Geospatial analysis-principles, technologies and software tools

Recently, Smith and m.j wrote the geospatial analysis-principles, technologies, and software tools. In terms of depth and breadth, this book is excellent in the space analysis books I have read, and may be difficult for beginners. However, it is very suitable for those who have a certain space analysis foundation, both the depth and accuracy of Content Framework and description parsing are impressive. For simple GIS applications, it may be a little complicated, but you should look at it if you are a pure GIS professional.

 

However, it may be the reason for translation. The expression of many statements is quite cool and not very smooth, so the thinking jumps faster, presumably this book took a lot of twists and turns during translation, and there was no need to take notes for purely spatial analysis theories and methods, but there were some good sentences to express, for example, in the chapter of geographic modeling, "a model must be built at an appropriate level of description for each phenomenon and be good at using a proper amount of detailed information for modeling purposes, this is more of an art than a science. "It is very accurate. Here are some Excerpt from the sentence. The right is a note:

 

 

Application is the driving force of GIS development.

3D ry and image-real-world visualization are essential elements of modern systems.

GIS commercial software is mainly driven by demands and applications and is embodied in the willingness to invest. Therefore, to a large extent, the available functions often reflect the reality of business and resources, rather than the development status of Geographical Science.

Spatial statistics is, to a large extent, an observation science rather than an experimental science.

Data analysis includes data-driven methods and model-driven methods.

Pay attention to the differences between space generalization attributes (density and so on) and space fine attributes (total amount and so on.

From a mathematical perspective, if an attribute can still be retained when the space is stretched or distorted, it is called a topology. In other words, topological properties are those that cannot be stretched or distorted.

Spatial Heterogeneity and spatial dependence.

The statistical process can be summarized as ppdac (problem, plan, data, analysis, and conclusion ). This is also a process model of spatial analysis.

Focus on "Space Culture ".

Spatial thinking is a cognitive skill that builds questions, answers, and uses spatial characteristics to express solutions in daily life, workplace, and science.

Data analysis should be probe, as part of a completely in-depth analysis process.

Question about the carrier: select a route for each vertex in the set point and return to the starting point. To minimize the length of the Line.

The service areas tool in network analyst in ArcGIS is used for service area analysis. A tool provided by many GIS software for determining service areas is to define travel time zones. This is the former commuting analysis (within one hour ).

Definition of geographic computing: art and science that uses computers to solve complex spatial problems.

GIS is gradually showing the trend of using standardized programming languages and scripting languages in the industry, rather than using specialized and developed scripting languages.

Coupling can be broadly positioned as two independent systems connected through data transmission. For example, repast and ArcGIS.

A model must be built at an appropriate level of description for each phenomenon, and be good at using a proper amount of detailed information for modeling purposes. This is more of an art than a science.

Modelers of complex systems cannot enjoy the intellectual advantage of modeling patterns.

Typical applications of REPAST include racial isolation, residential and enterprise site selection, etc.