Monitoring quarry areas using remote sensing techniques

Salim, Pauziyah Mohammad; Jais, Muhammad Anas Md; Sahriman, Noorita; Samad, Abd Manan; Abbas, Mohamed Yusoff; Maarof, Ismail; Tarmizi, Nazirah Md.

doi:10.1109/cspa.2017.8064974

Cited by 3 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, aerial or ground based solutions are often costly or not viable in restricted areas, which may prevent frequent updates. Recurrent satellite imagery is hence emerging as an alternative, as it allows to classify, segment and reconstruct large areas without on-site actions [5,6,7,8]. Today's abundance of Earth observation satellite images, notably due to the breakthrough of SmallSats, explains this growing trend.…”

Section: Introductionmentioning

confidence: 99%

Automatic Stockpile Volume Monitoring using Multi-view Stereo from SkySat Imagery

Marí,

de Franchis,

Meinhardt-Llopis

et al. 2021

Preprint

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

Automatic Stockpile Volume Monitoring using Multi-view Stereo from SkySat Imagery

Marí,

de Franchis,

Meinhardt-Llopis

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…However, such methods have limitations regarding safety and access to the sites. Current trends to estimate these volumes use remote sensing tools such as airborne lidar scanners (Zhao, 2016), stereo-photogrammetry from planes and UAVs (He et al, 2019, Fawzy, 2015, Uysal et al, 2015, Raeva et al, 2016, Tucci et al, 2019, Salim et al, 2017, and even photogrammetry from satellite imagery (Schmidt et al, 2015, Demirel et al, 2011, Ge et al, 2007, Salim et al, 2017.…”

Section: Introductionmentioning

confidence: 99%

Stockpile Monitoring Using Linear Shape-From-Shading on Planetscope Imagery

d'Autume

Perry²,

Morel

et al. 2020

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Abstract. The storage and management of stockpiles of materials is a fundamental process in large scale activities such as mining, civil engineering, and in the management of waste landfill sites. Following the evolution of stocks has always been important, and advancements in remote sensing technology are not only facilitating this, but also making it possible in near real-time. Nowadays, this monitoring appears to be performed almost exclusively using UAV based techniques. This paper proposes to apply a simple Shape-from-Shading method on low resolution satellite images provided by PlanetScope to monitor the evolution of the volume of stockpiles. The proposed Shape-from-Shading formulation makes it possible to handle occluding objects in the scene. The loss in accuracy due to the low resolution of PlanetScope images is well compensated by the daily revisit frequency and by the fact that spaceborne acquisitions require no human supervision. With satellites it is also easy to follow simultaneously several stocking sites all over the world. We test our method on two coal storage sites and demonstrate that the stockpiles are well detected.

show abstract