Results 61 to 70 of about 13,792,835 (170)

Evaluation of linear, nonlinear, and hybrid models for predicting PM2.5 based on a GTWR model and MODIS AOD data

, 2019
Ground monitoring station data of PM2.5 are not available for each day and all places in urban areas. In this research, taking Tehran as an example, a geographically and temporally weighted regression (GTWR) model was utilized to investigate the spatial ...
Amanollahi, J., Tzanis, C.G., Mirzaei, M.   +2 more
core   +1 more source

Unmasking Non-Static Drivers of Urban Ecological Resilience: Evidence from the Guanzhong Plain Urban Agglomeration

Land
Urban ecological resilience (UER) has become a central concern in rapidly urbanizing regions where development pressures increasingly interact with ecological constraints.
Xiaohui Ding, Yuan Wang, Kehui Li, Ruolan Li, Heng Wang   +4 more
doaj   +1 more source

A Comparison of Regression Methods for Inferring Near‐Surface NO2 With Satellite Data

Journal of Geophysical Research: Atmospheres, Volume 129, Issue 16, 28 August 2024.
Abstract Nitrogen dioxide (NO2) is an atmospheric pollutant emitted from anthropogenic and natural sources. Human exposure to high NO2 concentrations causes cardiovascular and respiratory illnesses. The Environmental Protection Agency operates ground monitors across the U.S.
Eliot J. Kim, Tracey Holloway, Ajinkya Kokandakar, Monica Harkey, Stephanie Elkins, Daniel L. Goldberg, Colleen Heck   +6 more
wiley   +1 more source

Estimation results of GTWR model.

Coronavirus disease 2019 (COVID-19) has brought dramatic changes in our daily life, especially in human mobility since 2020. As the major component of the integrated transport system in most cities, taxi trips represent a large portion of residents ...
Shen Zhang (302856), Yanan Zhang (1322391), Xueliang Sui (18389395)   +2 more
core   +1 more source

Nonparametric spatio-temporal modeling: Contruction of a geographically and temporally weighted spline regression

MethodsX
This research introduces a new model called Geographically Temporally and Weighted Spline Nonparametric Regression (GTWSNR), which is an extension of the Geographically Temporally Weighted Regression (GTWR) model.
Sifriyani, Syaripuddin, M. Fathurahman, Nariza Wanti Wulan Sari, Meirinda Fauziyah, Andrea Tri Rian Dani, Raudhatul Jannah, S. Dwi Juriani, Ratna Kusuma   +8 more
doaj   +1 more source

Distribution and Growth Drivers of Oases at a Global Scale

Earth's Future, Volume 12, Issue 4, April 2024.
Abstract The human‐environmental system in drylands is centered on oases. Despite its extent and socio‐ecological importance, understanding the dynamic changes of global oases and their human and environmental driving forces is imperative for sustainable development in drylands under global warming. Nevertheless, the dynamic changes of global oases and
Bochao Cui, Dongwei Gui, Qi Liu, Sameh Kotb Abd‐Elmabod, Yunfei Liu, Binbin Lu   +5 more
wiley   +1 more source

Spatiotemporal Evolution and Driving Mechanisms of Bike-Sharing-to-Metro Feeder Trips Based on OPGD-GTWR Models

Applied Sciences
Clarifying the spatiotemporal evolution and driving mechanisms of bike-sharing-to-metro feeder trips (BSMF) is key to optimizing urban public transport’s first-and-last-mile connectivity and advancing low-carbon development.
Wei Li, Dong Dai, Yixin Chen, Hong Chen, Zhaofei Wang   +4 more
doaj   +1 more source

Spatiotemporal Varying Effects of Built Environment on Taxi and Ride-Hailing Ridership in New York City

ISPRS International Journal of Geo-Information, 2020
The rapid growth of transportation network companies (TNCs) has reshaped the traditional taxi market in many modern cities around the world. This study aims to explore the spatiotemporal variations of built environment on traditional taxis (TTs) and TNC.
Xinxin Zhang, Bo Huang, Shunzhi Zhu
doaj   +1 more source

Understanding the Spatial Variation of Integrated Use of Ride‐Hailing Services With the Metro

Journal of Advanced Transportation, Volume 2024, Issue 1, 2024.
This study aims to explore the spatial heterogeneity of influential factors of integrated use of ride‐hailing service with the metro. Using the operation data of ride‐hailing services in Chengdu, China, first, an identification method of integrated ride‐hailing trips is proposed.
Mingyang Du, Zhicheng Li, Xuefeng Li, Jiacong Xu, Dong Liu, Mei-Po Kwan, Hongtai Yang   +6 more
wiley   +1 more source

Reciprocal growth and spatial spillover: From the perspective of agricultural trade competitiveness in countries along the BRI route

International Review of Economics & Finance
Based on the cross-country panel data from 2007 to 2024, this study employs the entropy weight model, PSM-DID method, DID spatial model, and Geographically and Temporally Weighted Regression (GTWR) Model to evaluate how the ''Belt and Road'' initiative ...
Jingbo Ning, Yuhan Gao, Lei Dou
doaj   +1 more source