Understanding the role of training sample size in the uncertainty of high-resolution LULC mapping using random forest

K Phinzi, NS Ngetar, QB Pham, GG Chakilu… - Earth Science …, 2023 - Springer
High-resolution sensors onboard satellites are generally reputed for rapidly producing land-
use/land-cover (LULC) maps with improved spatial detail. However, such maps are subject …

[HTML][HTML] PRISMA vs. Landsat 9 in lithological mapping− a K-fold Cross-Validation implementation with Random Forest

A Shebl, D Abriha, M Dawoud, MAH Ali… - The Egyptian Journal of …, 2024 - Elsevier
The selection of an optimal dataset is crucial for successful remote sensing analysis. The
PRISMA hyperspectral sensor (with 240 spectral bands) and Landsat OLI-2 (boasting high …

Predictive modeling of microplastic adsorption in aquatic environments using advanced machine learning models

SH Godasiaei - Science of The Total Environment, 2025 - Elsevier
This study addresses the critical environmental concerns surrounding microplastics, aiming
to elucidate the intricate factors influencing their behavior and interactions with organic …

Predictive modeling for multifaceted hydrothermal carbonization of biomass

T Katongtung, P Prasertpong, S Sukpancharoen… - Journal of …, 2024 - Elsevier
Hydrothermal carbonization is a widely recognized process for converting biomass into
biomass charcoal, aimed at reducing and replacing the use of natural resources while also …

Leveraging machine learning and computational approaches for predicting nanoparticle deposition in shell and tube heat exchangers

SH Godasiaei - Powder Technology, 2025 - Elsevier
This study investigates methods to enhance heat transfer efficiency and analyze fluid
dynamics by examining aluminum oxide nanoparticle deposition in circular tube heat …

Machine learning assisted prediction and analysis of in-plane elastic modulus of hybrid hierarchical square honeycombs

J Yang, D Yang, Y Tao, J Shi - Thin-Walled Structures, 2024 - Elsevier
In this study, experimental, finite element (FE) simulation, machine learning (ML), and
theoretical techniques are employed to investigate the in-plane elastic modulus (E HHSH) of …

A comparative analysis of machine learning techniques for national glacier mapping: Evaluating performance through spatial cross-validation in Perú

M Bueno, B Macera, N Montoya - Water, 2023 - mdpi.com
Accurate glacier mapping is crucial for assessing future water security in Andean
ecosystems. Traditional accuracy assessment may be biased due to overlooking spatial …

Group-Privacy Threats for Geodata in the Humanitarian Context

BK Masinde, CM Gevaert, MH Nagenborg… - … International Journal of …, 2023 - mdpi.com
The role of geodata technologies in humanitarian action is arguably indispensable in
determining when, where, and who needs aid before, during, and after a disaster. However …

[HTML][HTML] Aquatic vegetation mapping with UAS-cameras considering phenotypes

L Szabó, L Bertalan, G Szabó, I Grigorszky… - Ecological …, 2024 - Elsevier
Aquatic vegetation species at the genus level in an oxbow lake were identified in Hungary
based on a multispectral Uncrewed Aerial System (UAS) survey within an elongated oxbow …

Unraveling the spatial distribution and influencing factors of 'Bengke'traditional houses in Luhuo County, Western Sichuan

S Yu, D Fan, M Ge, Z Chen - PloS one, 2024 - journals.plos.org
The article examines the spatial distribution characteristics and influencing factors of
traditional Tibetan “Bengke” residential architecture in Luhuo County, Ganzi Tibetan …