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Ditemukan 20 dari pencarian Anda melalui kata kunci: subject="Mapping"
1 2 Berikutnya Hal. Akhir
cover
ASTER data processing and fusion for alteration minerals and silicification d…
Komentar Bagikan
Soufiane HajajAbderrazak El HartiAmine JellouliAmin Beiranvand PourSaloua Mnissar HimyariAbderrazak HamzaouiMazlan Hashim

Alteration minerals and silicification are typically associated with a variety of ore mineralizations and could be detected using multispectral remote sensing sensors as indicators for mineral exploration. In this investigation, the Visible Near-Infra-Red (VNIR), Short-Wave Infra-Red (SWIR), and Thermal Infra-Red (TIR) bands of the ASTER satellite sensor derived layers were fused to detect alte…

Edisi
Vol.5, December 2024
ISBN/ISSN
2666-5441
Deskripsi Fisik
-
Judul Seri
-
No. Panggil
18 hlm PDF, 39.870 KB
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Towards a fully data-driven prospectivity mapping methodology: A case study o…
Komentar Bagikan
Steven E. ZhangGlen T. NwailaJulie E. BourdeauDavid Corrigan

Mineral exploration campaigns are financially risky. Several state-of-the-art methods have been developed to mitigate the risk, including predictive modelling of mineral prospectivity using principal component analysis (PCA) and geographic information systems (GIS). The PCA and GIS approach is currently considered acceptable for generating mineral exploration targets. However, some of its limit…

Edisi
Vol.2, December 2021
ISBN/ISSN
2666-5441
Deskripsi Fisik
20 hlm PDF, 16.632 KB
Judul Seri
Artificial Intelligence in Geosciences
No. Panggil
551
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Machine learning-based prediction of trace element concentrations using data …
Komentar Bagikan
Steven E. ZhangGlen T. NwailaJulie E. BourdeauLewis D. Ashwal

In this study, we present a machine learning-based method to predict trace element concentrations from major and minor element concentration data using a legacy lithogeochemical database of magmatic rocks from the Karoo large igneous province (Gondwana Supercontinent). Wedemonstrate that a variety of trace elements, including most of the lanthanides, chalcophile, lithophile, and siderophile ele…

Edisi
Vol.2, December 2021
ISBN/ISSN
2666-5441
Deskripsi Fisik
16 hlm PDF, 3.494 KB
Judul Seri
Artificial Intelligence in Geosciences
No. Panggil
551
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Rapid mapping of landslides using satellite SAR imagery: A progressive learni…
Komentar Bagikan
Nikhil PrakashAndrea ManconiAlessandro Cesare Mondini

Rapid detection of landslides after an exceptional event is critical for planning effective disaster management. Previous works have typically used machine learning-based methods, including the recently popular deep-learning approaches, to identify characteristics surface features from satellite remote sensing data, especially from optical images. However, data acquisition from optical images i…

Edisi
Vol.25, February 2025
ISBN/ISSN
2590-1974
Deskripsi Fisik
12 hlm PDF, 5.502 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Mapping landforms of a hilly landscape using machine learning and high-resolu…
Komentar Bagikan
Netra R. RegmiNina D.S. WebbJacob I. WalterJoonghyeok HeoNicholas W. Hayman

Landform maps are important tools in assessment of soil- and eco-hydrogeomorphic processes and hazards, hydrological modeling, and natural resources and land management. Traditional techniques of mapping landforms based on field surveys or from aerial photographs can be time and labor intensive, highlighting the importance of remote sensing products based automatic or semi-automatic approaches.…

Edisi
Vol.24, December 2024
ISBN/ISSN
2590-1974
Deskripsi Fisik
11 hlm PDF, 13.809 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
An open-source, QGIS-based solution for digital geological mapping: GEOL-QMAPS
Komentar Bagikan
Julien PerretMark W. JessellEliott Betend

Digital geological mapping has experienced significant growth over the past three decades due to the advent of commercial geographical information systems, advances in global positioning systems, and the availability of portable hand-held devices, such as mobile personal computers (PCs), smartphones, and tablets. Numerous software packages have been developed to collect, combine, organise, visu…

Edisi
Vol.24, December 2024
ISBN/ISSN
2590-1974
Deskripsi Fisik
12 hlm PDF, 11.716 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
A machine learning approach for mapping susceptibility to land subsidence cau…
Komentar Bagikan
Diana OrlandiEsteban DíazRoberto TomasFederico A. GalatoloMario G.C.A. CiminoCarolina PagliNicola Perilli

Land subsidence is a worldwide threat that may cause irreversible damage to the environment and the infrastructures. Thus, identifying and mapping areas prone to land subsidence with accurate methods such as Land Subsidence Susceptibility Index (LSSI) mapping is crucial for mitigating the adverse impacts of this geohazard. Also, Machine Learning (ML) is now becoming a powerful tool to analyze v…

Edisi
Vol.24, December 2024
ISBN/ISSN
2590-1974
Deskripsi Fisik
14 hlm PDF, 15.318 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
A new approach to dust source mapping using visual interpretation and object-…
Komentar Bagikan
Ali Darvishi BolooraniNastaran NasiriMasoud SoleimaniRamin PapiFatemeh AmiriNajmeh Neysani SamanyAzher Ibrahim Al-TaeiSaham MirzaeiAli Al-Hemoud

The emission of dust particles, mainly from arid and semi-arid lands, as a result of climate change and human activities, is known to be a global issue. Identifying dust emission sources is the first key step in dealing with the hazardous consequences of this rising phenomenon. This study is an attempt to address one of the major challenges in mapping dust emission sources. Accordingly, an inno…

Edisi
Vol.23, September 2024
ISBN/ISSN
2590-1974
Deskripsi Fisik
9 hlm PDF, 13.165 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Comparative performance analysis of simple U-Net, residual attention U-Net, a…
Komentar Bagikan
Ali GhaznaviMohammadmehdi SaberioonJakub BromSibylle Itzerott

Inland water bodies play a vital role at all scales in the terrestrial water balance and Earth’s climate variability. Thus, an inventory of inland waters is crucially important for hydrologic and ecological studies and management. Therefore, the main aim of this study was to develop a deep learning-based method for inventorying and mapping inland water bodies using the RGB band of high-resolu…

Edisi
Vol.21, March 2024
ISBN/ISSN
2590-1974
Deskripsi Fisik
11 hlm PDF, 3.036 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Rapid estimation of minimum depth-to-bedrock from lidar leveraging deep-learn…
Komentar Bagikan
William OdomDaniel Doctor

Previously glaciated landscapes often share similar surficial characteristics, including large areas of exposed bedrock, blankets of till deposits, and alluvium-floored valleys. These materials play significant roles in geologic and hydrologic resources, geohazards, and landscape evolution; however, the vast extents of many previously glaciated landscapes have rendered comprehensive, detailed f…

Edisi
Vol.18 June 2023
ISBN/ISSN
2590-1974
Deskripsi Fisik
11 hlm PDF, 9.277 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
1 2 Berikutnya Hal. Akhir
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