@article{fdi:010084298,
  title = {{M}ulti-sensors remote sensing applications for assessing, monitoring, and mapping {NPK} content in soil and crops in {A}frican agricultural land},
  author = {{M}isbah, {K}. and {L}aamrani, {A}. and {K}hechba, {K}. and {D}hiba, {D}. and {C}hehbouni, {A}bdelghani},
  editor = {},
  language = {{ENG}},
  abstract = {{D}emand for agricultural products is increasing as population continues to grow in {A}frica. {T}o attain a higher crop yield while preserving the environment, appropriate management of macronutrients (i.e., nitrogen ({N}), phosphorus ({P}) and potassium ({K})) and crops are of critical prominence. {T}his paper aims to review the state of art of the use of remote sensing in soil agricultural applications, especially in monitoring {NPK} availability for widely grown crops in {A}frica. {I}n this study, we conducted a substantial literature review of the use of airborne imaging technology (e.g., different platforms and sensors), methods available for processing and analyzing spectral information, and advances of these applications in farming practices by the {A}frican scientific community. {H}ere we aimed to identify knowledge gaps in this field and challenges related to the acquisition, processing, and analysis of hyperspectral imagery for soil agriculture investigations. {T}o do so, publications over the past 10 years (i.e., 2008-2021) in hyperspectral imaging technology and applications in monitoring macronutrients status for crops were reviewed. {I}n this study, the imaging platforms and sensors, as well as the different methods of processing encountered across the literature, were investigated and their benefit for {NPK} assessment were highlighted. {F}urthermore, we identified and selected particular spectral regions, bands, or features that are most sensitive to describe {NPK} content (both in crop and soil) that allowed to characterize {NPK}. {I}n this review, we proposed a hyperspectral data-based research protocol to quantify variability of {NPK} in soil and crop at the field scale for the sake of optimizing fertilizers application. {W}e believe that this review will contribute promoting the adoption of hyperspectral technology (i.e., imaging and spectroscopy) for the optimization of soil {NPK} investigation, mapping, and monitoring in many {A}frican countries.},
  keywords = {hyperspectral imaging ; agricultural soils ; variable rate fertilization ; fertigation ; precision agriculture ; machine learning ; remote sensing ; crop yield ; {AFRIQUE} ; {ALGERIE} ; {BURKINA} {FASO} ; {EGYPTE} ; {KENYA} ; {MADAGASCAR} ; {MALAWI} ; {MAROC} ; {NIGERIA} ; {AFRIQUE} {DU} {SUD} ; {TANZANIE} ; {ZIMBABWE}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {14},
  numero = {1},
  pages = {81 [17 p.]},
  year = {2022},
  DOI = {10.3390/rs14010081},
  URL = {https://www.documentation.ird.fr/hor/fdi:010084298},
}