Potential of resampled multispectral data for detecting desmodium-brachiaria intercropped with maize in a 'push-pull' system
Poor crop yields remain one of the main causes of chronic food insecurity in Africa. This is largely caused by insect pests, weeds,unfavourable climatic conditions and degraded soils. Weed and pest control, based on the climate-adapted ‘push-pull’ system, has become an important target for sustainab...
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International Society for Photogrammetry and Remote Sensing
2021
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| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/1017/2020/isprs-archives-XLIII-B3-2020-1017-2020.pdf http://hdl.handle.net/11408/4167 |
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| author | Mudereri, Bester Tawona Abdel-Rahman, E.M. Dube, T. Landmann, T. Niassy, S. Tonnang, H.E.Z. Khan, Z.R. |
| author_facet | Mudereri, Bester Tawona Abdel-Rahman, E.M. Dube, T. Landmann, T. Niassy, S. Tonnang, H.E.Z. Khan, Z.R. |
| author_sort | Mudereri, Bester Tawona |
| collection | DSpace |
| description | Poor crop yields remain one of the main causes of chronic food insecurity in Africa. This is largely caused by insect pests, weeds,unfavourable climatic conditions and degraded soils. Weed and pest control, based on the climate-adapted ‘push-pull’ system, has become an important target for sustainable intensification of food production adopted by many small-holder farmers.
However, essential baseline information using remotely sensed data is missing, specifically for the ‘push-pull’ companion crops.
In this study, we investigated the spectral uniqueness of two of the most commonly used ‘companion’ crops (i.e. greenleaf Desmodium (Desmodium intortum) and Brachiaria (Brachiaria cv Mulato) with co-occurring soil, green maize, and maize stover. We used FieldSpec® Handheld 2™ analytical spectral device to collect in situ hyperspectral data in the visible and near-infrared
region of the electromagnetic spectrum. Random forest was then used to discriminate among the different companion crops, green maize, maize stover and the background soil. Experimental ‘push-pull’ plots at the International Centre of Insect Physiology and Ecology (icipe) in Kenya were used as test sites. The in-situ hyperspectral reflectance data were resampled to the spectral waveband configurations of four multispectral sensors (i.e. Landsat-8, Quickbird, Sentinel-2, and WorldView-2) using spectral response functions. The performance of the four sensors to detect the ‘push-pull’ companion crops, maize and soil was
compared. We were able to positively discriminate the two companion crops from the three potential background endmembers i.e. soil, green maize, and maize stover. Sentinel-2 and WorldView-2 outperformed (> 98% overall accuracy) Landsat-8 and Quickbird (96% overall accuracy), because of their added advantage of the strategically located red-edge bands. Our results
demonstrated the unique potential of the relatively new multispectral sensors’ and machine learning algorithms as a tool to accurately discern companion crops from co-occurring maize in ‘push-pull’ plots. |
| format | Presentation |
| id | ir-11408-4167 |
| institution | My University |
| language | English |
| publishDate | 2021 |
| publisher | International Society for Photogrammetry and Remote Sensing |
| record_format | dspace |
| spelling | ir-11408-41672022-06-27T13:49:05Z Potential of resampled multispectral data for detecting desmodium-brachiaria intercropped with maize in a 'push-pull' system Mudereri, Bester Tawona Abdel-Rahman, E.M. Dube, T. Landmann, T. Niassy, S. Tonnang, H.E.Z. Khan, Z.R. Cropping system Field spectroscopy Spectral resampling Multispectral remote sensing Poor crop yields remain one of the main causes of chronic food insecurity in Africa. This is largely caused by insect pests, weeds,unfavourable climatic conditions and degraded soils. Weed and pest control, based on the climate-adapted ‘push-pull’ system, has become an important target for sustainable intensification of food production adopted by many small-holder farmers. However, essential baseline information using remotely sensed data is missing, specifically for the ‘push-pull’ companion crops. In this study, we investigated the spectral uniqueness of two of the most commonly used ‘companion’ crops (i.e. greenleaf Desmodium (Desmodium intortum) and Brachiaria (Brachiaria cv Mulato) with co-occurring soil, green maize, and maize stover. We used FieldSpec® Handheld 2™ analytical spectral device to collect in situ hyperspectral data in the visible and near-infrared region of the electromagnetic spectrum. Random forest was then used to discriminate among the different companion crops, green maize, maize stover and the background soil. Experimental ‘push-pull’ plots at the International Centre of Insect Physiology and Ecology (icipe) in Kenya were used as test sites. The in-situ hyperspectral reflectance data were resampled to the spectral waveband configurations of four multispectral sensors (i.e. Landsat-8, Quickbird, Sentinel-2, and WorldView-2) using spectral response functions. The performance of the four sensors to detect the ‘push-pull’ companion crops, maize and soil was compared. We were able to positively discriminate the two companion crops from the three potential background endmembers i.e. soil, green maize, and maize stover. Sentinel-2 and WorldView-2 outperformed (> 98% overall accuracy) Landsat-8 and Quickbird (96% overall accuracy), because of their added advantage of the strategically located red-edge bands. Our results demonstrated the unique potential of the relatively new multispectral sensors’ and machine learning algorithms as a tool to accurately discern companion crops from co-occurring maize in ‘push-pull’ plots. 2021-05-12T12:15:48Z 2021-05-12T12:15:48Z 2020 Presentation 2194-9034 https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/1017/2020/isprs-archives-XLIII-B3-2020-1017-2020.pdf http://hdl.handle.net/11408/4167 en The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLIII-B3-2020, 2020 XXIV ISPRS Congress (2020 edition); open International Society for Photogrammetry and Remote Sensing |
| spellingShingle | Cropping system Field spectroscopy Spectral resampling Multispectral remote sensing Mudereri, Bester Tawona Abdel-Rahman, E.M. Dube, T. Landmann, T. Niassy, S. Tonnang, H.E.Z. Khan, Z.R. Potential of resampled multispectral data for detecting desmodium-brachiaria intercropped with maize in a 'push-pull' system |
| title | Potential of resampled multispectral data for detecting desmodium-brachiaria intercropped with maize in a 'push-pull' system |
| title_full | Potential of resampled multispectral data for detecting desmodium-brachiaria intercropped with maize in a 'push-pull' system |
| title_fullStr | Potential of resampled multispectral data for detecting desmodium-brachiaria intercropped with maize in a 'push-pull' system |
| title_full_unstemmed | Potential of resampled multispectral data for detecting desmodium-brachiaria intercropped with maize in a 'push-pull' system |
| title_short | Potential of resampled multispectral data for detecting desmodium-brachiaria intercropped with maize in a 'push-pull' system |
| title_sort | potential of resampled multispectral data for detecting desmodium-brachiaria intercropped with maize in a 'push-pull' system |
| topic | Cropping system Field spectroscopy Spectral resampling Multispectral remote sensing |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/1017/2020/isprs-archives-XLIII-B3-2020-1017-2020.pdf http://hdl.handle.net/11408/4167 |
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