نتایج جستجو برای: geographically weighted regression
تعداد نتایج: 422966 فیلتر نتایج به سال:
Soil organic matter (SOM) is an important component of soils, and knowing the spatial distribution and variation of SOM is the premise for sustainably utilizing soils. The objective of this study was to compare geographically weighted regression (GWR) with regression kriging (RK) for estimating the spatial distribution of SOM using field-sample data in SOM and auxiliary data in correlated envir...
This study is concerned with the relationship between transport accessibility and increases in land value, motivated by a desire to inform the land value capture debate. Focusing on residential land, here land value is examined through the form of house prices, using the Tyne and Wear Region of the UK as a case study. In a typical hedonic price model, adopted widely in property studies, the ass...
The technique of geographically weighted regression (GWR) is used to model spatial ‘drift’ in linear model coefficients. In this paper we extend the ideas of GWR in a number of ways. First, we introduce a set of analytically derived significance tests allowing a null hypothesis of no spatial parameter drift to be investigated. Second, we discuss ‘mixed’ GWR models where some parameters are fixe...
SUMMARY The primary objective of this study was to assess a human-induced dryland degradation in the cachment basin of the Balkhash Lake in the Middle Kazakhstan based on time series of rainfall data and normalized difference vegetation index (NDVI) for the period 1985-2000. We developed a method to remove the climatic signal from the change in vegetation activity over the study period. By appl...
Although relationships between fragmentation of urban development and other forms of administrative and land cover fragmentation are important, they are poorly understood. This research aimed to better understand these relationships in order to inform land use planning in the Roaring Fork/Colorado River Corridor of Colorado. Change in fragmentation of urban development between 1985 and 1999 was...
Despite the growing ubiquity of sensor deployments and the advances in sensor data analysis technology, relatively little attention has been paid to the spatial non-stationarity of sensed data which is an intrinsic property of the geographically distributed data. In this paper we deal with non-stationarity of geographically distributed data for the task of regression. At this purpose, we extend...
The effective use of spatial information, that is the geographic locations of population units, in a regression model-based approach to small area estimation is an important practical issue. One approach for incorporating such spatial information in a small area regression model is via Geographically Weighted Regression (GWR). In GWR the relationship between the outcome variable and the covaria...
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