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ESA-PhiLab-Edge/PhilEOBench-land_cover_classification

Simulated PhiSat Bench Dataset - Landcover This repository contains a simulated PhiSat2 dataset derived from Sentinel-2 data for landcover classification, with a spatial resolution of 10 meters per pixel. Landcover Labels The landcover labels in this dataset follow a classification scheme defined by the WorldCover PUM V1.1 guidelines. Each pixel is labeled with the dominant landcover class. The key classes include: Code Class Name Description 10 Tree… See the full description on the dataset page: https://huggingface.co/datasets/ESA-PhiLab-Edge/PhilEOBench-land_cover_classification.

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Simulated PhiSat Bench Dataset - Landcover

This repository contains a simulated PhiSat2 dataset derived from Sentinel-2 data for landcover classification, with a spatial resolution of 10 meters per pixel.

Landcover Labels

The landcover labels in this dataset follow a classification scheme defined by the WorldCover PUM V1.1 guidelines. Each pixel is labeled with the dominant landcover class. The key classes include:

CodeClass NameDescription
10Tree CoverAreas with ≥10% tree cover (includes plantations, flooded forests, excluding mangroves).
20ShrublandDominated by natural shrubs, typically <5 m tall.
30GrasslandHerbaceous vegetation like grasslands, steppes, prairies, and pastures.
40CroplandAnnual crops harvested within 12 months; greenhouses are classified as built-up.
50Built-upBuilt environments, including buildings, roads, and other artificial infrastructure.
60Bare/Sparse VegetationAreas with exposed soil, sand, or rocks; usually with <10% vegetative cover year-round.
70Snow and IceRegions that are persistently covered by snow or ice.
80Permanent Water BodiesWater bodies present for at least 9 months per year (can be fresh or salt water).
90Herbaceous WetlandAreas dominated by herbaceous plants that are permanently or seasonally flooded.
95MangrovesIntertidal zones with salt-tolerant tree vegetation.
100Moss and LichenRegions covered by lichens or mosses (often found in tundra or alpine zones).

Use Case

This dataset is intended for landcover classification tasks, including applications in urban planning, environmental monitoring, and resource management.