IJIRCSTJournal International Journal of Innovative Research in Computer Science and Technology I S Volume 12 Issue 2 Computer Science and Engineering English March - April 2024 N N Y 2024 04 20 Computer Sciences Machine Learning Approaches in Spatial Data Mining English Y 140 148 Shalini Bhaskar Bajaj English Y Ashima Narang English N Priyanka Vashisth English N https://doi.org/10.55524/ijircst.2024.12.2.25 This review paper surveys the integration of machine learning techniques in spatial data mining, a crucial intersection of geographic information systems and data mining. It examines the application of various machine learning algorithms such as classification, regression, clustering, and deep learning in spatial data analysis. The paper discusses challenges like data preprocessing, feature selection, and model interpretability, alongside recent advancements including spatial-temporal analysis and heterogeneous data integration. Through critical analysis of existing literature, it identifies trends, methodologies, and future research directions. Practical implications and applications across domains like urban planning, environmental monitoring, and epidemiology are explored. As a comprehensive resource, this review facilitates understanding and utilization of machine learning approaches for extracting insights from spatial data, benefiting researchers, practitioners, and policymakers alike. English Spatial Data Mining, Machine Learning, Geographic Information Systems, Classification, Clustering, Spatial-Temporal Analysis, Data Integration https://ijircst.org/abstract.php?article_id=1252