Monitoring the Extent of Reclamation of Small Scale Mining Areas Using Artificial Neural Networks-Reference-Cited by-同舟云学术

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Monitoring the Extent of Reclamation of Small Scale Mining Areas Using Artificial Neural Networks

Published:2019-04 Issue:4 Volume:5 Page:e01445
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Abaidoo Christian Aboagye,Osei Jnr Edward Matthew^ORCID,Arko-Adjei Anthony,Prah Benjamin Eric Kwesi

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference17 articles.

1. Remote Sensing Techniques for Monitoring Coal Surface Mining and Reclamation in the Powder River Basin;Alden,2009

2. Remotely sensed soil data analysis using artificial neural networks: a case study of El – Fayoum depression, Egypt;Amato;ISPRS Int. J. Geo-Inf.,2015

3. Anon, (2015a), https://nsidc.org/pipermail/glims/2008/000303.html, [Accessed 20 January 2016].

4. Mine Reclamation;Anon,2015

5. Using Artificial Networks for Digital Soil Mapping – A Comparison of MLP and SOM Approaches;Freire,2009

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2. Analysis of Post-Mining Vegetation Development Using Remote Sensing and Spatial Regression Approach: A Case Study of Former Babina Mine (Western Poland);Remote Sensing;2023-01-26

3. Design of an optimized deep learning algorithm for automatic classification of high-resolution satellite dataset (LISS IV) for studying land-use patterns in a mining region;Computers & Geosciences;2023-01

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