AI, GIS e Telerilevamento | Soluzioni Geospaziali

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AI, GIS and Remote Sensing | Intelligent Geospatial Solutions

Artificial Intelligence applied to territorial analysis. Automation, satellite image classification and vegetation index calculation for agriculture and the environment.

The future of spatial analysis brings together Geographic Information Systems (GIS), Artificial Intelligence (AI) and Remote Sensing. I develop advanced Python solutions for the classification of satellite (Sentinel, Landsat) and drone imagery, the automatic calculation of indices such as NDVI and SAVI, and in-depth raster analysis. I provide automated decision-support tools (GeoAI) for precision agriculture, forest monitoring and urban planning.

What I can do with AI and Remote Sensing

Satellite Image Analysis

Acquisition and processing of multispectral imagery to monitor territorial changes over time (Change Detection).

Vegetation Indices (NDVI/SAVI)

Calculation of NDVI, SAVI and NDWI maps to assess vegetation health and water stress, supporting precision agriculture.

AI-Based Classification

Use of Machine Learning algorithms (Random Forest, SVM, Neural Networks) to automatically classify land use from raster imagery.

Python Raster Automation

Development of Python scripts (GDAL, Rasterio, xarray) to massively process gigabytes of raster data, cutting days of work down to just minutes.

Decision Support

Creation of dashboards and predictive maps based on AI models to help organizations and businesses make data-driven decisions.

Drone Data Integration

Fusion of high-precision digital models (DSM/DTM) acquired from UAS/drones with multispectral analysis for micro-scale surveys.

Frequently Asked Questions

Can AI and remote sensing be used for territorial analysis?
Absolutely. This discipline, known as GeoAI, makes it possible to train algorithms to automatically recognize asbestos roofing, illegal landfills, changes in forest cover or crop types by analyzing satellite imagery, surpassing human visual analysis in both speed and scalability.
What is NDVI and what is it used for?
NDVI (Normalized Difference Vegetation Index) is an indicator calculated from multispectral bands (red and near-infrared) that detects vegetation vigor. It helps farmers and agronomists detect water stress or crop diseases early, enabling targeted interventions (precision agriculture).
What tools do you use to automate raster analysis?
I mainly use Python with the most advanced open source libraries (GDAL, Rasterio, NumPy, scikit-learn, PyTorch). These scripts can run either locally or on cloud servers to process enormous volumes of data (Big Earth Data).

Bring your territorial analysis into the future

Discover how artificial intelligence and satellite imagery can give your business crucial insights.

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