Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands

To support improved rangeland resource management and monitoring for nomadic pastoralists in northern Kenya, we used a task-based mobile application to incentivize pastoralists provide more than 100,000 surveys containing information on local rangeland, water and livestock resources. In this contrib...

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Detalles Bibliográficos
Autores principales: Fava, Francesco P., Jensen, Nathaniel D., Oto, Lucas de, Mude, Andrew G.
Formato: Ponencia
Lenguaje:Inglés
Publicado: International Livestock Research Institute 2018
Materias:
Acceso en línea:https://hdl.handle.net/10568/97610
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author Fava, Francesco P.
Jensen, Nathaniel D.
Oto, Lucas de
Mude, Andrew G.
author_browse Fava, Francesco P.
Jensen, Nathaniel D.
Mude, Andrew G.
Oto, Lucas de
author_facet Fava, Francesco P.
Jensen, Nathaniel D.
Oto, Lucas de
Mude, Andrew G.
author_sort Fava, Francesco P.
collection Repository of Agricultural Research Outputs (CGSpace)
description To support improved rangeland resource management and monitoring for nomadic pastoralists in northern Kenya, we used a task-based mobile application to incentivize pastoralists provide more than 100,000 surveys containing information on local rangeland, water and livestock resources. In this contribution we explore the potential of combining this information with remote sensing data for improved characterization of rangeland resource use and accessibility through integration of local socio-ecological knowledge into land cover mapping methods.
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publishDate 2018
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publisherStr International Livestock Research Institute
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spelling CGSpace976102023-02-15T10:51:56Z Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands Fava, Francesco P. Jensen, Nathaniel D. Oto, Lucas de Mude, Andrew G. data livestock rangelands pastoralism To support improved rangeland resource management and monitoring for nomadic pastoralists in northern Kenya, we used a task-based mobile application to incentivize pastoralists provide more than 100,000 surveys containing information on local rangeland, water and livestock resources. In this contribution we explore the potential of combining this information with remote sensing data for improved characterization of rangeland resource use and accessibility through integration of local socio-ecological knowledge into land cover mapping methods. 2018-10-03 2018-10-09T14:02:36Z 2018-10-09T14:02:36Z Presentation https://hdl.handle.net/10568/97610 en Open Access application/vnd.ms-powerpoint International Livestock Research Institute Fava, F., Jensen, N., Oto, L. de and Mude, A. 2018. Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands. Presented at the CGIAR Platform for Big Data in Agriculture Convention, Nairobi, 3-5 October 2018. Nairobi, Kenya: ILRI.
spellingShingle data
livestock
rangelands
pastoralism
Fava, Francesco P.
Jensen, Nathaniel D.
Oto, Lucas de
Mude, Andrew G.
Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands
title Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands
title_full Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands
title_fullStr Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands
title_full_unstemmed Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands
title_short Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands
title_sort integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands
topic data
livestock
rangelands
pastoralism
url https://hdl.handle.net/10568/97610
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AT otolucasde integratinglocalcrowdsourcedandremotelysenseddatatocharacterizerangelandresourceuseinextensivepasturelands
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