Estimation of surface thermal emissivity in a vineyard for UAV microbolometer thermal cameras using NASA HyTES hyperspectral thermal, Landsat and AggieAir optical data.

Landsat MODIS Emissivity NASA HYTES Thermal emissivity UAV land surface temperature microbolometer camera

Journal

Proceedings of SPIE--the International Society for Optical Engineering
ISSN: 0277-786X
Titre abrégé: Proc SPIE Int Soc Opt Eng
Pays: United States
ID NLM: 101524122

Informations de publication

Date de publication:
2019
Historique:
entrez: 31 7 2019
pubmed: 31 7 2019
medline: 31 7 2019
Statut: ppublish

Résumé

Microbolometer thermal cameras in UAVs and manned aircraft allow for the acquisition of high-resolution temperature data, which, along with optical reflectance, contributes to monitoring and modeling of agricultural and natural environments. Furthermore, these temperature measurements have facilitated the development of advanced models of crop water stress and evapotranspiration in precision agriculture and heat fluxes exchanges in small river streams and corridors. Microbolometer cameras capture thermal information at blackbody or radiometric settings (narrowband emissivity equates to unity). While it is customary that the modeler uses assumed emissivity values (e.g. 0.99-0.96 for agricultural and environmental settings); some applications (e.g. Vegetation Health Index), and complex models such as energy balance-based models (e.g. evapotranspiration) could benefit from spatial estimates of surface emissivity for true or kinetic temperature mapping. In that regard, this work presents an analysis of the spectral characteristics of a microbolometer camera with regard to emissivity, along with a methodology to infer thermal emissivity spatially based on the spectral characteristics of the microbolometer camera. For this work, the MODIS UCBS Emissivity Library, NASA HyTES hyperspectral emissivity, Landsat, and Utah State University AggieAir UAV surface reflectance products are employed. The methodology is applied to a commercial vineyard agricultural setting located in Lodi, California, where HyTES, Landsat, and AggieAir UAV spatial data were collected in the 2014 growing season. Assessment of the microbolometer spectral response with regards to emissivity and emissivity modeling performance for the area of study are presented and discussed.

Identifiants

pubmed: 31359903
doi: 10.1117/12.2518958
pmc: PMC6662723
mid: NIHMS1035795
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NASA
ID : NNX17AF51G
Pays : United States

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Auteurs

Alfonso Torres-Rua (A)

Utah State University, Civil and Env Engineering, Old Main Hill, Logan, Utah 84322, USA.

Mahyar Aboutalebi (M)

Utah State University, Civil and Env Engineering, Old Main Hill, Logan, Utah 84322, USA.

Timothy Wright (T)

Utah State University, College of Agriculture, Old Main Hill, Logan, Utah 84322, USA.

Ayman Nassar (A)

Utah State University, Civil and Env Engineering, Old Main Hill, Logan, Utah 84322, USA.

Pierre Guillevic (P)

University of Maryland, Department of Geographical Sciences, College Park, MD 20740, USA.

Lawrence Hipps (L)

Utah State University, College of Agriculture, Old Main Hill, Logan, Utah 84322, USA.

Feng Gao (F)

USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705 USA.

Kevin Jim (K)

OceanIT, 828 Fort Street Mall, Suite 600, Honolulu, Hawaii 96813.

Maria Mar Alsina (MM)

E&J Gallo, 600 Yosemite Blvd, Modesto, CA 95354.

Calvin Coopmans (C)

Utah State University, Electrical Engineering, Old Main Hill, Logan, Utah 84322, USA.

Mac McKee (M)

Utah State University, Civil and Env Engineering, Old Main Hill, Logan, Utah 84322, USA.

William Kustas (W)

USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705 USA.

Classifications MeSH