Geotechnical engineering is concerned with the application of civil engineering technology to some aspect of the earth, usually the natural materials found on or near the earth's surface. Civil engineers call these materials soil and rock. Soil, in an engineering sense, is the relatively loose agglomerate of mineral and organic materials and sediments found above the bedrock. Soils can be relatively easily broken down into their constituent mineral or organic particles. Rock, on the other hand, has very strong internal cohesive and molecular forces which hold its constituent mineral grains together. This is true for massive bedrock as well as for a piece of gravel found in a clay soil. The dividing line between soil and rock is arbitrary, and many natural materials encountered in engineering practice cannot be easily classified. They may be either a "very soft rock" or a "very hard soil." <...>

Metamorph;c processes have been taking place on a massive scale throughout the Earth's history, and have affected the bulk of the rocks now present in the crust. Despite this, they are not as well understood as sedimentary or volcanic processes, because metamorphism can scarcely ever be observed directly, and the study of metamorphic rocks is instead based on observation, inference and logic, founded in relatively simplistic experimental studies and the basic principles of chemistry and physics

The past three decades have seen a remarkable proliferation in the volume of literature devoted to geotechnical and foundation engineering. There are now a vast number of journals that address these subjects, and many conferences annually produce a welter of papers of variable quality. The undergraduate student is insulated from this plethora of information by curricula that usually follow a well-trodden path and which cover the basics of soil mechanics and engineering mechanics and which employ texts that have been tried, tested and refined over the past 50 years.

This book is the first in a two-volume series that introduces the field of spatial data science. It offers an accessible overview of the methodology of exploratory spatial data analysis. It also constitutes the definitive user’s guide for the widely adopted GeoDa open-source software for spatial analysis. Leveraging a large number of real-world empirical illustrations, readers will gain an understanding of the main concepts and techniques, using dynamic graphics for thematic mapping, statistical graphing, and, most centrally, the analysis of spatial autocorrelation. Key to this analysis is the concept of local indicators of spatial association, pioneered by the author and recently extended to the analysis of multivariate data.