  This paper proposes a system for automatic surface volume monitoring from
time series of SkySat pushframe imagery. A specific challenge of building and
comparing large 3D models from SkySat data is to correct inconsistencies
between the camera models associated to the multiple views that are necessary
to cover the area at a given time, where these camera models are represented as
Rational Polynomial Cameras (RPCs). We address the problem by proposing a
date-wise RPC refinement, able to handle dynamic areas covered by sets of
partially overlapping views. The cameras are refined by means of a rotation
that compensates for errors due to inaccurate knowledge of the satellite
attitude. The refined RPCs are then used to reconstruct multiple consistent
Digital Surface Models (DSMs) from different stereo pairs at each date. RPC
refinement strengthens the consistency between the DSMs of each date, which is
extremely beneficial to accurately measure volumes in the 3D surface models.
The system is tested in a real case scenario, to monitor large coal stockpiles.
Our volume estimates are validated with measurements collected on site in the
same period of time.

Computer Vision and Pattern Recognition;Image and Video Processing