🎁 Advanced Remote Sensing Techniques 🌍

All course offered from Udemy : Discounted links updated 2025

Course 1: Landuse Landcover with Machine Learning Using ArcGIS Only

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🔹 Highlights:

• Master the application of machine learning in ArcGIS for land use and land cover analysis.

• Learn advanced techniques for image classification using only ArcGIS tools.

• Gain hands-on experience with real-world data and case studies.

Course 2: Crop Yield Estimation using Remote Sensing and GIS ArcGIS
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🔹 Highlights:

• Discover the power of remote sensing and GIS in predicting crop yields.

• Step-by-step guidance on data collection, processing, and analysis.

• Real-world applications and project-based learning to enhance your skills.

Course 3: SWAT CUP Calibration Validation and Write Values to ArcSWAT
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🔹 Highlights:

• Understand the complete process of SWAT model calibration and validation.

• Learn how to integrate SWAT CUP with ArcSWAT for enhanced hydrological modeling.

• Practical examples to solidify your understanding and application.

Course 4: Complete Remote Sensing and GIS - ArcGIS – ERDAS
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🔹 Highlights:

• Comprehensive coverage of GIS and remote sensing fundamentals using ArcGIS and ERDAS.

• Learn how to perform essential GIS tasks with ease.

• Perfect for beginners and those looking to refresh their knowledge.

Course 5: Groundwater Potential Zones GIS - Complete Project ArcGIS
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🔹 Highlights:

• Conduct a complete groundwater potential zone assessment using GIS.

• Learn through a hands-on project that simulates real-world scenarios.

• Enhance your understanding of water resource management with GIS.

Course 6: Land Use Land Cover Classification GIS, ERDAS, ArcGIS, ML
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🔹 Highlights:

• Dive deep into land use and land cover classification using multiple GIS platforms.

• Explore machine learning techniques integrated with GIS and remote sensing.

• Apply your skills in ERDAS, ArcGIS, and other industry-standard tools.

Course 7: Future Land Use with GIS - TerrSet - CA Markov – ArcGIS
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🔹 Highlights:

• Predict future land use patterns using the CA-Markov model in TerrSet.

• Integrate results with ArcGIS for comprehensive spatial analysis.

• Practical exercises to master future land use modeling.

Course 8: ArcSWAT Model with ArcGIS - Run for Any Study Area – GIS
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🔹 Highlights:

• Learn how to run the ArcSWAT model for any geographic area.

• Comprehensive coverage of model setup, data preparation, and analysis.

• Perfect for professionals working in hydrology and water resource management.

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