Volume IV-3
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 127-134, 2018
https://doi.org/10.5194/isprs-annals-IV-3-127-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 127-134, 2018
https://doi.org/10.5194/isprs-annals-IV-3-127-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  23 Apr 2018

23 Apr 2018

GENERATING IMPACT MAPS FROM AUTOMATICALLY DETECTED BOMB CRATERS IN AERIAL WARTIME IMAGES USING MARKED POINT PROCESSES

Christian Kruse1, Franz Rottensteiner1, Thorsten Hoberg2, Marcel Ziems2, Julia Rebke2, and Christian Heipke1 Christian Kruse et al.
  • 1Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, 30167 Hanover, Germany
  • 2State Office for Geoinformation and Surveying of Lower Saxony, 30659 Hanover, Germany

Keywords: Aerial Wartime Images, Bomb Craters, Marked Point Processes, RJMCMC, Simulated Annealing

Abstract. The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.