Regression analysis of spatial data
Ecology Letters (2010) 13: 246–264 Abstract Many of the most interesting questions
ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number …
ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number …
Effects of incorporating spatial autocorrelation into the analysis of species distribution data
CF Dormann - Global ecology and biogeography, 2007 - Wiley Online Library
Aim Spatial autocorrelation (SAC) in data, ie the higher similarity of closer samples, is a
common phenomenon in ecology. SAC is starting to be considered in the analysis of …
common phenomenon in ecology. SAC is starting to be considered in the analysis of …
Examining spectral reflectance saturation in Landsat imagery and corresponding solutions to improve forest aboveground biomass estimation
The data saturation problem in Landsat imagery is well recognized and is regarded as an
important factor resulting in inaccurate forest aboveground biomass (AGB) estimation …
important factor resulting in inaccurate forest aboveground biomass (AGB) estimation …
Evaluation of the effect of geographical parameters on the formation of the land surface temperature by applying OLS and GWR, A case study Shiraz City, Iran
Examining the land surface temperature (LST) and its mechanism is very significant for
urban planning. The purpose of this study is to determine the factors affecting the surface …
urban planning. The purpose of this study is to determine the factors affecting the surface …
Multi-scale analysis of spatially varying relationships between agricultural landscape patterns and urbanization using geographically weighted regression
S Su, R Xiao, Y Zhang - Applied Geography, 2012 - Elsevier
Scientific interpretation of the relationships between agricultural landscape patterns and
urbanization is important for ecological planning and management. Ordinary least squares …
urbanization is important for ecological planning and management. Ordinary least squares …
Investigating spatial non-stationary and scale-dependent relationships between urban surface temperature and environmental factors using geographically weighted …
S Li, Z Zhao, X Miaomiao, Y Wang - Environmental Modelling & Software, 2010 - Elsevier
Despite growing concerns for the variation of urban thermal environments and driving
factors, relatively little attention has been paid to issues of spatial non-stationarity and scale …
factors, relatively little attention has been paid to issues of spatial non-stationarity and scale …
Spatially non-stationary relationships between urban residential land price and impact factors in Wuhan city, China
S Hu, S Yang, W Li, C Zhang, F Xu - Applied Geography, 2016 - Elsevier
Land price plays an important role in guiding land resource allocation for urban planning
and development, particularly in big cities of fast developing countries where infrastructures …
and development, particularly in big cities of fast developing countries where infrastructures …
The use of geographically weighted regression for spatial prediction: an evaluation of models using simulated data sets
Increasingly, the geographically weighted regression (GWR) model is being used for spatial
prediction rather than for inference. Our study compares GWR as a predictor to (a) its global …
prediction rather than for inference. Our study compares GWR as a predictor to (a) its global …
Predictive mapping of soil total nitrogen at a regional scale: A comparison between geographically weighted regression and cokriging
K Wang, C Zhang, W Li - Applied Geography, 2013 - Elsevier
Accurately mapping the spatial distribution of soil total nitrogen is important to precision
agriculture and environmental management. Geostatistical methods have been frequently …
agriculture and environmental management. Geostatistical methods have been frequently …