Remote sensing to UAV-based digital farmland

Nicola Falco; Haruko Wainwright; Craig Ulrich; Baptiste Dafflon; Susan S. Hubbard; Malcolm Williamson; Jackson D. Cothren; Richard G. Ham; Jay A. McEntire; McClain McEntire

doi:10.1109/IGARSS.2018.8518365

Remote sensing to UAV-based digital farmland

Nicola Falco, Haruko Wainwright, Craig Ulrich, Baptiste Dafflon, Susan S. Hubbard, Malcolm Williamson, Jackson D. Cothren, Richard G. Ham, Jay A. McEntire, McClain McEntire

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

This study presents preliminary observations of the first year of a crop monitoring experiment occurred in two soybean agriculture fields in the Arkansas delta. The project focuses on developing image processing and data integration techniques for UAV-based images to optimize advanced farm management such as soil microbial amendments. In particular, we present an effective algorithm that can use high-resolution UAV images efficiently to estimate sprout density and plant vigor/health throughout the growing season. Such plant characterization is extremely important for the identification of anomalous areas and provide easily interpretable information for a better decision making. We also present an integrative analysis of UAV-data with geophysical data and harvesting data, which shows high correlation between persistent spatial pattern of soil, plant phenology/growth, and crop yield.

Original language	English
Title of host publication	2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5936-5939
Number of pages	4
ISBN (Electronic)	9781538671504
DOIs	https://doi.org/10.1109/IGARSS.2018.8518365
State	Published - Oct 31 2018
Externally published	Yes
Event	38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Valencia, Spain Duration: Jul 22 2018 → Jul 27 2018

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2018-July

Conference

Conference	38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Country/Territory	Spain
City	Valencia
Period	07/22/18 → 07/27/18

Keywords

Image processing
Phenotyping
Precision agriculture
Remote sensing
Unmanned aerial vehicle (UAV)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/IGARSS.2018.8518365

Cite this

Falco, N., Wainwright, H., Ulrich, C., Dafflon, B., Hubbard, S. S., Williamson, M., Cothren, J. D., Ham, R. G., McEntire, J. A., & McEntire, M. (2018). Remote sensing to UAV-based digital farmland. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings (pp. 5936-5939). Article 8518365 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2018.8518365

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title = "Remote sensing to UAV-based digital farmland",

abstract = "This study presents preliminary observations of the first year of a crop monitoring experiment occurred in two soybean agriculture fields in the Arkansas delta. The project focuses on developing image processing and data integration techniques for UAV-based images to optimize advanced farm management such as soil microbial amendments. In particular, we present an effective algorithm that can use high-resolution UAV images efficiently to estimate sprout density and plant vigor/health throughout the growing season. Such plant characterization is extremely important for the identification of anomalous areas and provide easily interpretable information for a better decision making. We also present an integrative analysis of UAV-data with geophysical data and harvesting data, which shows high correlation between persistent spatial pattern of soil, plant phenology/growth, and crop yield.",

keywords = "Image processing, Phenotyping, Precision agriculture, Remote sensing, Unmanned aerial vehicle (UAV)",

author = "Nicola Falco and Haruko Wainwright and Craig Ulrich and Baptiste Dafflon and Hubbard, {Susan S.} and Malcolm Williamson and Cothren, {Jackson D.} and Ham, {Richard G.} and McEntire, {Jay A.} and McClain McEntire",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 ; Conference date: 22-07-2018 Through 27-07-2018",

year = "2018",

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day = "31",

doi = "10.1109/IGARSS.2018.8518365",

language = "English",

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

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Falco, N, Wainwright, H, Ulrich, C, Dafflon, B, Hubbard, SS, Williamson, M, Cothren, JD, Ham, RG, McEntire, JA & McEntire, M 2018, Remote sensing to UAV-based digital farmland. in 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings., 8518365, International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2018-July, Institute of Electrical and Electronics Engineers Inc., pp. 5936-5939, 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, 07/22/18. https://doi.org/10.1109/IGARSS.2018.8518365

Remote sensing to UAV-based digital farmland. / Falco, Nicola; Wainwright, Haruko; Ulrich, Craig et al.
2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 5936-5939 8518365 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Remote sensing to UAV-based digital farmland

AU - Falco, Nicola

AU - Wainwright, Haruko

AU - Ulrich, Craig

AU - Dafflon, Baptiste

AU - Hubbard, Susan S.

AU - Williamson, Malcolm

AU - Cothren, Jackson D.

AU - Ham, Richard G.

AU - McEntire, Jay A.

AU - McEntire, McClain

PY - 2018/10/31

Y1 - 2018/10/31

N2 - This study presents preliminary observations of the first year of a crop monitoring experiment occurred in two soybean agriculture fields in the Arkansas delta. The project focuses on developing image processing and data integration techniques for UAV-based images to optimize advanced farm management such as soil microbial amendments. In particular, we present an effective algorithm that can use high-resolution UAV images efficiently to estimate sprout density and plant vigor/health throughout the growing season. Such plant characterization is extremely important for the identification of anomalous areas and provide easily interpretable information for a better decision making. We also present an integrative analysis of UAV-data with geophysical data and harvesting data, which shows high correlation between persistent spatial pattern of soil, plant phenology/growth, and crop yield.

AB - This study presents preliminary observations of the first year of a crop monitoring experiment occurred in two soybean agriculture fields in the Arkansas delta. The project focuses on developing image processing and data integration techniques for UAV-based images to optimize advanced farm management such as soil microbial amendments. In particular, we present an effective algorithm that can use high-resolution UAV images efficiently to estimate sprout density and plant vigor/health throughout the growing season. Such plant characterization is extremely important for the identification of anomalous areas and provide easily interpretable information for a better decision making. We also present an integrative analysis of UAV-data with geophysical data and harvesting data, which shows high correlation between persistent spatial pattern of soil, plant phenology/growth, and crop yield.

KW - Image processing

KW - Phenotyping

KW - Precision agriculture

KW - Remote sensing

KW - Unmanned aerial vehicle (UAV)

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T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

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EP - 5939

BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018

Y2 - 22 July 2018 through 27 July 2018

ER -

Falco N, Wainwright H, Ulrich C, Dafflon B, Hubbard SS, Williamson M et al. Remote sensing to UAV-based digital farmland. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 5936-5939. 8518365. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS.2018.8518365

Remote sensing to UAV-based digital farmland

Abstract

Publication series

Conference

Keywords

UN SDGs

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