I will classify land cover using satellite imagery and machine learning

Czech Republic

I speak English, German
I am a remote sensing and GIS specialist focused on end-to-end geospatial automation. I build workflows for satellite image processing, NDVI monitoring, land cover analysis, change detection, and rast...
About this Gig

I will create land cover classification maps using satellite imagery and geospatial analysis. This service is useful for agriculture, forestry, environmental monitoring, urban planning, research, and land management projects.

I can classify your area into land cover classes such as vegetation, forest, agriculture, water, bare soil, built-up area, rangeland, wetlands, or custom classes based on your project needs. I can work with Sentinel-2, Landsat, GeoTIFFs, existing raster data, training samples, or reference maps.

Depending on the package, I can provide a basic land cover map, class-wise area statistics, GIS-ready output files, accuracy assessment if validation data is available, and a short interpretation report.

Deliverables can include PNG maps, GeoTIFF, shapefile, GeoPackage, CSV statistics, and PDF summary. Please provide your AOI boundary, required classes, target year or season, and any training/reference data if available.

Expertise:

Image processing

Classification

Clustering

Programming language:

Python

Frameworks:

Scikit-learn

Keras

Panda

Tools:

Jupyter Notebook

MLflow

Colab

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