How Do Temporal and Geographical Kernels Differ in Reflecting Regional Disparities? Insights from a Case Study in China DOI Creative Commons
Chunzhu Wei, Xufeng Liu, Wei Chen

et al.

Land, Journal Year: 2024, Volume and Issue: 14(1), P. 59 - 59

Published: Dec. 31, 2024

Rapid economic growth in China has brought about a significant challenge: the widening gap regional development. Addressing this disparity is crucial for ensuring sustainable However, existing studies have largely overlooked intrinsic spatial and temporal dynamics of disparities on various levels. This study thus employed five advanced multiscale geographically temporally weighted regression models—GWR, MGWR, GTWR, MGTWR, STWR—to analyze spatio-temporal relationships between ten key conventional socio-economic indicators per capita GDP across different administrative levels from 2000 to 2019. The findings highlight consistent increase disparities, with secondary industry emerging as dominant driver long-term inequality among analyzed. While clear inland-to-coastal gradient underscores persistence determinants, areas greater exhibit pronounced heterogeneity. Among models, STWR outperforms others capturing interpreting local variations demonstrating its utility understanding complex dynamics. provides novel insights into determinants offering robust analytical framework policymakers address region-specific variables driving over time space. These contribute development targeted dynamic policies promoting balanced growth.

Language: Английский

Prediction of Vanadium Contamination Distribution Pattern Through Remote Sensing Image Fusion and Machine Learning DOI Creative Commons

Z. G. Zhao,

Yuman Sun, Weiwei Jia

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(7), P. 1164 - 1164

Published: March 25, 2025

Soil vanadium contamination poses a significant threat to ecosystems. Hyperspectral remote sensing plays critical role in extracting spectral features of heavy metal contamination, mapping its spatial distribution, and monitoring trends over time. This study targets vanadium-contaminated area Panzhihua City, Sichuan Province. sampling measurements occurred the laboratory. (Gaofen-5, GF-5) multispectral (Gaofen-2, GF-2; Sentinel-2) images were acquired preprocessed, feature bands extracted by combining laboratory data. A dual-branch convolutional neural network (DB-CNN) fused hyperspectral confirmed fusion’s effectiveness. Six prevalent machine learning models adopted, unified framework leveraged Random Forest (RF) as second-layer model enhance predictive performance these base models. Both ensemble evaluated based on accuracy. The fusion process enhanced models, improving R2 values for (V) pentavalent (V5+) from 0.54 0.3 0.58 0.39, respectively, at 4 m resolution. Further optimization using RF refine Extreme Trees (ETs) significantly increased 0.83 0.75 V V5+, this scale. 934 nm 464 wavelengths identified most predicting soil contamination. integrated approach robustly delineates distribution characteristics V5+ soils, facilitating precise ecological risk assessments through comparative analysis accuracy across diverse

Language: Английский

Citations

0
Unlocking the nonlinear TOD-metro ridership relationship: A novel machine learning approach embedding spatiotemporal heterogeneity DOI
Yun Luo,

Bozhao Li,

Hui Zhang

et al.

Journal of Transport Geography, Journal Year: 2025, Volume and Issue: 126, P. 104222 - 104222

Published: April 8, 2025

Language: Английский

Citations

0
Prediction of blast vibration velocity based on multi-model dynamic weighting ensemble DOI

Weisu Weng,

M. Zhang, Yan Zhao

et al.

Mechanics of Advanced Materials and Structures, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 18

Published: April 27, 2025

Language: Английский

Citations

0
How Do Temporal and Geographical Kernels Differ in Reflecting Regional Disparities? Insights from a Case Study in China DOI Creative Commons
Chunzhu Wei, Xufeng Liu, Wei Chen

et al.

Land, Journal Year: 2024, Volume and Issue: 14(1), P. 59 - 59

Published: Dec. 31, 2024

Rapid economic growth in China has brought about a significant challenge: the widening gap regional development. Addressing this disparity is crucial for ensuring sustainable However, existing studies have largely overlooked intrinsic spatial and temporal dynamics of disparities on various levels. This study thus employed five advanced multiscale geographically temporally weighted regression models—GWR, MGWR, GTWR, MGTWR, STWR—to analyze spatio-temporal relationships between ten key conventional socio-economic indicators per capita GDP across different administrative levels from 2000 to 2019. The findings highlight consistent increase disparities, with secondary industry emerging as dominant driver long-term inequality among analyzed. While clear inland-to-coastal gradient underscores persistence determinants, areas greater exhibit pronounced heterogeneity. Among models, STWR outperforms others capturing interpreting local variations demonstrating its utility understanding complex dynamics. provides novel insights into determinants offering robust analytical framework policymakers address region-specific variables driving over time space. These contribute development targeted dynamic policies promoting balanced growth.

Language: Английский

Citations

0