Detection of River Sandbank for Sand Mining with the Presence of Other
  High Mineral Content Regions Using Multi-spectral Images
Jit Mukherjee
Sand mining is a booming industry. The river sandbank is one of the primary
sources of sand mining. Detection of potential river sandbank regions for sand
mining directly impacts the economy, society, and environment. In the past,
semi-supervised and supervised techniques have been used to detect mining
regions including sand mining. A few techniques employ multi-modal analysis
combining different modalities such as multi-spectral imaging, synthetic
aperture radar (\emph{SAR}) imaging, aerial images, and point cloud data.
However, the distinguishing spectral characteristics of river sandbank regions
are yet to be fully explored. This paper provides a novel method to detect
river sandbank regions for sand mining using multi-spectral images without any
labeled data over the seasons. Association with a river stream and the
abundance of minerals are the most prominent features of such a region. The
proposed work uses these distinguishing features to determine the spectral
signature of a river sandbank region, which is robust to other high mineral
abundance regions. It follows a two-step approach, where first, potential high
mineral regions are detected and next, they are segregated using the presence
of a river stream. The proposed technique provides average accuracy, precision,
and recall of 90.75%, 85.47%, and 73.5%, respectively over the seasons from
Landsat 8 images without using any labeled dataset.