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

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 var...

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Autores principales: Mishra, Bhogendra, Busetto, Lorenzo, Boschetti, Mirco, Laborte, Alice, Nelson, Andrew
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://hdl.handle.net/10568/164153
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author Mishra, Bhogendra
Busetto, Lorenzo
Boschetti, Mirco
Laborte, Alice
Nelson, Andrew
author_browse Boschetti, Mirco
Busetto, Lorenzo
Laborte, Alice
Mishra, Bhogendra
Nelson, Andrew
author_facet Mishra, Bhogendra
Busetto, Lorenzo
Boschetti, Mirco
Laborte, Alice
Nelson, Andrew
author_sort Mishra, Bhogendra
collection Repository of Agricultural Research Outputs (CGSpace)
description 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
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spelling CGSpace1641532024-12-20T06:19:39Z RICA: A rice crop calendar for Asia based on MODIS multi year data Mishra, Bhogendra Busetto, Lorenzo Boschetti, Mirco Laborte, Alice Nelson, Andrew management monitoring policy and law computers in earth sciences earth-surface processes global and planetary change 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 2021-12 2024-12-19T12:53:31Z 2024-12-19T12:53:31Z Journal Article https://hdl.handle.net/10568/164153 en Open Access Elsevier Mishra, Bhogendra; Busetto, Lorenzo; Boschetti, Mirco; Laborte, Alice and Nelson, Andrew. 2021. RICA: A rice crop calendar for Asia based on MODIS multi year data. International Journal of Applied Earth Observation and Geoinformation, Volume 103 p. 102471
spellingShingle management
monitoring
policy and law
computers in earth sciences
earth-surface processes
global and planetary change
Mishra, Bhogendra
Busetto, Lorenzo
Boschetti, Mirco
Laborte, Alice
Nelson, Andrew
RICA: A rice crop calendar for Asia based on MODIS multi year data
title RICA: A rice crop calendar for Asia based on MODIS multi year data
title_full RICA: A rice crop calendar for Asia based on MODIS multi year data
title_fullStr RICA: A rice crop calendar for Asia based on MODIS multi year data
title_full_unstemmed RICA: A rice crop calendar for Asia based on MODIS multi year data
title_short RICA: A rice crop calendar for Asia based on MODIS multi year data
title_sort rica a rice crop calendar for asia based on modis multi year data
topic management
monitoring
policy and law
computers in earth sciences
earth-surface processes
global and planetary change
url https://hdl.handle.net/10568/164153
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