Common Errors Faced by GIS Users in LULC Classification

 

1. Misclassification Between Urban and Barren Lands

Many users report that barren lands are often misclassified as urban areas when using SVM or Random Forest in ArcGIS. This usually happens due to spectral similarity or insufficient training samples.

2. Low Classification Accuracy Despite Using High-Resolution Imagery

Even after using high-resolution Sentinel-2 or Landsat data, users complain that the classification result appears blurred or contains mixed pixels. This is typically due to improper training sample selection or lack of feature extraction.

3. Overlapping Classes in the Signature File

Improper class definition during supervised classification can cause overlap between land use types such as agriculture and vegetation, making post-classification analysis unreliable.

4. Errors in Training Sample Collection

One of the most overlooked but impactful issues is the collection of biased or non-representative training samples. Poor sample distribution across classes leads to unbalanced results and lowers classifier performance.

5. Missing Steps in Image Preprocessing

Skipping crucial steps like atmospheric correction or layer stacking often results in low classifier confidence. Users working with raw imagery directly in ArcGIS report consistent issues with reflectance inconsistency.

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✅ Suggested Fix for the Above Issues:

To tackle these problems effectively, users need a structured workflow, real-time guidance, and practical examples. If you're tired of running into classification errors and spending hours debugging ArcGIS processes, it's time to upgrade your skills with a hands-on approach.

🎓 Learn the Complete Workflow from Start to Finish

Explore this step-by-step course designed specifically to handle Land Use Classification using Machine Learning in ArcGIS:

👉 Landuse Landcover with Machine Learning Using ArcGIS Only

This course covers:

• Training sample strategy

• Image preprocessing

• SVM classification settings

• Accuracy assessment

• Real-world LULC projects using ArcGIS only

Don’t let these common issues hold you back. Get equipped with the right tools and expert-led instructions to deliver high-quality land use maps using only ArcGIS.