Detecting spatiotemporal changes of corn developmental stages in the U.S. corn belt using MODIS WDRVI data

Toshihiro Sakamoto, Brian D. Wardlow, Anatoly A. Gitelson

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

The dates of crop developmental stages are important variables for many applications including assessment of the impact of abnormal weather on crop yield. Time-series 250-m vegetation-index (VI) data acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide valuable information for monitoring the spatiotemporal changes of corn growth across large geographic areas. The goal of this study is to evaluate the performance of a new crop phenology detection method, namely, two-step filtering (TSF), for revealing the spatiotemporal pattern of specific corn developmental stages (early vegetative: V2.5; silking: R1; dent: R5; mature: R6) over an eight-year period (20012008) across Iowa, Illinois, and Indiana using MODIS-derived Wide Dynamic Range VI data. Weekly crop progress reports produced by the U.S. Department of Agriculture National Agricultural Statistics Service (NASS) were used to assess the accuracy of TSF-based estimates of corn developmental stages. The results showed that the corn developmental stages could be estimated with high accuracy (the root mean squared error ranged from 4.1 to 5.5 days, the determination coefficient ranged from 0.66 to 0.84, and the coefficient of variation ranged from 2.1% to 3.7%) based on NASS-derived statistics on an agricultural statistics district level. In particular, the annual changes in the spatiotemporal patterns of the estimated silking stage had a high level of agreement with those of the NASS-derived statistics. These results suggested that the TSF method could provide local-scale information of corn phenological stages, which had an advantage over the NASS-derived statistics particularly in terms of the spatial resolution.

Original languageEnglish (US)
Article number5682035
Pages (from-to)1926-1936
Number of pages11
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume49
Issue number6 PART 1
DOIs
StatePublished - Jun 1 2011

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Keywords

  • Agriculture
  • optical imaging
  • remote sensing
  • time series
  • vegetation mapping

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

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