Estimating Yields of Household Fields in Rural Subsistence Farming Systems to Study Food Security in Burkina Faso

<b>:</b> Climate change has an increasing impact on food security and child nutrition, particularly among rural smallholder farmers in sub-Saharan Africa. Their limited resources and rainfall dependent farming practices make them sensitive to climate change-related effects. Data and rese...

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Main Authors: Isabel G. Karst, Isabel Mank, Issouf Traoré, Raissa Sorgho, Kim-Jana Stückemann, Séraphin Simboro, Ali Sié, Jonas Franke, Rainer Sauerborn
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/11/1717
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spelling doaj-fa591ff14fb5423eb38e1b1efab8ccf42020-11-25T02:13:43ZengMDPI AGRemote Sensing2072-42922020-05-01121717171710.3390/rs12111717Estimating Yields of Household Fields in Rural Subsistence Farming Systems to Study Food Security in Burkina FasoIsabel G. Karst0Isabel Mank1Issouf Traoré2Raissa Sorgho3Kim-Jana Stückemann4Séraphin Simboro5Ali Sié6Jonas Franke7Rainer Sauerborn8Remote Sensing Solutions (RSS) GmbH, Dingolfingerstr. 9, 81673 Munich, GermanyHeidelberg Institute of Global Health (HIGH), Faculty of Medicine, Heidelberg University, Im Neuenheimer Feld 130.3, 69120 Heidelberg, GermanyCentre de Recherche en Santé de Nouna (CRSN), Institut National de Santé Publique (INSP), P.O. Box 02 Nouna, Burkina FasoHeidelberg Institute of Global Health (HIGH), Faculty of Medicine, Heidelberg University, Im Neuenheimer Feld 130.3, 69120 Heidelberg, GermanyInstitute of Computer Science, University of Osnabrück, Wachsbleiche 27, 49090 Osnabrück, GermanyCentre de Recherche en Santé de Nouna (CRSN), Institut National de Santé Publique (INSP), P.O. Box 02 Nouna, Burkina FasoCentre de Recherche en Santé de Nouna (CRSN), Institut National de Santé Publique (INSP), P.O. Box 02 Nouna, Burkina FasoRemote Sensing Solutions (RSS) GmbH, Dingolfingerstr. 9, 81673 Munich, GermanyHeidelberg Institute of Global Health (HIGH), Faculty of Medicine, Heidelberg University, Im Neuenheimer Feld 130.3, 69120 Heidelberg, Germany<b>:</b> Climate change has an increasing impact on food security and child nutrition, particularly among rural smallholder farmers in sub-Saharan Africa. Their limited resources and rainfall dependent farming practices make them sensitive to climate change-related effects. Data and research linking yield, human health, and nutrition are scarce but can provide a basis for adaptation and risk management strategies. In support of studies on child undernutrition in Burkina Faso, this study analyzed the potential of remote sensing-based yield estimates at household level. Multi-temporal Sentinel-2 data from the growing season 2018 were used to model yield of household fields (median 1.4 hectares (ha), min 0.01 ha, max 12.6 ha) for the five most prominent crops in the Nouna Health and Demographic Surveillance (HDSS) area in Burkina Faso. Based on monthly metrics of vegetation indices (VIs) and in-situ harvest measurements from an extensive field survey, yield prediction models for different crops of high dietary importance (millet, sorghum, maize, and beans) were successfully generated producing R² between 0.4 and 0.54 (adj. R² between 0.32 and 0.5). The models were spatially applied and resulted in a yield estimation map at household level, enabling predictions of up to 2 months prior to harvest. The map links yield on a 10-m spatial resolution to households and consequently can display potential food insecurity. The results highlight the potential for satellite imagery to provide yield predictions of smallholder fields and are discussed in the context of health-related studies such as child undernutrition and food security in rural Africa under climate change.https://www.mdpi.com/2072-4292/12/11/1717food cropschild nutritionremote sensingSentinel-2vegetation index metricsWest Africa
collection DOAJ
language English
format Article
sources DOAJ
author Isabel G. Karst
Isabel Mank
Issouf Traoré
Raissa Sorgho
Kim-Jana Stückemann
Séraphin Simboro
Ali Sié
Jonas Franke
Rainer Sauerborn
spellingShingle Isabel G. Karst
Isabel Mank
Issouf Traoré
Raissa Sorgho
Kim-Jana Stückemann
Séraphin Simboro
Ali Sié
Jonas Franke
Rainer Sauerborn
Estimating Yields of Household Fields in Rural Subsistence Farming Systems to Study Food Security in Burkina Faso
Remote Sensing
food crops
child nutrition
remote sensing
Sentinel-2
vegetation index metrics
West Africa
author_facet Isabel G. Karst
Isabel Mank
Issouf Traoré
Raissa Sorgho
Kim-Jana Stückemann
Séraphin Simboro
Ali Sié
Jonas Franke
Rainer Sauerborn
author_sort Isabel G. Karst
title Estimating Yields of Household Fields in Rural Subsistence Farming Systems to Study Food Security in Burkina Faso
title_short Estimating Yields of Household Fields in Rural Subsistence Farming Systems to Study Food Security in Burkina Faso
title_full Estimating Yields of Household Fields in Rural Subsistence Farming Systems to Study Food Security in Burkina Faso
title_fullStr Estimating Yields of Household Fields in Rural Subsistence Farming Systems to Study Food Security in Burkina Faso
title_full_unstemmed Estimating Yields of Household Fields in Rural Subsistence Farming Systems to Study Food Security in Burkina Faso
title_sort estimating yields of household fields in rural subsistence farming systems to study food security in burkina faso
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-05-01
description <b>:</b> Climate change has an increasing impact on food security and child nutrition, particularly among rural smallholder farmers in sub-Saharan Africa. Their limited resources and rainfall dependent farming practices make them sensitive to climate change-related effects. Data and research linking yield, human health, and nutrition are scarce but can provide a basis for adaptation and risk management strategies. In support of studies on child undernutrition in Burkina Faso, this study analyzed the potential of remote sensing-based yield estimates at household level. Multi-temporal Sentinel-2 data from the growing season 2018 were used to model yield of household fields (median 1.4 hectares (ha), min 0.01 ha, max 12.6 ha) for the five most prominent crops in the Nouna Health and Demographic Surveillance (HDSS) area in Burkina Faso. Based on monthly metrics of vegetation indices (VIs) and in-situ harvest measurements from an extensive field survey, yield prediction models for different crops of high dietary importance (millet, sorghum, maize, and beans) were successfully generated producing R² between 0.4 and 0.54 (adj. R² between 0.32 and 0.5). The models were spatially applied and resulted in a yield estimation map at household level, enabling predictions of up to 2 months prior to harvest. The map links yield on a 10-m spatial resolution to households and consequently can display potential food insecurity. The results highlight the potential for satellite imagery to provide yield predictions of smallholder fields and are discussed in the context of health-related studies such as child undernutrition and food security in rural Africa under climate change.
topic food crops
child nutrition
remote sensing
Sentinel-2
vegetation index metrics
West Africa
url https://www.mdpi.com/2072-4292/12/11/1717
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