# ESA EO4SoilProtection 2024: Predicting Erosion Cat — Data

来源：https://www.kaggle.com/competitions/esa-eo4soilprotection-2024-predicting-erosion-cat/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

##Training Dataset (train_erosion.csv):
This dataset includes training points for model development. Use this dataset to train your models, understanding the distinct features and indicators of each erosion category. There are four erosion categories:
- 0 = No Gully/badland
- 1 = Gully
- 2 = Badland
- 3 = Landslides

##Validation Dataset (test_erosion.csv)
The dataset contains both public and private test points. Public points are available for internal validation of your models. It will help you fine-tune and assess the accuracy of your predictions during the development phase. Private dataset represents the final test of your model's effectiveness in real-world scenarios. Your goal is to predict these hidden values accurately. 

## Columns
Explanation of columns (variables) in the training dataset can be found [here](https://docs.google.com/document/d/1IbzrJuyOBRFNTzXzcvw_y0O25fVfj2osJFs1TukHflw/edit?usp=sharing).

##Important columns are:
* `sample_id`: unique ID
* `Coor_X`, `Coor_Y`: easting and northing in EPSG 3035
* `observation_year`: observation year
* ` UUID`: Universally Unique Identifier (https://en.wikipedia.org/wiki/Universally_unique_identifier) this allows you to point to exact sample / unique row