Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system

Abstract The advent of remote sensing from unmanned aerial systems (UAS) has opened the door to more affordable and effective methods of imaging and mapping of surface geophysical properties with many important applications in areas such as coastal zone management, ecology, agriculture, and defense....

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Autores principales:	Rehman S. Eon, Charles M. Bachmann
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1e102ee11e324033ba3f5e0e212e7bd8
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spelling	oai:doaj.org-article:1e102ee11e324033ba3f5e0e212e7bd82021-12-02T14:26:47ZMapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system10.1038/s41598-021-82783-32045-2322https://doaj.org/article/1e102ee11e324033ba3f5e0e212e7bd82021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82783-3https://doaj.org/toc/2045-2322Abstract The advent of remote sensing from unmanned aerial systems (UAS) has opened the door to more affordable and effective methods of imaging and mapping of surface geophysical properties with many important applications in areas such as coastal zone management, ecology, agriculture, and defense. We describe a study to validate and improve soil moisture content retrieval and mapping from hyperspectral imagery collected by a UAS system. Our approach uses a recently developed model known as the multilayer radiative transfer model of soil reflectance (MARMIT). MARMIT partitions contributions due to water and the sediment surface into equivalent but separate layers and describes these layers using an equivalent slab model formalism. The model water layer thickness along with the fraction of wet surface become parameters that must be optimized in a calibration step, with extinction due to water absorption being applied in the model based on equivalent water layer thickness, while transmission and reflection coefficients follow the Fresnel formalism. In this work, we evaluate the model in both field settings, using UAS hyperspectral imagery, and laboratory settings, using hyperspectral spectra obtained with a goniometer. Sediment samples obtained from four different field sites representing disparate environmental settings comprised the laboratory analysis while field validation used hyperspectral UAS imagery and coordinated ground truth obtained on a barrier island shore during field campaigns in 2018 and 2019. Analysis of the most significant wavelengths for retrieval indicate a number of different wavelengths in the short-wave infra-red (SWIR) that provide accurate fits to measured soil moisture content in the laboratory with normalized root mean square error (NRMSE)< 0.145, while independent evaluation from sequestered test data from the hyperspectral UAS imagery obtained during the field campaign obtained an average NRMSE = 0.169 and median NRMSE = 0.152 in a bootstrap analysis.Rehman S. EonCharles M. BachmannNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Rehman S. Eon Charles M. Bachmann Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system
description	Abstract The advent of remote sensing from unmanned aerial systems (UAS) has opened the door to more affordable and effective methods of imaging and mapping of surface geophysical properties with many important applications in areas such as coastal zone management, ecology, agriculture, and defense. We describe a study to validate and improve soil moisture content retrieval and mapping from hyperspectral imagery collected by a UAS system. Our approach uses a recently developed model known as the multilayer radiative transfer model of soil reflectance (MARMIT). MARMIT partitions contributions due to water and the sediment surface into equivalent but separate layers and describes these layers using an equivalent slab model formalism. The model water layer thickness along with the fraction of wet surface become parameters that must be optimized in a calibration step, with extinction due to water absorption being applied in the model based on equivalent water layer thickness, while transmission and reflection coefficients follow the Fresnel formalism. In this work, we evaluate the model in both field settings, using UAS hyperspectral imagery, and laboratory settings, using hyperspectral spectra obtained with a goniometer. Sediment samples obtained from four different field sites representing disparate environmental settings comprised the laboratory analysis while field validation used hyperspectral UAS imagery and coordinated ground truth obtained on a barrier island shore during field campaigns in 2018 and 2019. Analysis of the most significant wavelengths for retrieval indicate a number of different wavelengths in the short-wave infra-red (SWIR) that provide accurate fits to measured soil moisture content in the laboratory with normalized root mean square error (NRMSE)< 0.145, while independent evaluation from sequestered test data from the hyperspectral UAS imagery obtained during the field campaign obtained an average NRMSE = 0.169 and median NRMSE = 0.152 in a bootstrap analysis.
format	article
author	Rehman S. Eon Charles M. Bachmann
author_facet	Rehman S. Eon Charles M. Bachmann
author_sort	Rehman S. Eon
title	Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system
title_short	Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system
title_full	Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system
title_fullStr	Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system
title_full_unstemmed	Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system
title_sort	mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/1e102ee11e324033ba3f5e0e212e7bd8
work_keys_str_mv	AT rehmanseon mappingbarrierislandsoilmoistureusingaradiativetransfermodelofhyperspectralimageryfromanunmannedaerialsystem AT charlesmbachmann mappingbarrierislandsoilmoistureusingaradiativetransfermodelofhyperspectralimageryfromanunmannedaerialsystem
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Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system

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