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2021-09-05Zeitschriftenartikel DOI: 10.3390/rs13173523
Mapping Crop Types and Cropping Systems in Nigeria with Sentinel-2 Imagery
dc.contributor.authorIbrahim, Esther Shupel
dc.contributor.authorRufin, Philippe
dc.contributor.authorNill, Leon
dc.contributor.authorKamali, Bahareh
dc.contributor.authorNendel, Claas
dc.contributor.authorHostert, Patrick
dc.date.accessioned2021-10-13T12:48:05Z
dc.date.available2021-10-13T12:48:05Z
dc.date.issued2021-09-05none
dc.date.updated2021-10-01T13:29:29Z
dc.identifier.urihttp://edoc.hu-berlin.de/18452/24186
dc.description.abstractReliable crop type maps from satellite data are an essential prerequisite for quantifying crop growth, health, and yields. However, such maps do not exist for most parts of Africa, where smallholder farming is the dominant system. Prevalent cloud cover, small farm sizes, and mixed cropping systems pose substantial challenges when creating crop type maps for sub-Saharan Africa. In this study, we provide a mapping scheme based on freely available Sentinel-2A/B (S2) time series and very high-resolution SkySat data to map the main crops—maize and potato—and intercropping systems including these two crops on the Jos Plateau, Nigeria. We analyzed the spectral-temporal behavior of mixed crop classes to improve our understanding of inter-class spectral mixing. Building on the Framework for Operational Radiometric Correction for Environmental monitoring (FORCE), we preprocessed S2 time series and derived spectral-temporal metrics from S2 spectral bands for the main temporal cropping windows. These STMs were used as input features in a hierarchical random forest classification. Our results provide the first wall-to-wall crop type map for this key agricultural region of Nigeria. Our cropland identification had an overall accuracy of 84%, while the crop type map achieved an average accuracy of 72% for the five relevant crop classes. Our crop type map shows distinctive regional variations in the distribution of crop types. Maize is the dominant crop, followed by mixed cropping systems, including maize–cereals and potato–maize cropping; potato was found to be the least prevalent class. Plot analyses based on a sample of 1166 fields revealed largely homogeneous mapping patterns, demonstrating the effectiveness of our classification system also for intercropped classes, which are temporally and spatially highly heterogeneous. Moreover, we found that small field sizes were dominant in all crop types, regardless of whether or not intercropping was used. Maize–legume and maize exhibited the largest plots, with an area of up to 3 ha and slightly more than 10 ha, respectively; potato was mainly cultivated on fields smaller than 0.5 ha and only a few plots were larger than 1 ha. Besides providing the first spatially explicit map of cropping practices in the core production area of the Jos Plateau, Nigeria, the study also offers guidance for the creation of crop type maps for smallholder-dominated systems with intercropping. Critical temporal windows for crop type differentiation will enable the creation of mapping approaches in support of future smart agricultural practices for aspects such as food security, early warning systems, policies, and extension services.eng
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectspectral-temporal metricseng
dc.subjecttime serieseng
dc.subjectsmallholder agricultureeng
dc.subjectintercroppingeng
dc.subjectSkySateng
dc.subjectclassificationeng
dc.subjectrandom foresteng
dc.subjectmaizeeng
dc.subjectpotatoeng
dc.subjectsub-Saharan Africaeng
dc.subject.ddc630 Landwirtschaft und verwandte Bereichenone
dc.titleMapping Crop Types and Cropping Systems in Nigeria with Sentinel-2 Imagerynone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/24186-9
dc.identifier.doi10.3390/rs13173523none
dc.identifier.doihttp://dx.doi.org/10.18452/23526
dc.type.versionpublishedVersionnone
local.edoc.container-titleRemote sensingnone
local.edoc.pages24none
local.edoc.anmerkungThis article was supported by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin.none
local.edoc.type-nameZeitschriftenartikel
local.edoc.institutionMathematisch-Naturwissenschaftliche Fakultätnone
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-publisher-nameMDPInone
local.edoc.container-publisher-placeBaselnone
local.edoc.container-volume13none
local.edoc.container-issue17none
dc.description.versionPeer Reviewednone
local.edoc.container-articlenumber3523none
dc.identifier.eissn2072-4292
local.edoc.affiliationIbrahim, Esther Shupel; 1Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany; philippe.rufin@geo.hu-berlin.de (P.R.); leon.nill@hu-berlin.de (L.N.); patrick.hostert@geo.hu-berlin.de (P.H.)none
local.edoc.affiliationRufin, Philippe; 1Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany; philippe.rufin@geo.hu-berlin.de (P.R.); leon.nill@hu-berlin.de (L.N.); patrick.hostert@geo.hu-berlin.de (P.H.)none
local.edoc.affiliationNill, Leon; 1Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany; philippe.rufin@geo.hu-berlin.de (P.R.); leon.nill@hu-berlin.de (L.N.); patrick.hostert@geo.hu-berlin.de (P.H.)none
local.edoc.affiliationKamali, Bahareh; 2Leibniz Centre for Agricultural Landscape Research, Eberswalder Straße 84, 15374 Müncheberg, Germany; bkamali@uni-bonn.de (B.K.); Claas.Nendel@zalf.de (C.N.)none
local.edoc.affiliationNendel, Claas; 2Leibniz Centre for Agricultural Landscape Research, Eberswalder Straße 84, 15374 Müncheberg, Germany; bkamali@uni-bonn.de (B.K.); Claas.Nendel@zalf.de (C.N.)none
local.edoc.affiliationHostert, Patrick; 1Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany; philippe.rufin@geo.hu-berlin.de (P.R.); leon.nill@hu-berlin.de (L.N.); patrick.hostert@geo.hu-berlin.de (P.H.)none

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