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9 Results Found

  • Proceeding Paper
  • Open Access
2,873 Views
9 Pages

Kaoline Mapping Using ASTER Satellite Imagery: The Case Study of Kefalos Peninsula, Kos Island

  • Maria Kokkaliari,
  • Christos Kanellopoulos and
  • Ioannis Illiopoulos

The present work aims to map kaolin occurrences on the Kefalos peninsula, SW Kos Island, Greece, through the elaboration of ASTER satellite imagery. The island of Kos is located on the eastern edge of the South Aegean Active Volcanic Arc (SAAVA) and...

(This article belongs to the Proceedings of International Conference on Raw Materials and Circular Economy)
  • Article
  • Open Access
26 Citations
9,356 Views
19 Pages

Improving the Reliability of Mixture Tuned Matched Filtering Remote Sensing Classification Results Using Supervised Learning Algorithms and Cross-Validation

  • Devin Routh,
  • Lindsi Seegmiller,
  • Charlie Bettigole,
  • Catherine Kuhn and ,
  • Chadwick D. Oliver and
  • Henry B. Glick
  • + 1 author+ 0 author

23 October 2018

Mixture tuned matched filtering (MTMF) image classification capitalizes on the increasing spectral and spatial resolutions of available hyperspectral image data to identify the presence, and potentially the abundance, of a given cover type or endmemb...

(This article belongs to the Special Issue Hyperspectral Remote Sensing of Forest and Trees outside Forests Ecosystems)
  • Article
  • Open Access
108 Citations
12,525 Views
24 Pages

Comparison of Different Algorithms to Map Hydrothermal Alteration Zones Using ASTER Remote Sensing Data for Polymetallic Vein-Type Ore Exploration: Toroud–Chahshirin Magmatic Belt (TCMB), North Iran

  • Lida Noori,
  • Amin Beiranvand Pour,
  • Ghasem Askari,
  • Nader Taghipour and ,
  • Biswajeet Pradhan,
  • Chang-Wook Lee and
  • Mehdi Honarmand
  • + 2 authors+ 0 author

1 March 2019

Polymetallic vein-type ores are important sources of precious metal and a principal type of orebody for various base-metals. In this research, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data were used for ma...

(This article belongs to the Special Issue Multispectral and Hyperspectral Remote Sensing Data for Mineral Exploration and Environmental Monitoring of Mined Areas)
  • Article
  • Open Access
375 Views
30 Pages

Subpixel Detection of Lithium-Rich Pegmatites via Integrated Hyperspectral Unmixing and Multispectral Machine Learning

  • Douglas Santos,
  • Nuno Eusébio,
  • Filipa Dias,
  • Beatriz Araújo and ,
  • António Azzalini,
  • Ricardo Ribeiro,
  • Ana Cláudia Teodoro,
  • Nelson Pires and
  • Alexandre Lima
  • + 4 authors+ 0 author

7 October 2026

Lithium(Li)-rich pegmatites are an important source of Li for the energy transition, but their detection using remote sensing data/techniques remains challenging due to subpixel occurrence. This study presents an integrated prospectivity mapping fram...

  • Feature Paper
  • Article
  • Open Access
16 Citations
10,312 Views
24 Pages

Detecting and Mapping Slag Heaps at Ancient Copper Production Sites in Oman

  • Alexander J. Sivitskis,
  • Joseph W. Lehner,
  • Michael J. Harrower,
  • Ioana A. Dumitru and ,
  • Paige E. Paulsen,
  • Smiti Nathan,
  • Daniel R. Viete,
  • Suleiman Al-Jabri,
  • Barbara Helwing and
  • Bernhard Pracejus
  • + 7 authors+ 2 authors

14 December 2019

This study presents a new approach for detection and mapping of ancient slag heaps using 16-band multispectral satellite imagery. Understanding the distribution of slag (a byproduct of metal production) is of great importance for understanding how me...

(This article belongs to the Special Issue 2nd Edition Advances in Remote Sensing for Archaeological Heritage)
  • Article
  • Open Access
39 Citations
9,891 Views
19 Pages

7 September 2018

This study develops a site specific burn severity modelling using remote sensing techniques to develop severity patterns on vegetation and soil in the fire prone region of the Palo Verde National Park in Guanacaste, Costa Rica. Terrain physical featu...

(This article belongs to the Special Issue Remote Sensing of Wildfire)
  • Article
  • Open Access
125 Citations
11,122 Views
36 Pages

Application of Multi-Sensor Satellite Data for Exploration of Zn–Pb Sulfide Mineralization in the Franklinian Basin, North Greenland

  • Amin Beiranvand Pour,
  • Tae-Yoon S. Park,
  • Yongcheol Park,
  • Jong Kuk Hong and ,
  • Basem Zoheir,
  • Biswajeet Pradhan,
  • Iman Ayoobi and
  • Mazlan Hashim
  • + 3 authors+ 0 author

27 July 2018

Geological mapping and mineral exploration programs in the High Arctic have been naturally hindered by its remoteness and hostile climate conditions. The Franklinian Basin in North Greenland has a unique potential for exploration of world-class zinc...

(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
  • Article
  • Open Access
20 Citations
6,495 Views
46 Pages

15 March 2022

Glacier surface facies are valuable indicators of changes experienced by a glacial system. The interplay of accumulation and ablation facies, followed by intermixing with dust and debris, as well as the local climate, all induce observable and mappab...

(This article belongs to the Special Issue Earth Observation (EO), Remote Sensing (RS), and Geoinformation (GI) Applications in Svalbard)
  • Article
  • Open Access
43 Citations
7,081 Views
37 Pages

Identification of Phyllosilicates in the Antarctic Environment Using ASTER Satellite Data: Case Study from the Mesa Range, Campbell and Priestley Glaciers, Northern Victoria Land

  • Amin Beiranvand Pour,
  • Milad Sekandari,
  • Omeid Rahmani,
  • Laura Crispini and ,
  • Andreas Läufer,
  • Yongcheol Park,
  • Jong Kuk Hong,
  • Biswajeet Pradhan,
  • Mazlan Hashim and
  • Kamyar Mehranzamir
  • + 7 authors+ 2 authors

24 December 2020

In Antarctica, spectral mapping of altered minerals is very challenging due to the remoteness and inaccessibility of poorly exposed outcrops. This investigation evaluates the capability of Advanced Spaceborne Thermal Emission and Reflection Radiomete...

(This article belongs to the Special Issue Synergy of Remote Sensing and Deep Learning for Mineral Resources and Environment)