Thermal Imagery for Building and Utilities Owners

Woolpert's Qassim Abdullah; Nadja Turek

doi:10.14358/pers.87.10.689

Evaluation of the expediency of using thermal i magery data for decryption exogenous processes and vegetation

Geodesy and Cartography ◽

10.22389/0016-7126-2018-933-3-52-62 ◽

2018 ◽

Vol 933 (3) ◽

pp. 52-62

Author(s):

V.S. Tikunov ◽

I.A. Rylskiy ◽

S.B. Lukatzkiy

Keyword(s):

Spatial Data ◽

Laser Scanning ◽

Data Extraction ◽

Spectral Band ◽

Information Provision ◽

Lidar Data ◽

Thermal Imagery ◽

Scanning Lidar ◽

Field Works ◽

Object Features

Innovative methods of aerial surveys changed approaches to information provision of projecting dramatically in last years. Nowadays there are several methods pretending to be the most efficient for collecting geospatial data intended for projecting – airborne laser scanning (LIDAR) data, RGB aerial imagery (forming 3D pointclouds) and orthoimages. Thermal imagery is one of the additional methods that can be used for projecting. LIDAR data is precise, it allows us to measure relief even under the vegetation, or to collect laser re-flections from wires, metal constructions and poles. Precision and completeness of the DEM, produced from LIDAR data, allows to define relief microforms. Airborne imagery (visual spectrum) is very widespread and can be easily depicted. Thermal images are more strange and less widespread, they use different way of image forming, and spectral features of ob-jects can vary in specific ways. Either way, the additional spectral band can be useful for achieving additional spatial data and different object features, it can minimize field works. Here different aspects of thermal imagery are described in comparison with RGB (visual) images, LIDAR data and GIS layers. The attempt to estimate the feasibility of thermal imag-es for new data extraction is made.

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ESTABLISHING STREAM DISCHARGE LOCATIONS USING SUAS BASED THERMAL IMAGERY

10.1130/abs/2017ne-290912 ◽

2017 ◽

Author(s):

R.H. Becker ◽

Keyword(s):

Thermal Imagery ◽

Stream Discharge

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USING VERY HIGH RESOLUTION HYPERSPECTRAL AND THERMAL IMAGERY TO MAP URBAN MATERIALS IN CEDAR FALLS, IOWA

10.1130/abs/2018nc-312453 ◽

2018 ◽

Author(s):

Bingqing Liang ◽

Keyword(s):

High Resolution ◽

Thermal Imagery ◽

Very High

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Radiometric modeling of mechanical draft cooling towers to assist in the extraction of their absolute temperature from remote thermal imagery

10.1117/12.817527 ◽

2009 ◽

Author(s):

Matthew Montanaro ◽

Carl Salvaggio ◽

Scott D. Brown ◽

David W. Messinger ◽

Alfred J. Garrett ◽

...

Keyword(s):

Absolute Temperature ◽

Cooling Towers ◽

Thermal Imagery

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Using climate reanalysis data in conjunction with multi-temporal satellite thermal imagery to derive supraglacial debris thickness changes from energy-balance modelling

Journal of Glaciology ◽

10.1017/jog.2020.111 ◽

2021 ◽

pp. 1-19

Author(s):

Rebecca L. Stewart ◽

Matthew Westoby ◽

Francesca Pellicciotti ◽

Ann Rowan ◽

Darrel Swift ◽

...

Keyword(s):

Energy Balance ◽

Surface Energy ◽

Surface Energy Balance ◽

Current Knowledge ◽

Meteorological Data ◽

Reanalysis Data ◽

Balance Model ◽

Thermal Imagery ◽

Thickness Estimation ◽

Miage Glacier

Abstract Surface energy-balance models are commonly used in conjunction with satellite thermal imagery to estimate supraglacial debris thickness. Removing the need for local meteorological data in the debris thickness estimation workflow could improve the versatility and spatiotemporal application of debris thickness estimation. We evaluate the use of regional reanalysis data to derive debris thickness for two mountain glaciers using a surface energy-balance model. Results forced using ERA-5 agree with AWS-derived estimates to within 0.01 ± 0.05 m for Miage Glacier, Italy, and 0.01 ± 0.02 m for Khumbu Glacier, Nepal. ERA-5 data were then used to estimate spatiotemporal changes in debris thickness over a ~20-year period for Miage Glacier, Khumbu Glacier and Haut Glacier d'Arolla, Switzerland. We observe significant increases in debris thickness at the terminus for Haut Glacier d'Arolla and at the margins of the expanding debris cover at all glaciers. While simulated debris thickness was underestimated compared to point measurements in areas of thick debris, our approach can reconstruct glacier-scale debris thickness distribution and its temporal evolution over multiple decades. We find significant changes in debris thickness over areas of thin debris, areas susceptible to high ablation rates, where current knowledge of debris evolution is limited.

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