Map** the results of geographically weighted regression
J Mennis - Landmarks in Map**, 2017 - taylorfrancis.com
Geographically weighted regression (GWR) is a local spatial statistical technique for
exploring spatial nonstationarity. This chapter reviews previous approaches to map** the …
exploring spatial nonstationarity. This chapter reviews previous approaches to map** the …
Rainfall spatial estimations: A review from spatial interpolation to multi-source data merging
Q Hu, Z Li, L Wang, Y Huang, Y Wang, L Li - Water, 2019 - mdpi.com
Rainfall is one of the most basic meteorological and hydrological elements. Quantitative
rainfall estimation has always been a common concern in many fields of research and …
rainfall estimation has always been a common concern in many fields of research and …
[HTML][HTML] Examining the association between socio-demographic composition and COVID-19 fatalities in the European region using spatial regression approach
The socio-demographic factors have a substantial impact on the overall casualties caused
by the Coronavirus (COVID-19). In this study, the global and local spatial association …
by the Coronavirus (COVID-19). In this study, the global and local spatial association …
Exploring differentiated impacts of socioeconomic factors and urban forms on city-level CO2 emissions in China: Spatial heterogeneity and varying importance levels
Z Li, F Wang, T Kang, C Wang, X Chen, Z Miao… - Sustainable Cities and …, 2022 - Elsevier
Excessive anthropogenic carbon emissions due to rapid socioeconomic development and
urban expansion have resulted in significant climate change. Different levels of …
urban expansion have resulted in significant climate change. Different levels of …
Sociodemographic determinants of COVID-19 incidence rates in Oman: Geospatial modelling using multiscale geographically weighted regression (MGWR)
The current COVID-19 pandemic is evolving rapidly into one of the most devastating public
health crises in recent history. By mid-July 2020, reported cases exceeded 13 million …
health crises in recent history. By mid-July 2020, reported cases exceeded 13 million …
GWmodel: an R package for exploring spatial heterogeneity using geographically weighted models
Spatial statistics is a growing discipline providing important analytical techniques in a wide
range of disciplines in the natural and social sciences. In the R package GWmodel we …
range of disciplines in the natural and social sciences. In the R package GWmodel we …
Geographically weighted regression based methods for merging satellite and gauge precipitation
Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate
hydrological forecasting. To improve the spatial resolution and quality of satellite …
hydrological forecasting. To improve the spatial resolution and quality of satellite …
[HTML][HTML] Responses of ecosystem services to natural and anthropogenic forcings: A spatial regression based assessment in the world's largest mangrove ecosystem
Most of the Earth's Ecosystem Services (ESs) have experienced a decreasing trend in the
last few decades, primarily due to increasing human dominance in the natural environment …
last few decades, primarily due to increasing human dominance in the natural environment …
Inequality of public health and its role in spatial accessibility to medical facilities in China
Due to the close links between quality of life standards and level of regional development, it
is important to gain an improved understanding of the factors that contribute to unequal …
is important to gain an improved understanding of the factors that contribute to unequal …
The GWmodel R package: further topics for exploring spatial heterogeneity using geographically weighted models
In this study, we present a collection of local models, termed geographically weighted (GW)
models, which can be found within the GWmodel R package. A GW model suits situations …
models, which can be found within the GWmodel R package. A GW model suits situations …