Landuse landcover with machine learning using ArcGIS only

Creating land use maps is a complex process often plagued by errors and low accuracy rates. For instance, barren land or riverbeds may be misclassified as urban areas. To address these errors, it typically requires the use of multiple software tools, as a single software package may not be sufficient for all processes, such as post-classification pixel corrections. Often, other software is used alongside ArcGIS to correct these misclassifications because ArcGIS lacks a dedicated tool for pixel correction.

However, in this course, we have successfully managed to perform all tasks using ArcGIS alone. Land use classification is accomplished using machine learning techniques, specifically the Support Vector Machine (SVM) and Random Forest methods, through supervised training. Even post-classification pixel correction is handled within ArcGIS using specific strategies.

If you prefer to rely solely on ArcGIS without using any additional software, this course is designed for you. The first few videos are free. Here is the link.

Link to course: https://www.udemy.com/course/landuse-landcover-with-machine-learning-using-arcgis-only/?couponCode=AILANDUSE

Things that covered

Land use mapping

Land cover classification

ArcGIS machine learning

SVM land use classification

Random Forest land use mapping

Post-classification pixel correction

ArcGIS pixel correction

Supervised training ArcGIS

Land use errors correction

Urban area misclassification corrections

ArcGIS land use course

Barren land classification corrections 

Riverbed misclassification corrections

Single software land use mapping

ArcGIS only land use mapping

High accuracy land cover mapping

Machine learning in ArcGIS

Land use mapping techniques

Land cover classification errors corrections