CORN CROPS IDENTIFICATION USING MULTISPECTRAL IMAGES FROM UNMANNED AIRCRAFT SYSTEMS

Fedra Trujillano; Jessenia Gonzalez; Carlos Saito; Andres Flores; Daniel Racoceanu

doi:10.1109/IGARSS47720.2021.9553826

CORN CROPS IDENTIFICATION USING MULTISPECTRAL IMAGES FROM UNMANNED AIRCRAFT SYSTEMS

Fedra Trujillano
, Jessenia Gonzalez
, Carlos Saito
, Andres Flores
, Daniel Racoceanu

Sección de Electricidad y Electrónica

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

Corn is cultivated by smallholder farmers in Ancash - Peru and it is one of the most important crops of the region. Climate change and migration from rural to urban areas are affecting agricultural production and therefore, food security. Information about the cultivated extension is needed for the authorities in order to evaluate the impact in the region. The present study proposes corn areas segmentation in multi-spectral images acquired from Unmanned Aerial Vehicles (UAV), using convolutional neural networks. U-net and U-net using VGG11 encoder were compared using dice and IoU coefficient as metrics. Results show that with the second model, 81.5% dice coefficient can be obtained in this challenging task, allowing envisaging an effective and efficient use of this technology, in this hard context.

Idioma original	Inglés
Título de la publicación alojada	IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
Editorial	Institute of Electrical and Electronics Engineers Inc.
Páginas	4712-4715
Número de páginas	4
ISBN (versión digital)	9781665403696
DOI	https://doi.org/10.1109/IGARSS47720.2021.9553826
Estado	Publicada - 2021
Evento	2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Bélgica Duración: 12 jul. 2021 → 16 jul. 2021

Serie de la publicación

Nombre	International Geoscience and Remote Sensing Symposium (IGARSS)
Volumen	2021-July

Conferencia

Conferencia	2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
País/Territorio	Bélgica
Ciudad	Brussels
Período	12/07/21 → 16/07/21

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 2: Hambre cero
ODS 13: Acción por el clima

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10.1109/IGARSS47720.2021.9553826

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Trujillano, F., Gonzalez, J., Saito, C., Flores, A., & Racoceanu, D. (2021). CORN CROPS IDENTIFICATION USING MULTISPECTRAL IMAGES FROM UNMANNED AIRCRAFT SYSTEMS. En IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 4712-4715). (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2021-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS47720.2021.9553826

Trujillano, Fedra ; Gonzalez, Jessenia ; Saito, Carlos et al. / CORN CROPS IDENTIFICATION USING MULTISPECTRAL IMAGES FROM UNMANNED AIRCRAFT SYSTEMS. IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 4712-4715 (International Geoscience and Remote Sensing Symposium (IGARSS)).

@inproceedings{14d70569aa5046bcacf1d0f6fbf4d3a1,

title = "CORN CROPS IDENTIFICATION USING MULTISPECTRAL IMAGES FROM UNMANNED AIRCRAFT SYSTEMS",

abstract = "Corn is cultivated by smallholder farmers in Ancash - Peru and it is one of the most important crops of the region. Climate change and migration from rural to urban areas are affecting agricultural production and therefore, food security. Information about the cultivated extension is needed for the authorities in order to evaluate the impact in the region. The present study proposes corn areas segmentation in multi-spectral images acquired from Unmanned Aerial Vehicles (UAV), using convolutional neural networks. U-net and U-net using VGG11 encoder were compared using dice and IoU coefficient as metrics. Results show that with the second model, 81.5\% dice coefficient can be obtained in this challenging task, allowing envisaging an effective and efficient use of this technology, in this hard context.",

keywords = "Climate change, Corn identification, Semantic segmentation, UAV",

author = "Fedra Trujillano and Jessenia Gonzalez and Carlos Saito and Andres Flores and Daniel Racoceanu",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 ; Conference date: 12-07-2021 Through 16-07-2021",

year = "2021",

doi = "10.1109/IGARSS47720.2021.9553826",

language = "English",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "4712--4715",

booktitle = "IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",

}

Trujillano, F, Gonzalez, J, Saito, C, Flores, A & Racoceanu, D 2021, CORN CROPS IDENTIFICATION USING MULTISPECTRAL IMAGES FROM UNMANNED AIRCRAFT SYSTEMS. En IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2021-July, Institute of Electrical and Electronics Engineers Inc., pp. 4712-4715, 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021, Brussels, Bélgica, 12/07/21. https://doi.org/10.1109/IGARSS47720.2021.9553826

CORN CROPS IDENTIFICATION USING MULTISPECTRAL IMAGES FROM UNMANNED AIRCRAFT SYSTEMS. / Trujillano, Fedra; Gonzalez, Jessenia; Saito, Carlos et al.
IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. p. 4712-4715 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2021-July).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - CORN CROPS IDENTIFICATION USING MULTISPECTRAL IMAGES FROM UNMANNED AIRCRAFT SYSTEMS

AU - Trujillano, Fedra

AU - Gonzalez, Jessenia

AU - Saito, Carlos

AU - Flores, Andres

AU - Racoceanu, Daniel

PY - 2021

Y1 - 2021

N2 - Corn is cultivated by smallholder farmers in Ancash - Peru and it is one of the most important crops of the region. Climate change and migration from rural to urban areas are affecting agricultural production and therefore, food security. Information about the cultivated extension is needed for the authorities in order to evaluate the impact in the region. The present study proposes corn areas segmentation in multi-spectral images acquired from Unmanned Aerial Vehicles (UAV), using convolutional neural networks. U-net and U-net using VGG11 encoder were compared using dice and IoU coefficient as metrics. Results show that with the second model, 81.5% dice coefficient can be obtained in this challenging task, allowing envisaging an effective and efficient use of this technology, in this hard context.

AB - Corn is cultivated by smallholder farmers in Ancash - Peru and it is one of the most important crops of the region. Climate change and migration from rural to urban areas are affecting agricultural production and therefore, food security. Information about the cultivated extension is needed for the authorities in order to evaluate the impact in the region. The present study proposes corn areas segmentation in multi-spectral images acquired from Unmanned Aerial Vehicles (UAV), using convolutional neural networks. U-net and U-net using VGG11 encoder were compared using dice and IoU coefficient as metrics. Results show that with the second model, 81.5% dice coefficient can be obtained in this challenging task, allowing envisaging an effective and efficient use of this technology, in this hard context.

KW - Climate change

KW - Corn identification

KW - Semantic segmentation

KW - UAV

UR - https://www.scopus.com/pages/publications/85126031080

U2 - 10.1109/IGARSS47720.2021.9553826

DO - 10.1109/IGARSS47720.2021.9553826

M3 - Conference contribution

AN - SCOPUS:85126031080

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 4712

EP - 4715

BT - IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021

Y2 - 12 July 2021 through 16 July 2021

ER -

Trujillano F, Gonzalez J, Saito C, Flores A, Racoceanu D. CORN CROPS IDENTIFICATION USING MULTISPECTRAL IMAGES FROM UNMANNED AIRCRAFT SYSTEMS. En IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2021. p. 4712-4715. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS47720.2021.9553826

CORN CROPS IDENTIFICATION USING MULTISPECTRAL IMAGES FROM UNMANNED AIRCRAFT SYSTEMS

Resumen

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Conferencia

ODS de las Naciones Unidas

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