Spatial Data Science

  1. Spatial Machine Learning
    1. Feature Engineering for Spatial Data
      1. Geometric Features
        1. Area Calculations
          1. Perimeter Calculations
            1. Shape Indices
              1. Compactness Measures
              2. Spatial Relationship Features
                1. Distance Features
                  1. Proximity Features
                    1. Neighborhood Features
                      1. Connectivity Features
                      2. Contextual Features
                        1. Land Use Context
                          1. Demographic Context
                            1. Environmental Context
                            2. Raster-derived Features
                              1. Pixel Value Extraction
                                1. Texture Measures
                                  1. Spectral Indices
                                    1. Zonal Statistics
                                  2. Unsupervised Spatial Learning
                                    1. Spatial Clustering Algorithms
                                      1. Partitional Clustering
                                        1. Spatially Constrained K-means
                                          1. K-medoids with Spatial Constraints
                                          2. Hierarchical Clustering
                                            1. Agglomerative Clustering
                                              1. Ward's Method with Spatial Constraints
                                              2. Density-based Clustering
                                                1. DBSCAN
                                                  1. OPTICS
                                                    1. HDBSCAN
                                                    2. Region-based Clustering
                                                      1. SKATER
                                                        1. REDCAP
                                                          1. Max-p Regions
                                                        2. Dimensionality Reduction
                                                          1. Principal Component Analysis
                                                            1. Multidimensional Scaling
                                                              1. Spatial Principal Components
                                                            2. Supervised Spatial Learning
                                                              1. Spatial Cross-Validation
                                                                1. Spatial Blocking
                                                                  1. Leave-One-Region-Out
                                                                    1. Buffered Cross-Validation
                                                                      1. Spatial Clustering for CV
                                                                      2. Classification Methods
                                                                        1. Decision Trees
                                                                          1. Random Forest
                                                                            1. Support Vector Machines
                                                                              1. Gradient Boosting
                                                                                1. Neural Networks
                                                                                2. Regression Methods
                                                                                  1. Linear Regression with Spatial Features
                                                                                    1. Tree-based Regression
                                                                                      1. Ensemble Methods
                                                                                      2. Deep Learning for Spatial Data
                                                                                        1. Convolutional Neural Networks
                                                                                          1. Image Classification
                                                                                            1. Semantic Segmentation
                                                                                              1. Object Detection
                                                                                              2. Graph Neural Networks
                                                                                                1. Node Classification
                                                                                                  1. Graph Classification
                                                                                                2. Model Evaluation and Validation
                                                                                                  1. Spatial Accuracy Assessment
                                                                                                    1. Confusion Matrix Analysis
                                                                                                      1. ROC Curve Analysis
                                                                                                        1. Spatial Error Patterns

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                                                                                                    6. Spatial Statistics and Modeling

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                                                                                                    8. Advanced Spatial Analysis Topics