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...

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Autores principales: Cucho-Padin, G., Loayza, H., Palacios, S., Balcazar, M., Carbajal, M., Quiróz, R.
Formato: Journal Article
Lenguaje:Inglés
Publicado: Springer 2020
Materias:
Acceso en línea:https://hdl.handle.net/10568/106637
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author Cucho-Padin, G.
Loayza, H.
Palacios, S.
Balcazar, M.
Carbajal, M.
Quiróz, R.
author_browse Balcazar, M.
Carbajal, M.
Cucho-Padin, G.
Loayza, H.
Palacios, S.
Quiróz, R.
author_facet Cucho-Padin, G.
Loayza, H.
Palacios, S.
Balcazar, M.
Carbajal, M.
Quiróz, R.
author_sort Cucho-Padin, G.
collection Repository of Agricultural Research Outputs (CGSpace)
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.
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spelling CGSpace1066372025-03-13T09:46:14Z Development of low-cost remote sensing tools and methods for supporting smallholder agriculture Cucho-Padin, G. Loayza, H. Palacios, S. Balcazar, M. Carbajal, M. Quiróz, R. normalized difference vegetation index image processing multispectral imagery remote sensing sensors 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. 2020-01-14 2020-01-20T21:12:14Z 2020-01-20T21:12:14Z Journal Article https://hdl.handle.net/10568/106637 en Open Access Springer Cucho-Padin, G.; Loayza, H.; Palacios, S.; Balcazar, M.; Carbajal, M.; Quiroz, R. 2019. Development of low-cost remote sensing tools and methods for supporting smallholder agriculture. Applied Geomatics. ISSN: 1866-9298. 17 p.
spellingShingle normalized difference vegetation index
image processing
multispectral imagery
remote sensing
sensors
Cucho-Padin, G.
Loayza, H.
Palacios, S.
Balcazar, M.
Carbajal, M.
Quiróz, R.
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
topic normalized difference vegetation index
image processing
multispectral imagery
remote sensing
sensors
url https://hdl.handle.net/10568/106637
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