Monitoring crop phenology using a smartphone based near-surface remote sensing approach
Smallholder farmers play a critical role in supporting food security in developing countries. Monitoring crop phenology and disturbances to crop growth is critical in strengthening farmers’ ability to manage production risks. This study assesses the feasibility of using crowdsourced near-surface rem...
| Autores principales: | , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2019
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/145446 |
| _version_ | 1855539696432578560 |
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| author | Hufkens, Koen Melaas, Eli K. Mann, Michael L. Foster, Timothy Ceballos, Francisco Robles, Miguel Kramer, Berber |
| author_browse | Ceballos, Francisco Foster, Timothy Hufkens, Koen Kramer, Berber Mann, Michael L. Melaas, Eli K. Robles, Miguel |
| author_facet | Hufkens, Koen Melaas, Eli K. Mann, Michael L. Foster, Timothy Ceballos, Francisco Robles, Miguel Kramer, Berber |
| author_sort | Hufkens, Koen |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Smallholder farmers play a critical role in supporting food security in developing countries. Monitoring crop phenology and disturbances to crop growth is critical in strengthening farmers’ ability to manage production risks. This study assesses the feasibility of using crowdsourced near-surface remote sensing imagery to monitor winter wheat phenology and identify damage events in northwest India. In particular, we demonstrate how streams of pictures of individual smallholder fields, taken using inexpensive smartphones, can be used to quantify important phenological stages in agricultural crops, specifically the wheat heading phase and how it can be used to detect lodging events, a major cause of crop damage globally. Near-surface remote sensing offers granular visual field data, providing detailed information on the timing of key developmental phases of winter wheat and crop growth disturbances that are not registered by common satellite remote sensing vegetation indices or national crop cut surveys. This illustrates the potential of near-surface remote sensing as a scalable platform for collecting high-resolution plot-specific data that can be used in supporting crop modeling, extension and insurance schemes to increase resilience to production risk and enhance food security in smallholder agricultural systems. |
| format | Journal Article |
| id | CGSpace145446 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1454462025-12-08T10:11:39Z Monitoring crop phenology using a smartphone based near-surface remote sensing approach Hufkens, Koen Melaas, Eli K. Mann, Michael L. Foster, Timothy Ceballos, Francisco Robles, Miguel Kramer, Berber insurance lodging phenology remote sensing winter wheat smallholders agricultural productivity crop modelling Smallholder farmers play a critical role in supporting food security in developing countries. Monitoring crop phenology and disturbances to crop growth is critical in strengthening farmers’ ability to manage production risks. This study assesses the feasibility of using crowdsourced near-surface remote sensing imagery to monitor winter wheat phenology and identify damage events in northwest India. In particular, we demonstrate how streams of pictures of individual smallholder fields, taken using inexpensive smartphones, can be used to quantify important phenological stages in agricultural crops, specifically the wheat heading phase and how it can be used to detect lodging events, a major cause of crop damage globally. Near-surface remote sensing offers granular visual field data, providing detailed information on the timing of key developmental phases of winter wheat and crop growth disturbances that are not registered by common satellite remote sensing vegetation indices or national crop cut surveys. This illustrates the potential of near-surface remote sensing as a scalable platform for collecting high-resolution plot-specific data that can be used in supporting crop modeling, extension and insurance schemes to increase resilience to production risk and enhance food security in smallholder agricultural systems. 2019-02-15 2024-06-21T09:04:31Z 2024-06-21T09:04:31Z Journal Article https://hdl.handle.net/10568/145446 en https://doi.org/10.2499/p15738coll2.133534 https://doi.org/10.1088/1748-9326/ab5ebb https://doi.org/10.3390/rs13050924 https://doi.org/10.23846/TW13FE11 https://doi.org/10.2499/p15738coll2.134751 https://doi.org/10.2499/p15738coll2.134917 https://doi.org/10.2499/p15738coll2.134941 Open Access Elsevier Hufkens, Koen; Melaas, Eli K.; Mann, Michael L.; Foster, Timothy; Ceballos, Francisco; Robles, Miguel; and Kramer, Berber. 2019. Monitoring crop phenology using a smartphone based near-surface remote sensing approach. Agricultural and Forest Meteorology 265(February 2019): 327-337. https://doi.org/10.1016/j.agrformet.2018.11.002 |
| spellingShingle | insurance lodging phenology remote sensing winter wheat smallholders agricultural productivity crop modelling Hufkens, Koen Melaas, Eli K. Mann, Michael L. Foster, Timothy Ceballos, Francisco Robles, Miguel Kramer, Berber Monitoring crop phenology using a smartphone based near-surface remote sensing approach |
| title | Monitoring crop phenology using a smartphone based near-surface remote sensing approach |
| title_full | Monitoring crop phenology using a smartphone based near-surface remote sensing approach |
| title_fullStr | Monitoring crop phenology using a smartphone based near-surface remote sensing approach |
| title_full_unstemmed | Monitoring crop phenology using a smartphone based near-surface remote sensing approach |
| title_short | Monitoring crop phenology using a smartphone based near-surface remote sensing approach |
| title_sort | monitoring crop phenology using a smartphone based near surface remote sensing approach |
| topic | insurance lodging phenology remote sensing winter wheat smallholders agricultural productivity crop modelling |
| url | https://hdl.handle.net/10568/145446 |
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