Geostatistical Methods for Scaling

• Published in: Scale in Spatial Information and Analysis pp. 121 - 142
• Main Authors: Zhang, Jingxiong, Atkinson, Peter, Goodchild, Michael F.
• Format: Book Chapter
• Language: English
• Published: United States CRC Press 2014; Taylor & Francis Group
• Subjects: ENVIRONMENTAL ENGINEERING & TECHNOLOGY; Geographical information systems (GIS) & remote sensing; Human geography; Areal Interpolation; Transition Probability Models; Ordinary Kriging; Kriging Weights; Kriging Variance; Kriging Prediction; Areal Data; Universal Kriging; LAI NDVI Relationship; Block Kriging; Spatial Prediction; Unsampled Location; Geostatistical Methods; Indicator Geostatistics; Yao 2008a; Yao 2008b; Simple Kriging; Kriging Equations; Spatial Structural Information; Ath Entry; Landsat TM Image; Cumulative Distribution Functions; Inverse Problem; Geostatistical Approach; Indicator Kriging
• ISBN: 9781439829370; 1439829373
• DOI: 10.1201/b16751-10

Chapters 4 and 5 described variogram-and autocorrelation-based approaches to modeling scale, which are designed for geostatistical and lattice data, respectively. As mentioned toward the end of Chapter 5, this chapter seeks to describe geostatistical methods for scaling, whereas the next chapter addresses methods for scaling lattice data (e.g., various images or raster data).