TY - JOUR
T1 - RICA
T2 - A rice crop calendar for Asia based on MODIS multi year data
AU - Mishra, Bhogendra
AU - Busetto, Lorenzo
AU - Boschetti, Mirco
AU - Laborte, Alice
AU - Nelson, A.
N1 - Funding Information:
During the final stages of this manuscript, our co?author, colleague, and friend Dr Lorenzo Busetto suddenly and unexpectedly passed away. We mourn this loss, both personally and to science. We dedicate this work to him. The authors declare no conflict of interest. Funding statement. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Data. Data (shapefile and csv file) have been posted at https://figshare.com/s/615c7ab2aa8c9e5dc9ba with a reserved DOI 10.4121/13468929.
Publisher Copyright:
© 2021 The Authors
PY - 2021/12/1
Y1 - 2021/12/1
N2 - 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.
AB - 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.
KW - Phenology
KW - PhenoRice
KW - Agriculture
KW - Crop monitoring
KW - Earth observation
KW - Food security
KW - ITC-ISI-JOURNAL-ARTICLE
KW - ITC-GOLD
KW - UT-Gold-D
UR - https://figshare.com/s/615c7ab2aa8c9e5dc9ba
UR - https://ars.els-cdn.com/content/image/1-s2.0-S0303243421001781-mmc1.docx
UR - https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2021/isi/nelson_ric.pdf
U2 - 10.1016/j.jag.2021.102471
DO - 10.1016/j.jag.2021.102471
M3 - Article
SN - 0303-2434
VL - 103
JO - International Journal of Applied Earth Observation and Geoinformation
JF - International Journal of Applied Earth Observation and Geoinformation
M1 - 102471
ER -
