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Article

Retrospective Predictions of Rice and Other Crop Production in Madagascar Using Soil Moisture and an NDVI-Based Calendar from 2010–2017

1
Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA 02134, USA
2
Department of Nutrition, Harvard T.H. Chan School of Public Heath, Boston, MA 02115, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2022, 14(5), 1223; https://doi.org/10.3390/rs14051223
Submission received: 22 December 2021 / Revised: 24 February 2022 / Accepted: 24 February 2022 / Published: 2 March 2022
(This article belongs to the Special Issue Advances in Remote Sensing for Crop Monitoring and Yield Estimation)

Abstract

Malagasy subsistence farmers, who comprise 70% of the nearly 26 million people in Madagascar, often face food insecurity because of unreliable food production systems and adverse crop conditions. The 2020–2021 drought in Madagascar, in particular, is associated with an exceptional food crisis, yet we are unaware of peer-reviewed studies that quantitatively link variations in weather and climate to agricultural outcomes for staple crops in Madagascar. In this study, we use historical data to empirically assess the relationship between soil moisture and food production. Specifically, we focus on major staple crops that form the foundation of Malagasy food systems and nutrition, including rice, which accounts for 46% of the average Malagasy caloric intake, as well as cassava, maize, and sweet potato. Available data associated with survey-based crop statistics constrain our analysis to 2010–2017 across four clusters of Malagasy districts. Strong correlations are observed between remotely sensed soil moisture and rice production, ranging between 0.67 to 0.95 depending on the cluster and choice of crop calendar. Predictions are shown to be statistically significant at the 90% confidence level using bootstrapping techniques, as well as through an out-of-sample prediction framework. Soil moisture also shows skill in predicting cassava, maize, and sweet potato production, but only when the months most vulnerable to water stress are isolated. Additional analyses using more survey data, as well as potentially more-refined crop maps and calendars, will be useful for validating and improving soil-moisture-based predictions of yield.
Keywords: soil moisture; crop production; rice production; Madagascar; drought; agriculture soil moisture; crop production; rice production; Madagascar; drought; agriculture
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MDPI and ACS Style

Rigden, A.J.; Golden, C.; Huybers, P. Retrospective Predictions of Rice and Other Crop Production in Madagascar Using Soil Moisture and an NDVI-Based Calendar from 2010–2017. Remote Sens. 2022, 14, 1223. https://doi.org/10.3390/rs14051223

AMA Style

Rigden AJ, Golden C, Huybers P. Retrospective Predictions of Rice and Other Crop Production in Madagascar Using Soil Moisture and an NDVI-Based Calendar from 2010–2017. Remote Sensing. 2022; 14(5):1223. https://doi.org/10.3390/rs14051223

Chicago/Turabian Style

Rigden, Angela J., Christopher Golden, and Peter Huybers. 2022. "Retrospective Predictions of Rice and Other Crop Production in Madagascar Using Soil Moisture and an NDVI-Based Calendar from 2010–2017" Remote Sensing 14, no. 5: 1223. https://doi.org/10.3390/rs14051223

APA Style

Rigden, A. J., Golden, C., & Huybers, P. (2022). Retrospective Predictions of Rice and Other Crop Production in Madagascar Using Soil Moisture and an NDVI-Based Calendar from 2010–2017. Remote Sensing, 14(5), 1223. https://doi.org/10.3390/rs14051223

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