FORECASTING OF POTATO YIELD ESTIMATION BY SATELLITE BASED REMOTE SENSING TECHNIQUE
The goal of this research was to provide an operational technique with adequate technological components for monitoring and forecasting potato yield in Bangladesh. In the farmers’ fields of Shibganj upazila, the developed system investigates the combined use of satellite remote sensing (RS) and Geog...
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Zibeline International
2024-05-01
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| Series: | Acta Informatica Malaysia |
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| Online Access: | https://actainformaticamalaysia.com/archives/AIM/2aim2024/2aim2024-49-55.pdf |
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| author | Mohammad Mukhlesur Rahman Mohammad Amirul Islam Md. Golam Mahboob Nur Mohammad Istiak Ahmed |
| author_facet | Mohammad Mukhlesur Rahman Mohammad Amirul Islam Md. Golam Mahboob Nur Mohammad Istiak Ahmed |
| author_sort | Mohammad Mukhlesur Rahman |
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| description | The goal of this research was to provide an operational technique with adequate technological components for monitoring and forecasting potato yield in Bangladesh. In the farmers’ fields of Shibganj upazila, the developed system investigates the combined use of satellite remote sensing (RS) and Geographic Information System (GIS) technology. The goal of the study was to construct a remotely sensed yield prediction model that used the high spatial resolution of Sentinel 2A and Landsat 8 satellite images to forecast potato yield one month ahead of harvest. Sentinel 2A (MSI) and Landsat 8 (OLI) satellite images with high spatial resolution data of 10m and 30m, respectively, were assessed, and 10-day and 16-day NDVI data were collected from these two satellites in this research. The study locations for the three potato growing seasons of 2018-2019, 2019-2020, and 2020-2021 were selected upazila. Sentinel 2A (MSI) and Landsat 8 (OLI) satellite data were used to get the NDVI values and yields for 20 farmers’ potato fields at Shibganj, Bogura district. The predicted percentages of the mean yield gap (or underestimation) for Sentinel 2A were 8.58%, while for Landsat 8, these were 9.56%, respectively, at Shibganj upazila, Bogura, during the potato growing season 2020–2021. The findings demonstrated that there is a substantial co-efficient of determination (R2 = 0.93 and 0.78) between remotely sensed NDVI and field-level potato yield. Therefore, remotely sensed NDVI data may be a useful tool for making early predictions about the yield of potatoes. Error of mean yield (%) of Sentinel 2A was better than Landsat 8 at Shibganj upazila, Bogura during the potato growing season 2020-2021. |
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| institution | Kabale University |
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| language | English |
| publishDate | 2024-05-01 |
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| spelling | doaj-art-a810f9e8c8f84a97998480533b91ae2e2025-02-05T07:20:55ZengZibeline InternationalActa Informatica Malaysia2521-08742521-05052024-05-0182495510.26480/aim.02.2024.49.55FORECASTING OF POTATO YIELD ESTIMATION BY SATELLITE BASED REMOTE SENSING TECHNIQUEMohammad Mukhlesur Rahman0Mohammad Amirul Islam1Md. Golam Mahboob2Nur Mohammad3Istiak Ahmed4Agricultural Statistics & ICT Division, Bangladesh Agricultural Research Institute (BARI), 1701 Gazipur, Dhaka, BangladeshDepartment of Agricultural and Applied Statistics, Bangladesh Agricultural University, 2202 Mymensingh, BangladeshDepartment of Natural Resource Management, Bangladesh Agricultural Research Council, 1217 Dhaka, BangladeshAgricultural Statistics & ICT Division, Bangladesh Agricultural Research Institute (BARI), 1701 Gazipur, Dhaka, BangladeshAgricultural Statistics & ICT Division, Bangladesh Agricultural Research Institute (BARI), 1701 Gazipur, Dhaka, BangladeshThe goal of this research was to provide an operational technique with adequate technological components for monitoring and forecasting potato yield in Bangladesh. In the farmers’ fields of Shibganj upazila, the developed system investigates the combined use of satellite remote sensing (RS) and Geographic Information System (GIS) technology. The goal of the study was to construct a remotely sensed yield prediction model that used the high spatial resolution of Sentinel 2A and Landsat 8 satellite images to forecast potato yield one month ahead of harvest. Sentinel 2A (MSI) and Landsat 8 (OLI) satellite images with high spatial resolution data of 10m and 30m, respectively, were assessed, and 10-day and 16-day NDVI data were collected from these two satellites in this research. The study locations for the three potato growing seasons of 2018-2019, 2019-2020, and 2020-2021 were selected upazila. Sentinel 2A (MSI) and Landsat 8 (OLI) satellite data were used to get the NDVI values and yields for 20 farmers’ potato fields at Shibganj, Bogura district. The predicted percentages of the mean yield gap (or underestimation) for Sentinel 2A were 8.58%, while for Landsat 8, these were 9.56%, respectively, at Shibganj upazila, Bogura, during the potato growing season 2020–2021. The findings demonstrated that there is a substantial co-efficient of determination (R2 = 0.93 and 0.78) between remotely sensed NDVI and field-level potato yield. Therefore, remotely sensed NDVI data may be a useful tool for making early predictions about the yield of potatoes. Error of mean yield (%) of Sentinel 2A was better than Landsat 8 at Shibganj upazila, Bogura during the potato growing season 2020-2021.https://actainformaticamalaysia.com/archives/AIM/2aim2024/2aim2024-49-55.pdfremote sensingsentinel 2alandsat 8gisndvi |
| spellingShingle | Mohammad Mukhlesur Rahman Mohammad Amirul Islam Md. Golam Mahboob Nur Mohammad Istiak Ahmed FORECASTING OF POTATO YIELD ESTIMATION BY SATELLITE BASED REMOTE SENSING TECHNIQUE Acta Informatica Malaysia remote sensing sentinel 2a landsat 8 gis ndvi |
| title | FORECASTING OF POTATO YIELD ESTIMATION BY SATELLITE BASED REMOTE SENSING TECHNIQUE |
| title_full | FORECASTING OF POTATO YIELD ESTIMATION BY SATELLITE BASED REMOTE SENSING TECHNIQUE |
| title_fullStr | FORECASTING OF POTATO YIELD ESTIMATION BY SATELLITE BASED REMOTE SENSING TECHNIQUE |
| title_full_unstemmed | FORECASTING OF POTATO YIELD ESTIMATION BY SATELLITE BASED REMOTE SENSING TECHNIQUE |
| title_short | FORECASTING OF POTATO YIELD ESTIMATION BY SATELLITE BASED REMOTE SENSING TECHNIQUE |
| title_sort | forecasting of potato yield estimation by satellite based remote sensing technique |
| topic | remote sensing sentinel 2a landsat 8 gis ndvi |
| url | https://actainformaticamalaysia.com/archives/AIM/2aim2024/2aim2024-49-55.pdf |
| work_keys_str_mv | AT mohammadmukhlesurrahman forecastingofpotatoyieldestimationbysatellitebasedremotesensingtechnique AT mohammadamirulislam forecastingofpotatoyieldestimationbysatellitebasedremotesensingtechnique AT mdgolammahboob forecastingofpotatoyieldestimationbysatellitebasedremotesensingtechnique AT nurmohammad forecastingofpotatoyieldestimationbysatellitebasedremotesensingtechnique AT istiakahmed forecastingofpotatoyieldestimationbysatellitebasedremotesensingtechnique |