Overview | What the module does | The 3 × 3 scoring framework | Installation of optional dependencies | Step 1 — Run run_builtin_analysis() | Step 2 — Download the CAFO data | Step 3 — Score hub sites | Default usage | Compute a single score | With CDL raster (optional) | Step 4 — Inspect results | Step 5 — Map results | Step 6 — Export results | Multi-year analysis | Varying the catchment radius | Understanding the scoring dimensions | Performance notes | See also

Complete Documentation: analyze_crop_vegetation() Output Structure | Overview | Output Structure | 1. vegetation_indices (SpatRaster) | 2. analysis_results (List) | 2.1 stress_analysis (if analysis_type includes "stress" or "comprehensive") | 2.2 growth_analysis (if analysis_type includes "growth" or "comprehensive") | Index-specific statistics (for NDVI, EVI, GNDVI, DVI): | Growth stage prediction (overall): | 2.3 yield_analysis (if analysis_type includes "yield" or "comprehensive") | 2.4 summary_statistics | 2.5 validation (if reference_data provided) | 3. metadata (List) | Complete Example Workflow | Tips for Using Results | 1. Identifying Problem Areas | 2. Comparing Multiple Fields | 3. Time Series Analysis | Classification Methodology and References | Stress Detection | Growth Stage Classification | Yield Potential (Composite Index) | References | Validation Notes | Acknowledgments

What is manureshed? | View cheatsheet | Quick Start - Complete Analysis | Step-by-Step Analysis | 1. Check Available Data | 2. Basic Agricultural Analysis | 3. Add WWTP Data | Understanding the Results | Classifications | Accessing Results | Creating Maps | Classification Maps | WWTP Maps | Working with Different Years | Single Years | Multiple Years | Using Custom WWTP Data | State-Specific Analysis | Loading Individual Datasets | Tips for Success | Memory Management | Quality Checks | Next Steps | Getting Help

Overview | Basic Usage | Simple Comparison: Agricultural vs. WWTP | Understanding the Results | 1. Comparison Data | 2. Summary Statistics | 3. Visualization Plots | Advanced Examples | Multiple Scenarios | Year-over-Year Comparison | Scale Comparison | Saving Results | Save Plots | Save Data | Auto-save During Comparison | Interpreting Results | Understanding Deltas | Key Metrics to Watch | Use Cases | Management Analysis | Sensitivity Analysis | Regional Comparison | Tips and Best Practices | 1. Keep Comparisons Meaningful | 2. Name Scenarios Clearly | 3. Document Your Analysis | 4. Consider Statistical Significance | Troubleshooting | Different Scales | Missing Data | Related Functions | See Also

Overview | Installation Requirements | Launching the Dashboard | Dashboard Interface | Main Components | Sidebar Controls | Analysis Parameters | Action Buttons | Using the Map Tab | Interactive Map Features | Map Navigation Tips | Using the Statistics Tab | Value Boxes | Classification Distribution | Surplus/Deficit Distribution | Summary Statistics | Using the Data Table Tab | Interactive Table Features | Useful Filters | Help Tab | Workflow Examples | Example 1: Basic State Analysis | Example 2: Compare Agricultural vs. Integrated | Example 3: Year-over-Year Exploration | Example 4: Threshold Sensitivity | Example 5: Create Presentation Materials | Downloading Results | Data Download | Using Downloaded Data | Performance Tips | For Faster Analysis | Browser Performance | Troubleshooting | Dashboard Won't Launch | Analysis Fails | Map Not Displaying | Value Boxes Show Zero | Comparison with Programmatic Interface | When to Use Dashboard | When to Use R Code | Hybrid Approach | Sharing Results | For Colleagues Without R | For R Users | For Presentations | Accessibility Features | Privacy and Security | Advanced: Deploying for Teams | Option 1: Shinyapps.io | Option 2: RStudio Connect | Option 3: Shiny Server | Getting Help | Related Vignettes | Summary

Overview | Benchmark Setup | Comparative Approaches | Method 1: geospatialsuite::quick_map() | Method 2: Base terra::plot() | Method 3: ggplot2 with geom_raster | Performance Benchmarks | Memory Usage Comparison | Timing Comparison | Benchmark Results | Memory Efficiency Table | Plotting Time Comparison | XLarge Dataset Handling (10K×10K, ~762.9 MB) | Key Performance Characteristics | 1. Memory Efficiency | 2. Performance at Scale | 2. Robust Error Handling | 3. Consistency Across Data Sizes | Comparison with Related Packages | Similar Functionality in R Ecosystem | Key Performance Differences | Unique Advantages of quick_map() | Performance Summary Table | Reproducibility Notes | Conclusion | Note on Memory Profiling | References

Overview | Custom Thresholds | Understanding Thresholds | Automatic Threshold Calculation | State-Specific Analysis | Single State Analysis | Multi-State Comparison | Batch Processing | Multiple Years | Parallel Processing | Enhanced Batch Analysis | Performance Optimization | Benchmarking | Memory Management | Advanced Spatial Analysis | Transition Probabilities | Spatial Statistics | Custom Analysis Workflows | Research-Specific Analysis | Time Series Analysis | Data Export and Integration | Export for Other Software | Integration with Other Packages | Quality Control | Advanced Validation | Tips for Advanced Users | Performance Tips | Reproducibility

Overview | Quick Maps with quick_analysis() | Step-by-Step Map Creation | 1. Get Analysis Results First | 2. Agricultural Classification Maps | 3. Combined Maps (Agricultural + WWTP) | 4. WWTP Facility Maps | 5. WWTP Influence Maps | Comparison Plots | Before/After WWTP Integration | Network Plots | Spatial Transition Networks | Customizing Maps | Save Options | Custom Colors | Working with Different Scales | County Level | HUC8 Watersheds | HUC2 Regions | State-Specific Maps | Multi-Panel Figures | Tips for Good Maps | Map Quality | Color Choices | File Management | Troubleshooting | Common Issues

Overview | Standard vs. Custom Efficiency Factors | Basic Sensitivity Analysis | Load Required Data | Compare Different Nitrogen Efficiencies | Visualize Sensitivity Results | Phosphorus Sensitivity Analysis | Combined Sensitivity Analysis | Mapping Results Across Scenarios | Interpreting Results | Recommended Practice | Example: Complete Sensitivity Workflow | Summary | References

Overview | Using Custom WWTP Data | For Years Outside 2007-2016 | Advanced Custom Data Integration | Adding Other Nutrient Sources | Working with Different Time Periods | Custom Agricultural Data | Data Validation and Quality Control | Exporting Results | Troubleshooting Common Issues | WWTP Data Issues | Agricultural Data Issues | Getting Help | Common Questions | Function Help | Getting More Help | Handling Different Data Formats | Standard EPA Format | Different Units | Different File Format | Custom Column Names | Manual WWTP Processing | Unit Conversions | Common Conversions | Handling P2O5 vs P | Working with Different Spatial Scales | County Data (FIPS Codes) | HUC8 Watersheds | HUC2 Regions | State-Specific Analysis | Single State | Multiple States | Quality Control | Validate Your Data | Common Data Issues | Working with Multiple Years | Time Series Analysis | Data Management Tips | File Organization | Memory Management | Example: Complete Custom Workflow | Integration Issues | Best Practices for Custom Data | Data Documentation | Quality Assurance Workflow | Reporting Issues

Enhanced NDVI Analysis for Agriculture | Time Series NDVI Monitoring | Multi-Index Crop Assessment | Yield Prediction Support | Yield Potential Assessment | Crop Performance Metrics | Precision Agriculture Applications | Field-Level Analysis | Variable Rate Application Support | Crop Health Monitoring | Disease and Stress Detection | Early Warning Systems | Seasonal Crop Monitoring | Multi-Temporal Analysis | Harvest Timing Optimization | Water Management for Agriculture | Irrigation Needs Assessment | Crop Rotation Analysis | Multi-Year Crop Tracking | Sustainable Agriculture Metrics | Integration with Farm Management | Data Export for Farm Software | Economic Analysis Support | Quality Assurance and Validation | Data Quality Checks | Field Validation Support | Advanced Agricultural Workflows | Complete Farm Analysis Pipeline | Summary and Best Practices | Key Agricultural Functions | Best Practices for Agricultural Applications | Integration with Precision Agriculture | Understanding analyze_crop_vegetation() Outputs | Output Structure Overview | Interpreting Stress Analysis | Understanding Composite Yield Index | Growth Stage Predictions | Summary | CDL Analysis Capabilities: | Precision Agriculture Tools: | Integrated Workflows: | Key Advantages: | Applications: | Acknowledgments

Introduction | Learning Objectives | Prerequisites | Comprehensive Workflow Architecture | NDVI Crop Analysis Workflow | Basic Enhanced NDVI Workflow | Enhanced NDVI with Crop Masking | Comprehensive Vegetation Analysis Workflow | Multi-Index Vegetation Assessment | Crop-Specific Analysis Workflow | Water Quality Assessment Workflow | Comprehensive Water Quality Pipeline | Case Study 2: Environmental Monitoring and Water Quality Assessment | Step 1: Environmental Monitoring Setup | Step 2: Comprehensive Water Quality Analysis | Step 3: Land Use Impact Assessment | Step 4: Watershed-Scale Assessment | Step 5: Conservation Priority Mapping | Case Study 3: Temporal Change Detection and Monitoring | Step 1: Multi-Temporal Data Preparation | Step 2: Comprehensive Temporal Analysis | Step 3: Change Hotspot Identification | Step 4: Integrated Multi-Case Study Synthesis | Advanced Workflow Tips and Best Practices | 1. Workflow Optimization | 2. Reproducible Research Framework | Summary | Complete Case Studies: | Key Workflow Components: | Best Practices Demonstrated: | Real-World Applications: | Scalability: | Acknowledgments

Introduction | Key Features | Installation | Quick Start with Built-in Sample Data | Core Workflows | 1. Calculate Vegetation Indices | 2. Working with Multi-band Data | 3. Spatial Operations | 4. Data Visualization | Available Sample Datasets | Working with Your Own Data | Loading Raster Files with geospatialsuite | Single GeoTIFF File | Multiple GeoTIFF Files | Load from Directory | Real-World Landsat Workflow | Working with Vector Data | Loading Shapefiles | Working with GeoPackages | Multi-band Raster with Auto-Detection | Complete Real-World Example | Listing Available Indices | Getting Help | Summary

Introduction | Learning Objectives | Prerequisites | Universal Spatial Join Overview | Basic Spatial Joins | Vector to Raster Extraction (Most Common) | Extraction with Buffer | Zonal Statistics | Raster to Vector Analysis | Multiple Summary Functions | Raster Operations | Raster Resampling and Alignment | Scale Factor Operations | Vector to Vector Operations | Spatial Overlay | Nearest Neighbor Analysis | Advanced Integration Techniques | Multi-Dataset Integration | Terrain Analysis Integration | Coordinate Reference System Handling | Automatic CRS Management | Manual CRS Specification | Handling Missing Data | NA Strategy Options | Advanced Spatial Operations | Multi-Scale Analysis | Spatial Interpolation Integration | Working with Large Datasets | Chunked Processing | Memory-Efficient Raster Operations | Real-World Integration Examples | Agricultural Field Analysis | Watershed Analysis | Error Handling and Troubleshooting | Common Issues and Solutions | Performance Monitoring | Integration with Other Package Functions | Combining with Vegetation Analysis | Integration with Water Quality | Specialized Integration Functions | Multi-Scale Operations | Raster Mathematical Operations | Visualization of Integration Results | Mapping Integrated Data | Comparison Visualizations | Best Practices | Data Preparation | Method Selection Guidelines | Performance Optimization | Summary | Key Functions Used | Acknowledgments

Loading the Package | Quick Start: One-Line Mapping | Universal Spatial Map Function | Basic Point Mapping | Custom Color Schemes | Raster Mapping | Fast Raster Plotting | RGB Composite Mapping | Interactive Mapping | Regional Boundary Integration | Auto-Detection with Region Boundaries | Comparison Maps | Advanced Customization | Custom Color Palettes | Map Styling Options | Publication-Quality Maps | High-Resolution Output | Map Layout and Legends | Error Handling and Troubleshooting | Common Issues and Solutions | Diagnostic Functions | Best Practices | 1. Data Preparation | 2. Progressive Enhancement | 3. Performance Optimization | Integration with Other Packages | ggplot2 Integration | Leaflet Integration | Specialized Mapping Functions | NDVI Mapping | Water Quality Mapping | Export Options | Static Map Export | Interactive Map Export | Advanced Features | Multi-Layer Visualization | Automatic Map Type Detection | Performance Tips | For Large Datasets | Memory Management | Troubleshooting Common Issues | CRS Mismatches | Data Format Issues | Summary | Key Functions Summary | Acknowledgments

Introduction | Loading Required Packages | Quick Start with Sample Data | Understanding Vegetation Indices | Common Vegetation Indices | NDVI (Normalized Difference Vegetation Index) | EVI (Enhanced Vegetation Index) | SAVI (Soil Adjusted Vegetation Index) | Calculate Multiple Indices | Working with Multi-band Rasters | Working with Satellite Imagery | Loading and Processing Landsat Data | Processing Sentinel-2 Imagery | Multi-Temporal Analysis | Specialized Vegetation Indices | Chlorophyll Content Indices | Water Content Indices | Advanced Analysis | Zonal Statistics | Field-Level Analysis | Working with Real Field Data | List Available Indices | Best Practices | Index Selection Guidelines | Data Quality Considerations | Summary

Introduction | Learning Objectives | Prerequisites | Water Detection Indices | Basic Water Index Calculation | Available Water Indices | Multiple Water Index Calculation | Water Body Analysis | Comprehensive Water Body Characterization | Field Water Quality Data Analysis | Loading and Processing Water Quality Data | Multi-Parameter Analysis | Visualization | Water Index Visualization | Comparison Maps | Threshold Analysis | Water Quality Classification | Water Body Detection Thresholds | Temporal Analysis | Time Series Water Quality Monitoring | Real-World Applications | Lake Water Quality Assessment | Stream Network Integration | Error Handling and Troubleshooting | Common Issues and Solutions | Data Quality Checks | Integration with Other Package Functions | Combining Water Indices with Vegetation Analysis | Spatial Integration with Field Data | Best Practices | Index Selection Guidelines | Threshold Recommendations | Quality Control | Summary | Key Functions Used | Acknowledgments

What is FAIRmaterials and what does it do? | How to use FAIR CSV template: | Example of XRay ontology FAIR CSV sheet | Install and load the package | Running the default 'process_ontology_files' function: | PV ontology sheets: | turtle/owl output from PV Module in R: | json-ld output from PV Module in R: | HTML output | turtle/owl output from PV Module: | json-ld output from PV Module: | XRay Sample ontology sheets: | turtle/owl output from XRay Sample in R: | json-ld output from XRay Sample in R: | Removing values from visualization in R | Removing values from visualization in Python | Attempting to add external ontology information in R: | For PV Module: | For XRay Sample: | turtle/owl output from XRay Sample: | Attempting to add external ontology information in Python: | Merging two ontologies and specifying some of the metadata: | Example turtle/owl output from merged ontology: | Acknowledgment: