Short‐Term Rental Platform in the Urban Tourism Context: A Geographically Weighted Regression (GWR) and a Multiscale GWR (MGWR) Approaches

Semiparametric geographically weighted generalised linear modelling in GWR 4.0

Spatial Modeling of Residential Crowding in Alexandria Governorate, Egypt: A Geographically Weighted Regression (GWR) Technique

Despite growing research for residential crowding effects on housing market and public health perspectives, relatively little attention has been paid to explore and model spatial patterns of residential crowding over space. This paper focuses upon analyzing the spatial relationships between residential crowding and socio-demographic variables in Alexandria neighborhoods, Egypt. Global and local...

X - Ray and Gwr Sources

3 RESUMEN ABSTRACT We discuss the model for the Galactic sample of the AM CVn systems with P orb ≤ 1500 s that can be detected in the optical and/or X-ray bands and may be resolved by the gravitational waves detector LISA. At 3 ∼ < P ∼ < 10 min all detectable systems are X-ray sources. At P ∼ > 10 min most systems are only detectable in the V-band. About 30% of the X-ray sources is also detecta...

Ground Level PM2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO2 and Enhanced Vegetation Index (EVI)

Highly accurate data on the spatial distribution of ambient fine particulate matter (<2.5 μm: PM2.5) is currently quite limited in China. By introducing NO₂ and Enhanced Vegetation Index (EVI) into the Geographically Weighted Regression (GWR) model, a newly developed GWR model combined with a fused Aerosol Optical Depth (AOD) product and meteorological parameters could explain approximately 87%...

Modeling of the Relationships Between Spatio-Temporal Changes of Traffic Volume and Particulate Matter-2.5 Pollutant Concentration Based on Geographically Weighted Regression (GWR) and Inverse Distance Weighting (IDW) Model: A Case Study in Tehran M

Background and Aim: High concentrations of particulate matter-25 (PM2.5) have been the cause of the unhealthiest days in Tehran, Iran in recent years. This study was conducted with the aim of the spatio-temporal analysis of traffic volume and its relationship with PM2.5 pollutant concentrations in Tehran metropolis, Tehran during 2015-2018, using the Geographic Information System (GIS). Materi...