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Remote Sens. 2014, 6(10), 9435-9457; doi:10.3390/rs6109435

Transforming Image-Objects into Multiscale Fields: A GEOBIA Approach to Mitigate Urban Microclimatic Variability within H-Res Thermal Infrared Airborne Flight-Lines

1
Department of Geography, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N1N4, Canada
2
Canadian Pacific Railway, 7550 Ogden Dale Road S.E. Calgary, AB T2C 4X9, Canada
*
Author to whom correspondence should be addressed.
Received: 1 July 2014 / Revised: 12 September 2014 / Accepted: 17 September 2014 / Published: 1 October 2014
(This article belongs to the Special Issue Advances in Geographic Object-Based Image Analysis (GEOBIA))
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Abstract

In an effort to minimize complex urban microclimatic variability within high-resolution (H-Res) airborne thermal infrared (TIR) flight-lines, we describe the Thermal Urban Road Normalization (TURN) algorithm, which is based on the idea of pseudo invariant features. By assuming a homogeneous road temperature within a TIR scene, we hypothesize that any variation observed in road temperature is the effect of local microclimatic variability. To model microclimatic variability, we define a road-object class (Road), compute the within-Road temperature variability, sample it at different spatial intervals (i.e., 10, 20, 50, and 100 m) then interpolate samples over each flight-line to create an object-weighted variable temperature field (a TURN-surface). The optimal TURN-surface is then subtracted from the original TIR image, essentially creating a microclimate-free scene. Results at different sampling intervals are assessed based on their: (i) ability to visually and statistically reduce overall scene variability and (ii) computation speed. TURN is evaluated on three non-adjacent TABI-1800 flight-lines (~182 km2) that were acquired in 2012 at night over The City of Calgary, Alberta, Canada. TURN also meets a recent GEOBIA (Geospatial Object Based Image Analysis) challenge by incorporating existing GIS vector objects within the GEOBIA workflow, rather than relying exclusively on segmentation methods. View Full-Text
Keywords: Thermal Urban Road Normalization (TURN); surface temperature; temporal variation; microclimatic variability; thermal infrared imagery; geographic objects; TABI 1800 Thermal Urban Road Normalization (TURN); surface temperature; temporal variation; microclimatic variability; thermal infrared imagery; geographic objects; TABI 1800
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Rahman, M.M.; Hay, G.J.; Couloigner, I.; Hemachandran, B. Transforming Image-Objects into Multiscale Fields: A GEOBIA Approach to Mitigate Urban Microclimatic Variability within H-Res Thermal Infrared Airborne Flight-Lines. Remote Sens. 2014, 6, 9435-9457.

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