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DISFOR
DISFOR offers dense labelled satellite time-series data on forest disturbance timing and agents of disturbance. It contains 3823 unique time-series. Each time-series corresponds to a single 10x10m Sentinel-2 pixel.
Usage
A Python package is available at https://github.com/JR-DIGITAL/DISFOR. It offers utilities to load and filter the available data. See the github page for installation instructions. There are also usage guides available in the documentation at: https://jr-digital.github.io/DISFOR/usage/dataset-overview/
Dataset Overview
There are four main parts of this dataset:
samples.parquet: Providing location and metadata of sampled pointslabels.parquet: Providing labels for each sampled time-seriespixel_data.parquet: Providing Sentinel-2 band data for each acquistion in the time-series- Sentinel-2 Chips: Image chip time-series for each sample
samples.parquet
This contains the sampled points along with metadata on the points. It provides the following columns:
| Column name | Description |
|---|---|
| sample_id | Unique sample ID for each sample point |
| original_sample_id | Sample ID of the point in the original publication of the dataset |
| interpreter | Shorthand code for the interpreter who labelled this sample |
| dataset | Number of the original sampling campaign in which this point was labelled |
| source | The ancillary data source used to interpret the agent |
| source_description | A long text description of the used source. Link to the original data if available |
| s2_tile | If available, which Sentinel 2 Tile the sample intersects |
| cluster_id | Unique ID to group samples which are spatio-temporally autocorrelated |
| cluster_description | What type of cluster it is |
| comment | Free text comment about the interpretation of the sampled point |
| confidence | Confidence of sampling: high where both timing and agent are confident, medium were only the timing is confident |
| geometry | Coordinates of the sampled point. In CRS EPSG:4326 |
labels.parquet
This contains the time-series labels for each sampled point in samples.parquet. The following columns are available:
| Column name | Description |
|---|---|
| sample_id | Taken from sample table |
| original_sample_id | Taken from sample table |
| dataset | Taken from sample table |
| label | Interpreted class of the segment (see next table) |
| original_label | The label which was originally assigned and remapped to label |
| start | Start date of the segment |
| end | End date of the segment |
| start_next_label | Start date of the next label. Some labels are encoded as events (Clear Cuts for example) and are not immediately followed by another label, this column allows a full segmentation of the time-series. Null if it is the last label of the sample |
The provided label is a hierarchical label, following this hierarchy:
| Level 1 | Level 2 | Level 3 |
|---|---|---|
| 100 - Healthy Vegetation | 110 - Undisturbed Forest | |
| 120 - Revegetation | 121 - With Trees (after clear cut) | |
| 122 - Canopy closing (after thinning/defoliation) | ||
| 123 - Without Trees (shrubs and grasses, no reforestation visible) | ||
| 200 - Disturbed | 210 - Planned | 211 - Clear Cut |
| 212 - Thinning | ||
| 213 - Forestry Mulching (Non Forest Vegetation Removal) | ||
| 220 - Salvage | 221 - After Biotic Disturbances | |
| 222 - After Abiotic Disturbances | ||
| 230 - Biotic | 231 - Bark Beetle | |
| 232 - Gypsy Moth (temporal segment of visible disturbance) | ||
| 240 - Abiotic | 241 - Drought | |
| 242 - Wildfire | ||
| 243 - Wind | ||
| 244 - Avalanche | ||
| 245 - Flood |
This mapping from label numbers to text is also available in classes.json.
pixel_data.parquet
This dataset provides the Sentinel-2 time-series of spectral values from which the labels were interpreted. The following columns are available:
| Column name | Datatype | Description |
|---|---|---|
| sample_id | UINT16 | Taken from sample table |
| timestamp | DATE | UTC date of the S2 acquisition |
| label | UINT16 | Interpreted class of the segment, see previous table |
| clear | BOOL | True if the pixel is clear (SCL value any of 2,4,5,6) |
| percent_clear_4x4 [8x8, 16x16, 32x32] | UINT8 | The percentage of clear pixels (SCL in 2,4,5,6) within a 4x4, 8x8, 16x16 or 32x32 pixel image chip |
| B02, B03, B04, B05, B06, B07, B08, B8A, B11, B12 | UINT16 | DN value for the spectral band |
| SCL | UINT8 | Sentinel 2 Scene Classification Value |
Sentinel-2 Chips
The files disfor-<start-id>-<end-id>.tar.zst provide tarballs with Sentinel-2 chips for each sample. The chips are of size 32x32px,
the sampled point is always at [16,16]. The available bands are: B02, B03, B04, B05, B06, B07, B08, B8A, B11, B12.
Sentinel-2 bands with a native resolution of 20m (B11, B12) were resampled to 10m using nearest neighbor resampling.
The file structure in each tarball is:
tiffs/<sample_id>/YYYY-MM-DD.tif
Train Test Split
There is a train test split available which was constructed to reduce spatial autocorrelation and information leakage between the sets. Two JSONs with lists of sample_ids are available in
train_ids.jsonval_ids.json
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