Seasonal cultivated and fallow cropland mapping using MODIS-based automated cropland classification algorithm

Wu, Zhuoting and Thenkabail, Prasad S. and Mueller, Rick and Zakzeski, Audra and Melton, Forrest and Johnson, Lee and Rosevelt, Carolyn and Dwyer, John and Jones, Jeanine and Verdin, James P. (2014) Seasonal cultivated and fallow cropland mapping using MODIS-based automated cropland classification algorithm. Journal of Applied Remote Sensing, 8 (1). 083685. ISSN 1931-3195

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Abstract

Increasing drought occurrences and growing populations demand accurate, routine, and consistent cultivated and fallow cropland products to enable water and food security analysis. The overarching goal of this research was to develop and test automated cropland classification algorithm (ACCA) that provide accurate, consistent, and repeatable information on seasonal cultivated as well as seasonal fallow cropland extents and areas based on the Moderate Resolution Imaging Spectroradiometer remote sensing data. Seasonal ACCA development process involves writing series of iterative decision tree codes to separate cultivated and fallow croplands from noncroplands, aiming to accurately mirror reliable reference data sources. A pixel-by-pixel accuracy assessment when compared with the U.S. Department of Agriculture (USDA) cropland data showed, on average, a producer's accuracy of 93% and a user's accuracy of 85% across all months. Further, ACCA-derived cropland maps agreed well with the USDA Farm Service Agency crop acreage-reported data for both cultivated and fallow croplands with R-square values over 0.7 and field surveys with an accuracy of >= 95% for cultivated croplands and >= 76% for fallow croplands. Our results demonstrated the ability of ACCA to generate cropland products, such as cultivated and fallow cropland extents and areas, accurately, automatically, and repeatedly throughout the growing season.

Item Type:	Article
ID number or DOI:	10.1117/1.JRS.8.083685
Keywords:	accuracy assessment; adjusted vegetation index; automated cropland classification algorithm; basin; central great-plains; cropland statistics; cultivated croplands; Distributions; fallow croplands; FOOD security; irrigated areas; landsat imagery; MODIS; ndvi data; time-series; US
Subjects:	Q Science > QA Mathematics S Agriculture > S Agriculture (General)
NAU Depositing Author Academic Status:	Faculty/Staff
Department/Unit:	Research Centers > Merriam-Powell Center for Environmental Research
Date Deposited:	16 Oct 2015 23:10
URI:	http://openknowledge.nau.edu/id/eprint/798

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