Ditapis dengan
Detection and Attribution of a Spatial Heterogeneity in the Temporal Evolutio…
The hydrosphere is an element of the climate system and changes in the latter are reasonably projected over the river outflow. Climatic changes, however, are unevenly distributed over the Earth, and understanding their regional imprint on the hydrosphere is of great importance. In this study, we have conducted a statistical analysis of the monthly maximum and minimum river discharge recorded in…
- Edisi
- Vol.15, Issue 1, January 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 17 hlm PDF, 2.840 KB
- Judul Seri
- Geosciences
- No. Panggil
- 550
A Developed Computational Code to Build a 3D Fracture Network to Reduce the U…
Rock masses comprise intact rock and discontinuities, such as fractures, which significantly influence their mechanical and hydraulic properties. Uncertainty in constructing the fracture network can notably affect the outcomes of sensitive analyses, including tunnel stability simulations. Thus, accurately determining specific parameters of rock joints, including orientation and trace length, is…
- Edisi
- Vol.15, Issue 1, January 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 22 hlm PDF, 3.692 KB
- Judul Seri
- Geosciences
- No. Panggil
- 550
Assessing the ecological vulnerability of forest landscape to agricultural fr…
Forest conservation in human-dominated tropical landscapes ensures provision of major ecosystem services. However, conservation goals are threatened by growing demands for agricultural products. As the expansion of agricultural frontiers continues to exert increasing pressure on forest cover, it is crucial to provide indicators on forest vulnerability to improve our understanding of forest dyna…
- Edisi
- Vol.84, February 2020
- ISBN/ISSN
- 1569-8432
- Deskripsi Fisik
- 13 hlm PDF, 13.168 KB
- Judul Seri
- International Journal of Applied Earth Observation and Geoinformation - Open Access
- No. Panggil
- 910.285
A method for vertical adjustment of digital aerial photogrammetry data by usi…
The accuracy of vertical position information can be degraded by various sources of error in digital aerial photogrammetry (DAP) based point clouds. To address this issue, we propose a relatively straightforward method for automated correction of such point clouds. This method can be used in conjunction with any 3D reconstruction method in which a point cloud is generated from a pair of aerial …
- Edisi
- Vol.84, February 2020
- ISBN/ISSN
- 1569-8432
- Deskripsi Fisik
- 9 hlm PDF, 1.547 KB
- Judul Seri
- International Journal of Applied Earth Observation and Geoinformation - Open Access
- No. Panggil
- 910.285
Water resource forecasting with machine learning and deep learning: A sciento…
Water prediction plays a crucial role in modern-day water resource management, encompassing both hydrological patterns and demand forecasts. To gain insights into its current focus, status, and emerging themes, this study analyzed 876 articles published between 2015 and 2022, retrieved from the Web of Science database. Leveraging CiteSpace visualization software, bibliometric techniques, and li…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 12 hlm PDF, 4.935 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Fully invertible hyperbolic neural networks for segmenting large-scale surfac…
The large spatial/temporal/frequency scale of geoscience and remote-sensing datasets causes memory issues when using convolutional neural networks for (sub-) surface data segmentation. Recently developed fully reversible or fully invertible networks can mostly avoid memory limitations by recomputing the states during the backward pass through the network. This results in a low and fixed memory …
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 13 hlm PDF, 3.537 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Benchmarking data handling strategies for landslide susceptibility modeling u…
Machine learning (ML) algorithms are frequently used in landslide susceptibility modeling. Different data handling strategies may generate variations in landslide susceptibility modeling, even when using the same ML algorithm. This research aims to compare the combinations of inventory data handling, cross validation (CV), and hyperparameter tuning strategies to generate landslide susceptibilit…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 16 hlm PDF, 33.426 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Application of ChatGPT in soil science research and the perceptions of soil s…
Since its arrival in late November 2022, ChatGPT-3.5 has rapidly gained popularity and significantly impacted how research is planned, conducted, and published using a generative artificial intelligence approach. ChatGPT-4 was released four months later and became more popular in November 2023. However, there is little study about the perception of scientists of these chatbots, especially in so…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 8 hlm PDF, 2.483 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Estimation of dusk time F-region electron density vertical profiles using LST…
The vertical profile of the ionosphere density plays a significant role in the development of low-latitude Equatorial Plasma Bubbles (EPBs), that in turn lead to ionospheric scintillation which can severely degrade precision and availability of critical users of the Global Navigation Satellite System (GNSS). Accurate estimation of ionospheric delays through vertical electron density profiles is…
- Edisi
- Vol.4, December 2023
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 11 hlm PDF, 9.300 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Irregularly sampled seismic data interpolation via wavelet-based convolutiona…
Seismic data interpolation, especially irregularly sampled data interpolation, is a critical task for seismic processing and subsequent interpretation. Recently, with the development of machine learning and deep learning, convolutional neural networks (CNNs) are applied for interpolating irregularly sampled seismic data. CNN based approaches can address the apparent defects of traditional inter…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 11 hlm PDF, 5.141 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
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