RICA: A rice crop calendar for Asia based on MODIS multi year data

Bhogendra Mishra, Lorenzo Busetto, Mirco Boschetti, Alice Laborte, A. Nelson

Research output: Contribution to journalArticleAcademicpeer-review

22 Citations (Scopus)
354 Downloads (Pure)

Abstract

Information on when and where rice is planted and harvested is important for crop management under a changing climate and for monitoring crop production for early warning and market information systems. The diversity of plant genetic, crop management, and environmental conditions leads to a wide variation in the number of rice crops per year and the dates of crop establishment and harvesting across Asia. Asia-wide rice crop calendars exist (e.g., RiceAtlas) but are based on heterogeneous data sources with varying levels of detail and are challenging to update. Earth observations can contribute to consistent and replicable crop calendars. Here we demonstrate and validate a method for generating a rice crop calendar across Asia. Our analysis at administrative unit-level is based on pixel-level analysis with the PhenoRice algorithm using MODIS imagery (2003–16) to estimate start of season (SoS) and end of season (EoS) dates. PhenoRice outputs were post-processed to generate representative statistics on the number of rice crop seasons per year and their SoS/EoS dates per administrative unit across Asia, called RICA (a RIce crop Calendar for Asia). RICA SoS and EoS dates across all seasons correlated strongly with RiceAtlas crop establishment and harvesting dates (R2 of 0.88 and 0.82 respectively, n = 1,186). The mean absolute errors were around 26 and 33 days for SoS and EoS, respectively. A detailed assessment in the Philippines where data in RiceAtlas are particularly accurate had even better results (R2 of 0.93 and 0.85 respectively, n = 131). Comparisons to other published rice calendars also suggested that RICA captured rice cropping season dates well. Our study results in a unique and validated method to estimate rice crop calendar information on continental scale from remote sensing data.
Original languageEnglish
Article number102471
JournalInternational Journal of Applied Earth Observation and Geoinformation
Volume103
Early online date3 Sept 2021
DOIs
Publication statusPublished - 1 Dec 2021

Keywords

  • Phenology
  • PhenoRice
  • Agriculture
  • Crop monitoring
  • Earth observation
  • Food security
  • ITC-ISI-JOURNAL-ARTICLE
  • ITC-GOLD
  • UT-Gold-D

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