> ## Documentation Index > Fetch the complete documentation index at: https://docs.nikaplanet.com/llms.txt > Use this file to discover all available pages before exploring further. # Geospatial Analysis > Learn how to perform geospatial analysis with NikaWorkspace in 7 easy steps ## Geospatial Analysis Learn how to perform geospatial analysis with NikaWorkspace in 7 easy steps. This tutorial will guide you from creating your first notebook to publishing your analysis results. ## Step 1: Create Your First Notebook ### Quick Start 1. **Navigate to Notebooks**: Click on "Notebooks" in the left sidebar 2. **Click "+" Button**: Click the "+" button in the notebook list 3. **Select "Blank Notebook"**: Choose "Blank Notebook" from the dropdown menu 4. **Auto-Save Enabled**: Your notebook is automatically saved ### Rename Your Notebook * **Click Title Area**: Click on the notebook title at the top left * **Type New Name**: Enter a descriptive name like "Geospatial Analysis Project" * **Professional Naming**: Use clear, descriptive names for your projects Create Blank Notebook ## Step 2: Start Your Machine ### Select Machine Configuration Choose from available configurations: * **CPUx3**: 3 CPU cores, 24GB RAM, ready in under 30 seconds (recommended for beginners) * **CPUx7**: 7 CPU cores, 53GB RAM, ready in over 2 minutes * **GPU Machines**: For machine learning and complex processing ### Start Machine 1. **Click "Start Machine"**: Click the prominent white button 2. **Wait for Ready**: Machine will be ready in 15-40 seconds 3. **Monitor Status**: Hover over the green dot to check machine status Start Machine ## Step 3: Add Content Blocks ### Using the "+" Icon 1. **Find "+" Button**: Look for the "+" icon on the left of any row 2. **Click "+"**: Click to add a new block 3. **Select Block Type**: Choose from code, markdown, alerts, or media blocks ### Using Keyboard Shortcut * **Press "/"**: Type "/" in any empty row to trigger block selection * **Choose Block**: Select the desired block type from the menu ### Available Block Types * **Code Block**: For Python code execution * **Alert Block**: Highlight important information * **Headings**: Create section headers * **Media**: Insert images, videos, or file attachments Cool Blocks Available ## Step 4: Run Your Code ### Multiple Execution Methods 1. **Hover Menu**: Hover over code block and click the play button (▶️) 2. **Keyboard Shortcut**: Select block and press `Shift+Enter` 3. **Run All**: Use "Run All" button in top-right toolbar for sequential execution ### Streaming Execution * **Real-time Output**: Results stream in from the kernel * **Background Processing**: Long-running code continues even if you close the workspace * **Return Later**: Come back hours later to see completed results Run Button in Hover Menu ## Step 5: Use Pre-installed Geospatial Libraries ### GDAL and CUDA Ready All VM kernels come with: * **GDAL 3.9.1**: Geospatial Data Abstraction Library * **CUDA 12.2**: NVIDIA CUDA for GPU acceleration * **Python 3.10/3.11**: Multiple Python versions available ### Example Geospatial Code ```python theme={null} # Import geospatial libraries import rasterio import geopandas as gpd import numpy as np # Load raster data with rasterio.open('/workspace/data/satellite.tif') as src: data = src.read() print(f"Raster size: {src.width} x {src.height}") # Load vector data gdf = gpd.read_file('/workspace/data/shapefile.shp') print(f"Number of features: {len(gdf)}") # Perform analysis ndvi = (data[3] - data[2]) / (data[3] + data[2]) print(f"NDVI calculated successfully") ``` GDAL CUDA Pre-installed ## Step 6: Use AI-Powered Features ### Quick AI Edit * **Press `Cmd/Ctrl + K`**: Get AI suggestions for code improvements * **Green Suggestions**: AI suggestions appear in green text * **Preview Execution**: Test suggested changes before accepting * **Accept/Reject**: Choose which suggestions to keep ### Error Resolution with GAIA * **"Resolve in GAIA" Button**: Click when you encounter errors * **AI Analysis**: GAIA analyzes your entire notebook context * **Chat Interface**: Ask questions and get AI assistance * **Direct Modifications**: AI can modify your notebook directly Resolve in GAIA Button ## Step 7: Publish Your Analysis ### Prepare for Publishing 1. **Finalize Your Analysis**: Ensure all code blocks are executed 2. **Add Documentation**: Include markdown blocks explaining your work 3. **Test Functionality**: Verify all interactive features work ### Publish Your Notebook 1. **Right-click Notebook**: Right-click on your notebook in the list 2. **Select "Publish"**: Choose the publish option from the context menu 3. **Fill Required Fields**: Enter title\*, version\*, and category\* 4. **Generate Thumbnail**: Use AI generation if you don't have a thumbnail 5. **Set Visibility**: Choose Team Only or Public access 6. **Click Publish**: Finalize your publication ### View Published Notebook * **Click Arrow Icon**: Click the arrow icon in the publish dialog * **New Tab Opens**: Your published notebook opens in a new tab * **Static View**: Notebook is view-only for others * **Public Hub**: If public, appears in the NikaHub Publish Dialog with Required Fields ## Key Features Summary ### Easy to Use * **Auto-save**: Everything is automatically saved * **Streaming Execution**: Long-running tasks continue in background * **Multiple Execution Methods**: Hover, keyboard shortcuts, or run all * **Block Reordering**: Easy reordering with arrow buttons ### Powerful Analysis * **Pre-installed Libraries**: GDAL, CUDA, and Python ready to use * **Large Dataset Support**: Work with TB-PB sized geospatial data * **GPU Acceleration**: Use CUDA for faster processing * **Real-time Linting**: Code quality feedback as you type ### AI-Powered * **Quick AI Edit**: Get code suggestions with `Cmd/Ctrl + K` * **Error Resolution**: Use GAIA for intelligent error fixing * **Context-Aware**: AI understands your entire notebook * **Chat Interface**: Natural language interaction with AI ### Collaboration Ready * **Team Publishing**: Share with team members * **Public Hub**: Share with the broader community * **Version Control**: Maintain different versions of your work * **Easy Updates**: Modify and republish as needed ## Next Steps Now that you've completed the tutorial: 1. **Explore Libraries**: Check [Supported Python Libraries](/guides/data-analysis/supported-python-libraries) 2. **Advanced Features**: Learn about [AI Coding in Notebook](/guides/data-analysis/ai-coding-in-notebook) 3. **Machine Management**: Understand [Starting Your Machine](/guides/data-analysis/start-machine) 4. **Publishing**: Master [Publishing Your Notebook](/guides/data-analysis/publish-notebook) Happy geospatial analyzing!