GEOSPATIAL APPLICATION DEVELOPMENT USING PYTHON PROGRAMMING.

Academics and researchers currently grapple with a pressing issue; the demand for precise and insightful geographical information has surged across various fields, encompassing urban planning, environmental monitoring, agriculture, and disaster management. This surge has revealed a substantial knowledge gap, underscoring the need for effective applications that can bridge the gap between cutting-edge technologies and practical usage. Geospatial Application Development Using Python Programming emerges as the definitive solution to this challenge. This comprehensive book equips academics, researchers, and professionals with the essential tools and insights required to leverage the capabilities of Python programming in the realm of spatial analysis. It goes beyond merely connecting these two realms; it actively fosters their collaboration. By advancing knowledge in spatial sciences and highlighting Python’s pivotal role in data analysis and application development, this book plays a crucial part in addressing the challenge of effectively harnessing geographical data. Title Page Copyright Page Book Series Table of Contents Detailed Table of Contents Foreword Preface Chapter 1: Introduction to Geospatial Data and Python Programming Chapter 2: Python Programming for Geospatial Applications Chapter 3: Python-Powered Remote Sensing Data Chapter 4: Towards Spatial Data Visualization With Python Chapter 5: Spatial Data Visualization With Python Chapter 6: Exploring Vector and Raster Data Formats for Geospatial Visualization With Python Chapter 7: Geospatial Data Visualization With Folium Chapter 8: Applying Geospatial Data to Choose the Optimal Route During the Road Design Stage Chapter 9: Python Library for Road Network Analysis in the Case of Debre Berhan City Chapter 10: Impacts of Climate Changes on Traffic Flows Using Geospatial Data Analysis Chapter 11: Deep Learning Approach to Estimate the Maize Yield Prediction Using Data From Cameroon Compilation of References About the Contributors Index