Geography has always been important to humans. Stone-age hunters anticipated the location of their quarry, early explorers lived or died by their knowledge of geography, and current societies work and play based on their understanding of who belongs where. Applied geography, in the form of maps and spatial information, has served discovery, planning, cooperation, and conflict for at least the past 3000 years (Figure 1-1). Maps are among the most beautiful and useful documents of human civilization.

Welcome to GIS Tutorial for Pro 2.8. This fourth-edition step-by-step workbook focuses on ArcGIS Pro but also covers Online and some of its major apps for mobile computing, including
Dashboards, and Collector.

The natural resources on the earth seem to be randomly distributed but their variations over space and time are not all random. They exhibit a spatial correlation. This spatial correlation can be captured by geostatistics. Geostatistics deals with the analysis and modelling of geo-referenced data. The point observations are analyzed and interpolated to create spatial maps. For geostatistical interpolation, first the spatial correlation structures of the parameter of interest are quantified and then spatial interpolation is done using the quantified spatial correlation and optimal predictions at unobserved locations to create a map.

Вы приступаете к изучению расширения к ArcGIS компании ESRI®  модуля Geostatistical Analyst, предназначенного для усовершенствованного моделирова ния поверхности с использованием детерминистских и геостатистических методов. Модуль Geostatistical Analyst расширяет возможности ArcMap за счет появления дополнительных инструментов, предназначенных для исследовательского анализа пространственных данных, а также Мастера операций геостатистики, который поможет вам в процессе построения статистически достоверной поверхности. Поверхности, создаваемые с помощью модуля Geostatistical Analyst, могут быть впоследствии использованы в моделях ГИС и для визуализации, в том числе с использованием таких расширений ArcGIS, как ArcGIS Spatial Analyst и 3D Analyst. <...>

This book is an introduction to critical cartography and GIS. As such, it is neither a textbook nor a software manual. My purpose is to discuss various aspects of mapping theory and practice, from critical social theory to some of the most interesting new mapping practices such as map hacking and the geospatial web. It is an appreciation of a more critical cartography and GIS.

GIS Applications in Agriculture, Volume Four: Conservation Planning, edited by Tom Mueller and Gretchen F. Sassenrath, is the fourth volume in the book series GIS Applications in Agriculture, which is designed to enhance the application and use of geographic information systems (GISs) in agriculture by providing detailed GIS applications that are useful to scientists, educators, students, consultants, and farmers. The first volume, GIS Applications in Agriculture, edited by Francis J. Pierce and David Clay, was published by CRC Press in 2007. The second volume, GIS Applications in Agriculture: Nutrient Management for Improved Energy Efficiency, edited by David Clay and John Shanahan, and the third volume, GIS Applications in Agriculture: Invasive Species, edited by Sharon Clay, were published by CRC Press in 2011. While the newest book in this series, the idea of a book on conservation planning using GIS was identified in 2007 when the book series began. Intuitively, conservation planning through GIS applications should appeal to all conservationists who clearly understand that a key to achieving soil and water conservation is rooted in an understanding of the spatial and temporal variation in both soil and water resources and natural and human-induced forces that affect the quality and quantity of those resources. <...>

GIS Tutorial 1: Basic Workbook is the direct result of the authors' experiences teaching GIS to high school students in a summer program at Carnegie Mellon University, undergraduate and graduate students in several departments and disciplines at Carnegie Mellon University, as well as working professionals. GIS Tutorial 1 is a hands-on workbook with step-by-step exercises that take the reader from the basics of using ArcGlS Desktop interfaces through performing advanced spatial analyses. <...>

In this introductory chapter we describe general problems of spatial environmental data analysis, modeling, validation and visualization. Many of these problems are considered in detail in the following chapters using geostatistical models, machine learning algorithms (MLA) of neural networks and Support Vector Machines, and the Bayesian Maximum Entropy (BME) approach. The term “mapping” in the book is considered not only as an interpolation in two- or threedimensional geographical space, but in a more general sense of estimating the desired dependencies from empirical data.

Geostatistics aims at providing quantitative descriptions of natural variables distributed in space or in time and space. Examples of such variables are 

Ore grades in a mineral deposit 

Depth and thickness of a geological layer 

Porosity and permeability in a porous medium 

Density of trees of a certain species in a forest 

Soil properties in a region 

Rainfall over a catchment area 

Pressure, temperature, and wind velocity in the atmosphere
Concentrations of pollutants in a contaminated site

Geostatistical simulation makes strong assumptions of stationarity in the mean and the variance over the domain of interest. Unfortunately, geological nature usually does not reflect this assumption and we are forced to subdivide our model area into stationary regions that have some common geological controls and similar statistical properties. This paper addresses the significant complexity introduced by boundaries. Boundaries are often soft, that is, samples near boundaries influence multiple rock types.