Drought monitoring of some Moroccan agricultural areas: Settat and Meknes using remote sensing techniques and a soil moisture-based drought index

Laachrate, Hibatoullah; Fadil, Abdelhamid; Ghafiri, Abdessamad

doi:10.1109/morgeo49228.2020.9121917

Cited by 3 publications

(3 citation statements)

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“…The PhenoMA is another high-throughput phenotyping platform currently installed in Benguerir ( Quahir et al., 2022 ). Field phenotyping using various remote sensing techniques has been deployed for drought monitoring ( Bijaber et al., 2018 ; Bouras et al., 2020 ; Laachrate et al., 2020 ), and grain yield prediction ( Belmahi et al., 2023 ).…”

Section: Overview Of the Status Of Field Phenotyping In Africamentioning

confidence: 99%

Field phenotyping for African crops: overview and perspectives

Cudjoe,

Virlet,

Castle

et al. 2023

Front. Plant Sci.

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Improvements in crop productivity are required to meet the dietary demands of the rapidly-increasing African population. The development of key staple crop cultivars that are high-yielding and resilient to biotic and abiotic stresses is essential. To contribute to this objective, high-throughput plant phenotyping approaches are important enablers for the African plant science community to measure complex quantitative phenotypes and to establish the genetic basis of agriculturally relevant traits. These advances will facilitate the screening of germplasm for optimum performance and adaptation to low-input agriculture and resource-constrained environments. Increasing the capacity to investigate plant function and structure through non-invasive technologies is an effective strategy to aid plant breeding and additionally may contribute to precision agriculture. However, despite the significant global advances in basic knowledge and sensor technology for plant phenotyping, Africa still lags behind in the development and implementation of these systems due to several practical, financial, geographical and political barriers. Currently, field phenotyping is mostly carried out by manual methods that are prone to error, costly, labor-intensive and may come with adverse economic implications. Therefore, improvements in advanced field phenotyping capabilities and appropriate implementation are key factors for success in modern breeding and agricultural monitoring. In this review, we provide an overview of the current state of field phenotyping and the challenges limiting its implementation in some African countries. We suggest that the lack of appropriate field phenotyping infrastructures is impeding the development of improved crop cultivars and will have a detrimental impact on the agricultural sector and on food security. We highlight the prospects for integrating emerging and advanced low-cost phenotyping technologies into breeding protocols and characterizing crop responses to environmental challenges in field experimentation. Finally, we explore strategies for overcoming the barriers and maximizing the full potential of emerging field phenotyping technologies in African agriculture. This review paper will open new windows and provide new perspectives for breeders and the entire plant science community in Africa.

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Section: Overview Of the Status Of Field Phenotyping In Africamentioning

confidence: 99%

Field phenotyping for African crops: overview and perspectives

Cudjoe,

Virlet,

Castle

et al. 2023

Front. Plant Sci.

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“…MIDIwasinitiallyusedinsemi-aridregionsinChina(Zhang&Jia,2013)whichareregionswitha climateverysimilartotheMoroccanonesince93%oftheterritoryisclassifiedasasemi-aridto aridclimate (Balaghietal.,2007).ToestimatetheMIDIindexthreeotherindiceswerecalculated PCI, SMCI, and TCI using the same approach chosen by Laachrate et al (2020b)…”

Section: Microwave Integrated Drought Index (Midi)mentioning

confidence: 99%

“…Inthestudy,the2015-2016growingseasondroughtwastrackedforMeknesandSettat.Another study (Laachrateetal.,2020b)hasalsotrackedthesamedroughteventforthesameregionsbutusing anotherdroughtindex:MicrowaveIntegratedDroughtIndex(MIDI)withfourgeneratingapproaches ofdroughtmaps.Theaimofthisstudywastocomparetheresultsofthefourapproachestothose ofBijaberetal.2018tochoosethebestapproachtoMIDIcalculationanddroughtclassification.In thiswork,agriculturaldroughtwasassessedforMoroccousingdifferentdroughtindices.Drought indices defined as: "typically computed numerical representations of drought severity" (World MeteorologicalOrganization(WMO)&GlobalWaterPartnership(GWP),2016)arepowerfultools indroughtassessment.Theyprovideusefulinformationaboutdroughtcharacteristicsandsimplify complexrelationshipsusinghydrometeorologicalandclimaticparametersfordifferentapplications (WMO&GWP,2016).Anoverviewofthemaindroughtindicescanbefoundin"Handbookof droughtindicatorsandindices" (WMO&GWP,2016).Manydroughtindicescanbeused,butin thisstudythreecompositeindiceswerechosen:CompositeDroughtIndicator(CDI),SoilMoisture AgriculturalDroughtIndex(SMADI),andMIDI.Compositeindiceswereusedratherthansimple indicestohaveabetterdroughtassessmentbasedondifferentparametersofthehydrologicalcycle. TheseindiceshaveincommontheuseofSoilMoisture(SM)whichisanimportantparameterfor such extreme events (Laachrate et al, 2020b) (especially agricultural droughts that are linked to SMshortage),andfloods (Laachrateetal.,2019).OtherapplicationsofSMcanbefoundinthe reviewpaper:"SoilMoistureRetrievalUsingMicrowaveRemoteSensing:ReviewofTechniques andApplications"(Laachrateetal.,2020a)includinghydrologyandLandSurfaceModels,hazards, climatechange,andagriculture.SMdatasetsusedinthisstudyweretakenfromtheGoogleEarth Engine(GEE)datacatalogbasedontheSoilMoistureandOceanSalinity(SMOS)mission.This missionisaboutasatellitelaunchedin2009bytheEuropeanSpatialAgencywiththeaimofretrieving SMandoceansalinityparameters.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Drought Using Earth Observation Data and Cloud Computing in Morocco for 2010-2020

Laachrate

Fadil

2022

International Journal of Applied Geospatial Research

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Drought is an extreme event that has hit several countries in the world including Morocco. The aim of this research was to assess drought in Morocco with a view to providing information for planning and management of droughts. For this, three drought indices were chosen: Combined Drought Indicator (CDI), Soil Moisture Agricultural Drought Index (SMADI), and Microwave Integrated Drought Index (MIDI). Drought monitor was done during the growing seasons of 2010-2020 using Earth Observation data and cloud computing with the mapping of the drought indices and their inter-comparing via Pearson correlation. The main drought events were tracked and drought characteristics analyzed. Seven drought years were tracked for regions of cereal production. CDI and MIDI were very well correlated, whereas SMADI showed poor correlation with CDI and MIDI. Validation of results was done by comparing our results with another study for the 2015-2016 drought event and comparing yearly precipitation with the long-term average. An Earth Engine App of the three indices was published to make public drought maps.

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