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Optimizing Geospatial Analytics: Processing Large Satellite Imagery Datasets using Spark on Dataproc and Visualizing in BigQuery GeoViz

Large Satellite Imagery Datasets

Large Satellite Imagery Datasets using Spark on Dataproc and Visualizing in BigQuery GeoViz

  • Use Case : Organizations working with geospatial data (e.g., agriculture, forestry, disaster management, urban planning) need to process large-scale satellite imagery to extract insights like vegetation health, land use patterns, and environmental monitoring. Traditional systems struggle with scalability, cost, and performance when handling petabyte-scale geospatial raster/vector datasets.

Objective

  • To use Apache Spark on Dataproc for distributed geospatial data processing.

    To store processed results in BigQuery for SQL-based analytics.

    To enable visual exploration of geospatial results using BigQuery GeoViz.

Project Description

  • Raw Data Ingestion :

    Satellite imagery datasets (e.g., Landsat, Sentinel, MODIS) are stored in Google Cloud Storage (GCS).

    GCS acts as the raw data lake.

Batch Data Processing

  • A Dataproc cluster (Apache Spark) is used to run geospatial libraries (e.g., GeoMesa, RasterFrames, GDAL) for preprocessing:

    Tiling, reprojection, and mosaicking imagery.

    Extracting vegetation indices (NDVI), land-use classification, and atmospheric corrections.

Data Transformation & Storage

  • Processed raster/vector outputs are exported to BigQuery tables (structured geospatial features).

    BigQuery’s geospatial functions (ST_GeogPoint, ST_Intersects, ST_Distance) allow querying spatial relationships.

Analytics & Visualization

  • Users query processed data in BigQuery with SQL + GIS extensions.

    Insights are visualized using BigQuery GeoViz or Looker Studio dashboards with maps.

Automation & Monitoring

  • Cloud Composer (Apache Airflow) orchestrates workflows.
  • Cloud Monitoring & Logging ensures pipeline reliability and cost control.
  • Google Cloud Services & Technologies :
    Category Google Cloud Services / Technologies
    Storage Google Cloud Storage (raw satellite imagery)
    Compute / Processing Dataproc (Apache Spark, GDAL, RasterFrames, GeoMesa)
    Data Warehouse BigQuery (geospatial SQL functions)
    Visualization BigQuery GeoViz, Looker Studio
    Orchestration Cloud Composer (Apache Airflow)
    Monitoring & Logging Cloud Monitoring, Cloud Logging
    Optional Enhancements AI/ML with Vertex AI for advanced classification (e.g., land cover detection)