Week01
61 slides
What Is GIS and Why Is It Used?
GIS as a decision-support framework, its core components, applications and evolving relationship with artificial intelligence.
Teaching & open materials
Knowledge grows when it is shared.
Lecture presentations prepared for GIS and GeoAI courses.
MIS 369
AI-Enhanced Geographic Information Systems
A 14-week course connecting GIS foundations with spatial machine learning, deep learning, explainable AI and responsible GeoAI practice.
Week02
43 slides
Spatial Data and Data Models
Vector and raster models, attribute structures, topology and representations of spatial phenomena.
Week03
43 slides
Map Design and Spatial Visualization
Cartographic principles, visual hierarchy, symbology and effective communication of spatial information.
Week04
43 slides
Coordinate Systems and Map Projections
Datums, coordinate reference systems, projection selection and transformation-related errors.
Week05
43 slides
Data Quality and Geodatabase Management
Positional accuracy, data integrity, quality control and geodatabase design.
Week06
43 slides
Vector-Based Spatial Analysis
Conceptual and applied foundations of buffer, overlay, proximity and network-based analysis.
Week07
43 slides
Raster Analysis, Remote Sensing and Land Cover
Raster operations, satellite image analysis, classification and land-cover information extraction.
Week08
43 slides
Web GIS, Cloud and Midterm Review
Web GIS architectures, cloud services and an integrated review of the first-half course topics.
Week09
36 slides
Foundations of GeoAI and Spatial Machine Learning
GeoAI concepts, spatial learning problems, feature engineering and the risk of spatial data leakage.
Week10
36 slides
Supervised Spatial Machine Learning
Classification and regression, model selection, spatial cross-validation and performance metrics.
Week11
36 slides
Spatial Patterns, Clustering and Anomaly Analysis
Spatial autocorrelation, clustering, hot-spot analysis and spatial outlier detection.
Week12
36 slides
Deep Learning for Geospatial Image Analysis
CNN-based methods, object detection, segmentation and interpretation of geospatial imagery.
Week13
36 slides
Advanced GeoAI, Foundation Models, XAI and Responsible Use
Foundation models, explainable AI, ethical risks, uncertainty and principles for responsible GeoAI.
Week14
36 slides
GeoAI Final Project Studio
Problem framing, data and method design, validation, interpretation and final project presentation.
© Murat Başeğmez · For educational use with attribution.