University of Twente Student Theses
Critical nodes for food security : detecting food storage facilities using remote sensing images
Salami, Emmanuel Tosin (2024) Critical nodes for food security : detecting food storage facilities using remote sensing images.
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| Abstract: | The rising global population, projected to reach 9.1 billion by 2050, demands a 70% increase in food production. Currently, 1.3 billion tons of food are wasted annually due to post-harvest losses, particularly in developing countries. Despite the numerous research of silos as a food storage facility for food security, little has been done on the automatic detection of the silo’s structures using earth observation data. This study aims to enhance food security by addressing the lack of information on the spatial coverage of grain storage facilities, especially silos. By employing multi-resolution optical earth observation data, namely High Resolution (HR) Sentinel-2 satellite data and Very High Resolution (VHR) aerial images from the National Agricultural Imagery Program (NAIP), this research develops innovative methods for the detection and mapping of silos. The research explores machine learning algorithms to automatically identify the silo's locations leveraging on their specific properties in terms of object's size, shape, and spectral signature. This study focuses on the United States as a case study due to its extensive grain production and storage capabilities. The research integrates multiresolution earth observation data, and machine learning algorithms to detect silos, aiming to contribute to sustainable development goals by reducing post-harvest losses and informing policymaking for food security. |
| Item Type: | Essay (Master) |
| Faculty: | ITC: Faculty of Geo-information Science and Earth Observation |
| Subject: | 38 earth sciences |
| Programme: | Geoinformation Science and Earth Observation MSc (75014) |
| Link to this item: | https://purl.utwente.nl/essays/102214 |
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