Integrating multiple data sources, we reveal a broader distribution for Glironia venusta and highlight how sampling strategies shape our understanding of rare arboreal mammals. ABSTRACT Introduction Arboreal and nocturnal mammals in the Amazon remain poorly understood due to low detectability and methodological limitations. Glironia venusta, one of the
Alexander Roldán Arévalo‐Sandi +5 more
wiley +1 more source
Spatio-Temporal Modeling of Land-Use/Land-Cover Change and Land Surface Temperature Using SVM and CA-Markov in Dilla Town, Ethiopia. [PDF]
Kebede TA +4 more
europepmc +1 more source
ABSTRACT Accurate and automatic determination of the boundaries of agricultural parcels is essential for planning sustainable agricultural policies, managing agricultural production, tracking products and enabling precision farming applications. In recent years, pre‐trained visual base models with zero‐shot segmentation capabilities, such as the ...
Fatih Fehmi Şimşek +3 more
wiley +1 more source
A hybrid empirical and semi analytical inversion approach for remote sensing estimation of SPM in Ebinur Lake China. [PDF]
Liu C +6 more
europepmc +1 more source
ABSTRACT Land subsidence is an increasing environmental hazard in semi‐arid agricultural basins where intensive groundwater abstraction, compressible geological units, and expanding land‐use pressures interact. This study presents a PS‐InSAR and machine‐learning‐based framework for land subsidence susceptibility mapping in the Çumra District of the ...
Burhan Baha Bilgilioğlu
wiley +1 more source
PM-MCD: A network combining pyramid feature extraction and multi-scale attention fusion for multiclass change detection. [PDF]
Fan Y, Yang X, Li B.
europepmc +1 more source
ABSTRACT Wildfire susceptibility mapping (WSM) is critical for forest management, land‐use planning, and disaster risk mitigation. Although hybrid artificial neural network (ANN) models optimized by metaheuristic algorithms are increasingly used in susceptibility mapping, they are often evaluated without strong machine learning benchmarks, spatially ...
Talha Taşkanat
wiley +1 more source
Daily Land Surface Temperature Reconstruction in Landsat Cross-Track Areas Using Deep Ensemble Learning With Uncertainty Quantification. [PDF]
Liu S, Wang S, Zhang L.
europepmc +1 more source
Analysis of Models to Estimate Morbidity Rates of Respiratory Diseases Through Deep Learning
ABSTRACT Respiratory diseases remain a challenge in Brazil due to socioeconomic inequalities and environmental risks that intensify population vulnerability. This study compared XGBoost with a deep learning model using stacked Gated Recurrent Units (GRU), trained with morbidity data from respiratory diseases and exogenous variables such as per capita ...
Liliane Moreira Nery +6 more
wiley +1 more source
Desertification monitoring in arid oasis environment using Google Earth Engine, machine learning, and field-based hydrogeological assessment. [PDF]
Moumane A +8 more
europepmc +1 more source

