Geographically Weighted Method Integrated with Logistic Regression for Analyzing Spatially Varying Accuracy Measures of Remote Sensing Image Classification

Geographically Weighted Regression the analysis of spatially varying relationships

Local least absolute deviation estimation of spatially varying coefficient models: robust geographically weighted regression approaches

This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date...

On Chance-adjusted Measures for Accuracy Assessment in Remote Sensing Image Classification

The underlying rationale and practical utility of chance-adjusted indices (e.g., kappa, tau) as accuracy measures in remote sensing image classification have been under criticism for a long time despite the fact that they are near universally used. It has been suggested that the degree of chance agreement may be overestimated, or it makes no sense to use kappa or tau for their declared objectiv...

Remote Sensing Image Classification

Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity

model which allows diferent relationships to exist at diferent points in space. This technique is loosely based on kernel regression. The method itself is introduced and related issues such as the choice of a spatial weighting function are discussed. Following this, a series of related statistical tests are considered which can be described generally as tests f o r spatial nonstationarity. Usin...