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

International Journal of Applied Earth Observations and Geoinformation

Lorenzo Busetto¹  Bhogendra Mishra²  Mirco Boschetti³  Alice Laborte³  Andrew Nelson⁴ 

[1] Science Hub, Kathmandu, Nepal;Department of Natural Resources, ITC - Faculty of Geo-Information Science and Earth Observation of the University of Twente, the Netherlands;Institute for Electromagnetic Sensing of the Environment, Italian National Research Council, Via Bassini 15, Milan 20133, Italy;International Rice Research Institute, Los Baños, Laguna, Philippines;

关键词: Phenology;    PhenoRice;    Agriculture;    Crop monitoring;    Earth observation;    Food security;   

DOI  :  

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown