Ditapis dengan
Applying machine learning methods to predict geology using soil sample geoche…
In this study we compared various machine learning techniques that used soil geochemistry to aid in geologic mapping. We tested six different sampling methods (undersample, oversample, Synthetic Minority Oversampling Technique (SMOTE), Adaptive Synthetic Sampling (ADASYN), SMOTE and Edited Nearest Neighbor (SMOTEENN), and SMOTE and Tomek links (SMOTETomek)). SMOTE performed best with ADASYN and…
- Edisi
- Vol.16, December 2022
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 13 hlm PDF, 13.315 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
A plugin for computing the pore/grain network tortuosity of a porous medium f…
Tortuosity is an important geometrical parameter of the pore or grain network in a porous medium. Here we present and discuss an implementation of a plugin to estimate the pore/grain network tortuosity of a porous medium sample. The tortuosity is estimated according to the geometric reconstruction algorithm that can be applied to 2D or 3D μCT image samples. To illustrate the tortuosity plugin …
- Edisi
- Vol.5, March 2020
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 14 hlm PDF, 6.599 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
End-to-end simulations to optimize imaging spectroscopy mission requirements …
CNES is currently carrying out a Phase A study to assess the feasibility of a future hyperspectral imaging sensor (10 m spatial resolution) combined with a panchromatic camera (2.5 m spatial resolution). This mission focuses on both high spatial and spectral resolution requirements, as inherited from previous French studies such as HYPEX, HYPXIM, and BIODIVERSITY. To meet user requirements, cos…
- Edisi
- Vol.12, April 2024
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 20 hlm PDF, 15.892 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
How suitable are vegetation indices for estimating the (R)USLE C-factor for c…
The cover and management factor (C-factor) of the Universal Soil Loss Equation (USLE) represents the effects of crop cover, weighted by rainfall pattern, on predicted soil erosion rates. This requires an estimate of seasonal rainfall erosivity and soil protection afforded by the crop at different phenological stages, expressed by a soil loss ratio (SLR). However, soil erosion modelers often rel…
- Edisi
- Vol.10, December 2023
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 14 hlm PDF, 11.159 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Batas Wilayah 
Ekologi 
Fotogrametri 
Geografi 
Geologi 
GIS 
Ilmu Tanah 
Kartografi 
Manajemen Bencana 
Oceanografi 
Penginderaan Jauh 
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