Paper Info
Title
Unsupervised Detection Of Active, New, And Closed Coal Mines With Reclamation Activity From Landsat 8 Oli/Tirs Images
Abstract
Monitoring and classification of surface coal mine regions have several research aspects, as they have huge impacts on the eco-environment of a region. Mining regions change over time immensely. New potential mines get opened. Whereas, few mines stay active and many of them get closed. Closed mine regions are reclaimed to environment through plantation. In the past, semi-supervised and supervised techniques have been used to detect mine classes and assess the changes of land use and land cover classes. In this work, mine regions are detected in an adaptive manner from satellite images unlike the techniques in the literature. Further, a change detection technique is used to detect active, new, and closed surface coal mines in a region. Detected closed mines are further analysed to evaluate reclamation of that region. Average precision and recall of active, new, and closed mining regions of the proposed technique are found to be [84.7%, 62.8%], [74.2%, 64.5%], and [70.1%, 58.2%], respectively.
Year
DOI
Venue
2019
10.1007/978-3-030-34869-4_43
PATTERN RECOGNITION AND MACHINE INTELLIGENCE, PREMI 2019, PT I
Keywords
DocType
Volume
Clay mineral ratio, Coal mine index, Surface coal mine, Change detection, Mine classes, Landsat 8
Conference
11941
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Jit Mukherjee100.34
Jayanta Mukhopadhyay27226.05
Debashish Chakravarty354.62
Subhas Aikat411.36