Publications

Rahman, Mir Mustafizur; Hay, Geoffrey J.; Couloigner, Isabelle; Hemachandran, Bharanidharan (2014). Transforming Image-Objects into Multiscale Fields: A GEOBIA Approach to Mitigate Urban Microclimatic Variability within H-Res Thermal Infrared Airborne Flight-Lines. REMOTE SENSING, 6(10), 9435-9457.

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 microclimatefree 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 (similar to 182 km(2)) 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.

DOI:
10.3390/rs6109435

ISSN:
2072-4292