Development of low-cost remote sensing tools and methods for supporting smallholder agriculture
Agricultural UAV-based remote sensing tools to facilitate decision-making for increasing productivity in developing countries were developed and tested. Specifically, a high-quality multispectral sensor and sophisticated-yet-user-friendly data processing techniques (software) under an open-access po...
| Autores principales: | , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
Springer Link
2020
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| Acceso en línea: | https://repositorio.catie.ac.cr/handle/11554/9331 https://doi.org/10.1007/s12518-019-00292-5 |
| _version_ | 1855417627106607104 |
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| author | Chucho Padin, Gonzalo Loayza, Hildo Palacios, Susan Balcazar, Mario Carbajal, Mariella Quiroz, Roberto |
| author_browse | Balcazar, Mario Carbajal, Mariella Chucho Padin, Gonzalo Loayza, Hildo Palacios, Susan Quiroz, Roberto |
| author_facet | Chucho Padin, Gonzalo Loayza, Hildo Palacios, Susan Balcazar, Mario Carbajal, Mariella Quiroz, Roberto |
| author_sort | Chucho Padin, Gonzalo |
| collection | Repositorio CATIE |
| description | Agricultural UAV-based remote sensing tools to facilitate decision-making for increasing productivity in developing countries were developed and tested. Specifically, a high-quality multispectral sensor and sophisticated-yet-user-friendly data processing techniques (software) under an open-access policy were implemented. The multispectral sensor—IMAGRI-CIP—is a low-cost adaptable multi-sensor array that allows acquiring high-quality and low-SNR images from a UAV platform used to estimate vegetation indexes such as NDVI. Also, a set of software tools that included wavelet-based image alignment, image stitching, and crop classification have been implemented and made available to the remote sensing community. A validation field experiment carried out at the International Potato Center facilities (Lima, Peru) to test the developed tools is reported. A thorough comparison study with a wide-used commercial agricultural camera showed that IMAGRI-CIP provides highly correlated NDVI values (R2≥ 0.8). Additionally, an application field experiment was conducted in Kilosa, Tanzania, to test the tools in smallholder farm settings, featuring high-heterogeneous crop plots. Results showed high accuracy (> 82%) to identify 13 different crops either as mono-crop or as mixed-crops. |
| format | Artículo |
| id | RepoCATIE9331 |
| institution | Centro Agronómico Tropical de Investigación y Enseñanza |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Springer Link |
| publisherStr | Springer Link |
| record_format | dspace |
| spelling | RepoCATIE93312023-11-16T16:28:06Z Development of low-cost remote sensing tools and methods for supporting smallholder agriculture Chucho Padin, Gonzalo Loayza, Hildo Palacios, Susan Balcazar, Mario Carbajal, Mariella Quiroz, Roberto Agricultural UAV-based remote sensing tools to facilitate decision-making for increasing productivity in developing countries were developed and tested. Specifically, a high-quality multispectral sensor and sophisticated-yet-user-friendly data processing techniques (software) under an open-access policy were implemented. The multispectral sensor—IMAGRI-CIP—is a low-cost adaptable multi-sensor array that allows acquiring high-quality and low-SNR images from a UAV platform used to estimate vegetation indexes such as NDVI. Also, a set of software tools that included wavelet-based image alignment, image stitching, and crop classification have been implemented and made available to the remote sensing community. A validation field experiment carried out at the International Potato Center facilities (Lima, Peru) to test the developed tools is reported. A thorough comparison study with a wide-used commercial agricultural camera showed that IMAGRI-CIP provides highly correlated NDVI values (R2≥ 0.8). Additionally, an application field experiment was conducted in Kilosa, Tanzania, to test the tools in smallholder farm settings, featuring high-heterogeneous crop plots. Results showed high accuracy (> 82%) to identify 13 different crops either as mono-crop or as mixed-crops. 2020-01-14T16:08:17Z 2020-01-14T16:08:17Z 2019 Artículo https://repositorio.catie.ac.cr/handle/11554/9331 https://doi.org/10.1007/s12518-019-00292-5 en Applied Geomatics info:eu-repo/semantics/openAccess Springer Link |
| spellingShingle | Chucho Padin, Gonzalo Loayza, Hildo Palacios, Susan Balcazar, Mario Carbajal, Mariella Quiroz, Roberto Development of low-cost remote sensing tools and methods for supporting smallholder agriculture |
| title | Development of low-cost remote sensing tools and methods for supporting smallholder agriculture |
| title_full | Development of low-cost remote sensing tools and methods for supporting smallholder agriculture |
| title_fullStr | Development of low-cost remote sensing tools and methods for supporting smallholder agriculture |
| title_full_unstemmed | Development of low-cost remote sensing tools and methods for supporting smallholder agriculture |
| title_short | Development of low-cost remote sensing tools and methods for supporting smallholder agriculture |
| title_sort | development of low cost remote sensing tools and methods for supporting smallholder agriculture |
| url | https://repositorio.catie.ac.cr/handle/11554/9331 https://doi.org/10.1007/s12518-019-00292-5 |
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