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

Bhogendra Mishra,Lorenzo Busetto,Mirco Boschetti,Alice Laborte,Andrew Nelson

doi:10.1016/j.jag.2021.102471

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.

Highlights

Crop calendars report the timing of key agricultural activities and crop development
At the end of this automated matching process, we evaluated the performance of RICA by i) comparing the number of seasons for which a match between RICA and RiceAtlas was found with the number of sea sons reported in RiceAtlas and analysing the matched/non-matched with respect to RiceAtlas seasons (Main, Second, Third), and ii) comparing the start of season (SoS) and end of season (EoS) dates for the seasons for which a match was identified, and computing the coefficient of determination (R2), the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE) between RICA and RiceAtlas SoS and EoS
We report separate results for Japan, and for the Philippines, two countries for which the SoS and EoS dates in RiceAtlas are known to be of good quality based on the underlying data that was collected and the expert analyses conducted when compiling those data for RiceAtlas

Summary

Introduction

Crop calendars report the timing of key agricultural activities and crop development. Contain information only on the timing of crop planting and harvesting for major crops, and report these dates as planting and harvesting windows for large geographic areas (Dimou et al, 2018; FAO, 2010). This is partic ularly true for crop calendars that go beyond national scale (from mul tiple countries up to continental and global coverage). The same review outlines their importance for specific applications such as monitoring crop condition, estimating crop area and harvested production, agricultural policy, emergency planning in the event of disasters. Crop calendars are important layers of in formation for the United Nations Sustainable Development Goal (SDG) target 12.3 - to halve per capita global food waste at the retail and consumer levels and reduce food losses along production and supply chains, including post-harvest losses by 2030 (FAO, 2020a)

Objectives

Methods

Results

Conclusion