Detecting shadows in multi-temporal aerial imagery to support near-real-time change detection. Issue 4 (4th July 2017)

• Record Type: Journal Article
• Authors: Storey, Emanuel A.; Stow, Douglas A.; Coulter, Lloyd L.; Chen, Christopher
• Is Part Of: GIScience & remote sensing. Volume 54:Issue 4(2017)
• Page Start: 453
• Page End: 470
• Publication Date: 2017-07-04
• Subjects: shadow classification -- shadow normalization -- shadow detection -- post-hazard damage assessment -- change detection; Geodesy -- Periodicals; Cartography -- Periodicals; Aerial photogrammetry -- Periodicals; Remote sensing -- Periodicals; 526.05
• DOI: 10.1080/15481603.2017.1279729
• Languages: English
• ISSNs: 1548-1603

Abstract

Abstract : Multi-temporal aerial imagery captured via an approach called repeat station imaging (RSI) facilitates post-hazard assessment of damage to infrastructure. Spectral-radiometric (SR) variations caused by differences in shadowing may inhibit successful change detection based on image differencing. This study evaluates a novel approach to shadow classification based on bi-temporal imagery, which exploits SR change signatures associated with transient shadows. Changes in intensity (brightness from red–green–blue images) and intensity-normalized blue waveband values provide a basis for classifying transient shadows across a range of material types with unique reflectance properties, using thresholds that proved versatile for very different scenes. We derive classification thresholds for persistent shadows based on hue to intensity ratio ( H/I ) images, by exploiting statistics obtained from transient shadow areas. We assess shadow classification accuracy based on this procedure, and compare it to the more conventional approach of thresholding individual H/I images based on frequency distributions. Our efficient and semi-automated shadow classification procedure shows improved mean accuracy (93.3%) and versatility with different image sets over the conventional approach (84.7%). For proof-of-concept, we demonstrate that overlaying bi-temporal imagery also facilitates normalization of intensity values in transient shadow areas, as part of an integrated procedure to support near-real-time change detection.