Mapping cropping practices of a sugarcane-based cropping system in Kenya using remote sensing

Over the recent past, there has been a growing concern on the need for mapping cropping practices in order to improve decision-making in the agricultural sector. We developed an original method for mapping cropping practices: crop type and harvest mode, in a sugarcane landscape of western Kenya using remote sensing data. At local scale, a temporal series of 15-m resolution Landsat 8 images was obtained for Kibos sugar management zone over 20 dates (April 2013 to March 2014) to characterize cropping practices. To map the crop type and harvest mode we used ground survey and factory data over 1280 fields, digitized field boundaries, and spectral indices (the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI)) were computed for all Landsat images. The results showed NDVI classified crop type at 83.3% accuracy, while NDWI classified harvest mode at 90% accuracy. The crop map will inform better planning decisions for the sugar industry operations, while the harvest mode map will be used to plan for sensitizations forums on best management and environmental practices.

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Bibliographic Details
Main Authors: Mulianga, Betty, Bégué, Agnès, Clouvel, Pascal, Todoroff, Pierre
Format: article biblioteca
Language:eng
Subjects:F08 - Systèmes et modes de culture, U30 - Méthodes de recherche, F01 - Culture des plantes, E90 - Structure agraire, Saccharum officinarum, télédétection, système de culture, cartographie de l'utilisation des terres, pratique culturale, récolte, Landsat, http://aims.fao.org/aos/agrovoc/c_6727, http://aims.fao.org/aos/agrovoc/c_6498, http://aims.fao.org/aos/agrovoc/c_1971, http://aims.fao.org/aos/agrovoc/c_9000100, http://aims.fao.org/aos/agrovoc/c_2018, http://aims.fao.org/aos/agrovoc/c_3500, http://aims.fao.org/aos/agrovoc/c_36766, http://aims.fao.org/aos/agrovoc/c_4086,
Online Access:http://agritrop.cirad.fr/577980/
http://agritrop.cirad.fr/577980/1/remotesensing-07-14428.pdf
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spelling dig-cirad-fr-5779802024-01-28T23:00:49Z http://agritrop.cirad.fr/577980/ http://agritrop.cirad.fr/577980/ Mapping cropping practices of a sugarcane-based cropping system in Kenya using remote sensing. Mulianga Betty, Bégué Agnès, Clouvel Pascal, Todoroff Pierre. 2015. Remote Sensing, 7 (11) : 14428-14444.https://doi.org/10.3390/rs71114428 <https://doi.org/10.3390/rs71114428> Mapping cropping practices of a sugarcane-based cropping system in Kenya using remote sensing Mulianga, Betty Bégué, Agnès Clouvel, Pascal Todoroff, Pierre eng 2015 Remote Sensing F08 - Systèmes et modes de culture U30 - Méthodes de recherche F01 - Culture des plantes E90 - Structure agraire Saccharum officinarum télédétection système de culture cartographie de l'utilisation des terres pratique culturale récolte Landsat http://aims.fao.org/aos/agrovoc/c_6727 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_1971 http://aims.fao.org/aos/agrovoc/c_9000100 http://aims.fao.org/aos/agrovoc/c_2018 http://aims.fao.org/aos/agrovoc/c_3500 http://aims.fao.org/aos/agrovoc/c_36766 Kenya http://aims.fao.org/aos/agrovoc/c_4086 Over the recent past, there has been a growing concern on the need for mapping cropping practices in order to improve decision-making in the agricultural sector. We developed an original method for mapping cropping practices: crop type and harvest mode, in a sugarcane landscape of western Kenya using remote sensing data. At local scale, a temporal series of 15-m resolution Landsat 8 images was obtained for Kibos sugar management zone over 20 dates (April 2013 to March 2014) to characterize cropping practices. To map the crop type and harvest mode we used ground survey and factory data over 1280 fields, digitized field boundaries, and spectral indices (the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI)) were computed for all Landsat images. The results showed NDVI classified crop type at 83.3% accuracy, while NDWI classified harvest mode at 90% accuracy. The crop map will inform better planning decisions for the sugar industry operations, while the harvest mode map will be used to plan for sensitizations forums on best management and environmental practices. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/577980/1/remotesensing-07-14428.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.3390/rs71114428 10.3390/rs71114428 info:eu-repo/semantics/altIdentifier/doi/10.3390/rs71114428 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.3390/rs71114428
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic F08 - Systèmes et modes de culture
U30 - Méthodes de recherche
F01 - Culture des plantes
E90 - Structure agraire
Saccharum officinarum
télédétection
système de culture
cartographie de l'utilisation des terres
pratique culturale
récolte
Landsat
http://aims.fao.org/aos/agrovoc/c_6727
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_1971
http://aims.fao.org/aos/agrovoc/c_9000100
http://aims.fao.org/aos/agrovoc/c_2018
http://aims.fao.org/aos/agrovoc/c_3500
http://aims.fao.org/aos/agrovoc/c_36766
http://aims.fao.org/aos/agrovoc/c_4086
F08 - Systèmes et modes de culture
U30 - Méthodes de recherche
F01 - Culture des plantes
E90 - Structure agraire
Saccharum officinarum
télédétection
système de culture
cartographie de l'utilisation des terres
pratique culturale
récolte
Landsat
http://aims.fao.org/aos/agrovoc/c_6727
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_1971
http://aims.fao.org/aos/agrovoc/c_9000100
http://aims.fao.org/aos/agrovoc/c_2018
http://aims.fao.org/aos/agrovoc/c_3500
http://aims.fao.org/aos/agrovoc/c_36766
http://aims.fao.org/aos/agrovoc/c_4086
spellingShingle F08 - Systèmes et modes de culture
U30 - Méthodes de recherche
F01 - Culture des plantes
E90 - Structure agraire
Saccharum officinarum
télédétection
système de culture
cartographie de l'utilisation des terres
pratique culturale
récolte
Landsat
http://aims.fao.org/aos/agrovoc/c_6727
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_1971
http://aims.fao.org/aos/agrovoc/c_9000100
http://aims.fao.org/aos/agrovoc/c_2018
http://aims.fao.org/aos/agrovoc/c_3500
http://aims.fao.org/aos/agrovoc/c_36766
http://aims.fao.org/aos/agrovoc/c_4086
F08 - Systèmes et modes de culture
U30 - Méthodes de recherche
F01 - Culture des plantes
E90 - Structure agraire
Saccharum officinarum
télédétection
système de culture
cartographie de l'utilisation des terres
pratique culturale
récolte
Landsat
http://aims.fao.org/aos/agrovoc/c_6727
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_1971
http://aims.fao.org/aos/agrovoc/c_9000100
http://aims.fao.org/aos/agrovoc/c_2018
http://aims.fao.org/aos/agrovoc/c_3500
http://aims.fao.org/aos/agrovoc/c_36766
http://aims.fao.org/aos/agrovoc/c_4086
Mulianga, Betty
Bégué, Agnès
Clouvel, Pascal
Todoroff, Pierre
Mapping cropping practices of a sugarcane-based cropping system in Kenya using remote sensing
description Over the recent past, there has been a growing concern on the need for mapping cropping practices in order to improve decision-making in the agricultural sector. We developed an original method for mapping cropping practices: crop type and harvest mode, in a sugarcane landscape of western Kenya using remote sensing data. At local scale, a temporal series of 15-m resolution Landsat 8 images was obtained for Kibos sugar management zone over 20 dates (April 2013 to March 2014) to characterize cropping practices. To map the crop type and harvest mode we used ground survey and factory data over 1280 fields, digitized field boundaries, and spectral indices (the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI)) were computed for all Landsat images. The results showed NDVI classified crop type at 83.3% accuracy, while NDWI classified harvest mode at 90% accuracy. The crop map will inform better planning decisions for the sugar industry operations, while the harvest mode map will be used to plan for sensitizations forums on best management and environmental practices.
format article
topic_facet F08 - Systèmes et modes de culture
U30 - Méthodes de recherche
F01 - Culture des plantes
E90 - Structure agraire
Saccharum officinarum
télédétection
système de culture
cartographie de l'utilisation des terres
pratique culturale
récolte
Landsat
http://aims.fao.org/aos/agrovoc/c_6727
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_1971
http://aims.fao.org/aos/agrovoc/c_9000100
http://aims.fao.org/aos/agrovoc/c_2018
http://aims.fao.org/aos/agrovoc/c_3500
http://aims.fao.org/aos/agrovoc/c_36766
http://aims.fao.org/aos/agrovoc/c_4086
author Mulianga, Betty
Bégué, Agnès
Clouvel, Pascal
Todoroff, Pierre
author_facet Mulianga, Betty
Bégué, Agnès
Clouvel, Pascal
Todoroff, Pierre
author_sort Mulianga, Betty
title Mapping cropping practices of a sugarcane-based cropping system in Kenya using remote sensing
title_short Mapping cropping practices of a sugarcane-based cropping system in Kenya using remote sensing
title_full Mapping cropping practices of a sugarcane-based cropping system in Kenya using remote sensing
title_fullStr Mapping cropping practices of a sugarcane-based cropping system in Kenya using remote sensing
title_full_unstemmed Mapping cropping practices of a sugarcane-based cropping system in Kenya using remote sensing
title_sort mapping cropping practices of a sugarcane-based cropping system in kenya using remote sensing
url http://agritrop.cirad.fr/577980/
http://agritrop.cirad.fr/577980/1/remotesensing-07-14428.pdf
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AT begueagnes mappingcroppingpracticesofasugarcanebasedcroppingsysteminkenyausingremotesensing
AT clouvelpascal mappingcroppingpracticesofasugarcanebasedcroppingsysteminkenyausingremotesensing
AT todoroffpierre mappingcroppingpracticesofasugarcanebasedcroppingsysteminkenyausingremotesensing
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