Mathematics and Spatial Analysis Notes

Mathematics and Spatial Analysis Notes#

This repository is a Jupyter Book collection of notes and interactive chapters covering mathematical foundations and spatial learning topics.

About This Book#

The content is organized around the repository’s current structure and TOC. It focuses on:

  • core Linear Algebra concepts used in spatial and machine learning applications

  • Calculus principles for limits, derivatives, and indeterminate forms

  • Optimization and regularization techniques for model fitting and generalization

  • Spatial learning and spatial autocorrelation methods for geographic data analysis

Author#

I am a Research Associate and GIS Programmer at the West Virginia GIS Technical Center, West Virginia University. These notes support my work in Geographic Information Science, urban environment modeling, and spatial data analytics.

Education#

  • 2019–2024   Ph.D. in Geospatial Information Sciences, University of Texas at Dallas, Texas, USA

  • 2017–2019   M.A. in Geography, Binghamton University (SUNY), New York, USA

  • 2013–2017   B.S. in Geographic Information Science, Yunnan University, Yunnan, China

Current Sections#

The current book sections are:

  • Linear Algebra

  • Calculus

  • Optimization

  • Spatial Learning

Contents