Ditapis dengan
CloudSense: A model for cloud type identification using machine learning from…
The knowledge of type of precipitating cloud is crucial for radar based quantitative estimates of precipitation. We propose a novel model called CloudSense which uses machine learning to accurately identify the type of precipitating clouds over the complex terrain locations in the Western Ghats (WG) of India. CloudSense uses vertical reflectivity profiles collected during July–August 2018 fro…
- Edisi
- Vol.24, December 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 12 hlm PDF, 6.755 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
An UNet3+ Network based on global pyramid aggregation for change detection in…
Change detection (CD) is a meaningful and challenging task for remote sensing (RS) image analysis. Deep learning (DL) based methods have shown great potential in change detection tasks, there are still two problems with existing deep learning methods such as CNN and Transformer: (1) They do not target different depths to extract global semantics in the network; (2) The increase in network depth…
- Edisi
- Vol.24, December 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 14 hlm PDF, 4.185 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
An open-source, QGIS-based solution for digital geological mapping: GEOL-QMAPS
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
A machine learning approach for mapping susceptibility to land subsidence cau…
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
A generative deep neural network as an alternative to co-kriging
In geosciences, kriging is leading spatial interpolation, and co-kriging is the most commonly used method for accomplishing spatial interpolation of a target variable by incorporating information from a secondary variable. Co-kriging relies on the assumption of spatial stationarity, which may not hold true in all geospatial contexts, leading to potential inaccuracies in interpolation. The effec…
- Edisi
- Vol.24, December 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 9 hlm PDF, 2.533 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
A comparative study on machine learning approaches for rock mass classificati…
Current rock engineering design in drill and blast tunnelling primarily relies on engineers' observational assessments. Measure While Drilling (MWD) data, a high-resolution sensor dataset collected during tunnel excavation, is underutilised, mainly serving for geological visualisation. This study aims to automate the translation of MWD data into actionable metrics for rock engineering. It seeks…
- Edisi
- Vol.24, December 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 24 hlm PDF, 15.152 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Using multiple-point geostatistics for geomodeling of a vein-type gold deposit
Geostatistical cascade modeling of Mineral Resources is challenging in vein-type gold deposits. The narrow shape and long-range features of these auriferous veins, coupled with the paucity of drill-hole data, can complicate the modeling process and make the use of two-point geostatistical algorithms impractical. Instead, multiple-point geostatistics techniques can be a suitable alternative. How…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 15 hlm PDF, 9.916 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
User-friendly carbon-cycle modelling and aspects of Phanerozoic climate change
Carbon-cycle modelling is essential for testing the main carbon sources and sinks as climate forcings, and we introduce and describe GEOCARB_NET, a graphical user interface for the geologic carbon and sulfur cycle model GEOCARBSULFvolc. The software system is menu-driven, user-friendly, and the user is never far removed from the basic input parameters from which atmospheric CO2 and O2 concentra…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 15 hlm PDF, 20.852 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Resolution enhancement and segmentation of polar bubbly ice micro CT scans vi…
Accurate segmentation of 3D micro CT scans is a key step in the process of analysis of the microstructure of porous materials. In polar ice core studies, the environmental effects on the firn column could be detected if the microstructure is digitized accurately. The most challenging task is to obtain the microstructure parameters of the bubbly ice section. To identify the minimum, necessary re…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 13 hlm PDF, 3.950 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
POSIT: An automated tool for detecting and characterizing diverse morphologic…
Accurate detection and characterization of seafloor morphologies are crucial for marine researchers and industries involved in underwater mapping, environmental monitoring, or resource exploration. Although their detection has relied on visual inspection of detailed bathymetries, few efforts to automate the process can be found in the literature. This study presents a novel MatLab computer code…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 14 hlm PDF, 29.245 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
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