations. The authors recommend the CDL only be used for land cover change analysis if the error can be estimated and is within change estimates.

View Accepted Manuscript (DOE)

Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: U.S. Environmental Protection Agency (EPA)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1785964

Journal Information:: ISPRS international journal of geo-information, Journal Name: ISPRS international journal of geo-information Journal Issue: 5 Vol. 10; ISSN 2220-9964

Publisher:: MDPICopyright Statement

Country of Publication:: United States

Language:: English

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58 GEOSCIENCES
USDA
agricultural census
cropland data layer
croplands
land cover change
land cover/land use
national resourceinventory

Examining the Characteristics of the Cropland Data Layer in the Context of Estimating Land Cover Change

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