Geospatial Machine Learning

Master AI, Deep Learning and ML for Geospatial Analysis

Master AI, Deep Learning and ML for Geospatial Analysis

Become Expert in advanced Remote Sensing/GIS pixel-based & and object-based image analysis in Google Earth Engine & QGIS.

This book addresses the mapping of soil-landscape parameters in the geospatial domain. It begins by discussing the fundamental concepts, and then explains how machine learning and geomatics can be applied for more efficient mapping and to improve our understanding and management of ‘soil’. The judicious utilization of a piece of land is one of the biggest and most important current challenges, especially in light of the rapid global urbanization, which requires continuous monitoring of resource consumption.

Understand/ apply machine learning in Geographic information systems and Remote Sensing in QGIS and Google Earth Engine.

Building an Analytics Dashboard to Analyze and Predict Quakes using Bokeh and Python

As computer and space technologies have been developed, geoscience information systems(GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields.