latest modification update
Browse files- changelog.md +75 -70
changelog.md
CHANGED
|
@@ -1,70 +1,75 @@
|
|
| 1 |
-
# Changelog
|
| 2 |
-
|
| 3 |
-
All notable changes to the dataset will be documented in this file.
|
| 4 |
-
|
| 5 |
-
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
|
| 6 |
-
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
|
| 7 |
-
|
| 8 |
-
### `v1.1.
|
| 9 |
-
|
| 10 |
-
|
| 11 |
-
|
| 12 |
-
|
| 13 |
-
|
| 14 |
-
|
| 15 |
-
|
| 16 |
-
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
|
| 20 |
-
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
|
| 24 |
-
|
| 25 |
-
|
| 26 |
-
|
| 27 |
-
|
| 28 |
-
-
|
| 29 |
-
-
|
| 30 |
-
-
|
| 31 |
-
-
|
| 32 |
-
|
| 33 |
-
|
| 34 |
-
|
| 35 |
-
|
| 36 |
-
|
| 37 |
-
|
| 38 |
-
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
* `
|
| 42 |
-
*
|
| 43 |
-
* `
|
| 44 |
-
* `
|
| 45 |
-
* `
|
| 46 |
-
|
| 47 |
-
|
| 48 |
-
|
| 49 |
-
|
| 50 |
-
|
| 51 |
-
|
| 52 |
-
|
| 53 |
-
|
| 54 |
-
|
| 55 |
-
|
| 56 |
-
|
| 57 |
-
|
| 58 |
-
|
| 59 |
-
|
| 60 |
-
|
| 61 |
-
|
| 62 |
-
|
| 63 |
-
|
| 64 |
-
|
| 65 |
-
|
| 66 |
-
|
| 67 |
-
|
| 68 |
-
|
| 69 |
-
|
| 70 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Changelog
|
| 2 |
+
|
| 3 |
+
All notable changes to the dataset will be documented in this file.
|
| 4 |
+
|
| 5 |
+
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
|
| 6 |
+
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
|
| 7 |
+
|
| 8 |
+
### `v1.1.1` - 30.01.2025
|
| 9 |
+
|
| 10 |
+
In `AGBD.py`, line 399, `{"split": "val"}` was changed to `{"split": "validation"}` so as to match the split names of the `AGBD_raw` dataset. The README.md was updated accordingly.
|
| 11 |
+
|
| 12 |
+
|
| 13 |
+
### `v1.1.0` - 04.12.2024
|
| 14 |
+
|
| 15 |
+
Overall, the structure of the input data now looks like:
|
| 16 |
+
```
|
| 17 |
+
from datasets import load_dataset
|
| 18 |
+
|
| 19 |
+
dataset = load_dataset('AGBD.py',trust_remote_code=True,streaming=True)
|
| 20 |
+
for sample in dataset['train']:
|
| 21 |
+
_in = sample['input']
|
| 22 |
+
break
|
| 23 |
+
|
| 24 |
+
np.array(_in).shape # (24, 15, 15)
|
| 25 |
+
```
|
| 26 |
+
Where the shape follows the convention below:
|
| 27 |
+
```
|
| 28 |
+
- 12 x Sentinel-2 bands
|
| 29 |
+
- 3 x Sentinel-2 dates (s2_num_days, s2_doy_cos, s2_doy_sin)
|
| 30 |
+
- 4 x Latitude/longitude (lat_cos, lat_sin, lon_cos, lon_sin)
|
| 31 |
+
- 3 x GEDI dates (gedi_num_days, gedi_doy_cos, gedi_doy_sin)
|
| 32 |
+
- 2 x ALOS bands (HH, HV)
|
| 33 |
+
- 2 x CH bands (ch, std)
|
| 34 |
+
- (N + 1) x LC (lc_encoded, lc_prob), where N = 14 for onehot, N = 5 for cat2vec, and N = 2 for sin/cos
|
| 35 |
+
- 3 x Topographic bands (slope, aspect_cos, aspect_sin)
|
| 36 |
+
- 1 x DEM (dem)
|
| 37 |
+
```
|
| 38 |
+
|
| 39 |
+
#### Added
|
| 40 |
+
* New features:
|
| 41 |
+
* `slope` : the percentage of the slope where each pixel is located; it is a `float` between $0$ and $1$
|
| 42 |
+
* `aspect_cos`,` aspect_sin` : the sine and cosine encoded aspect, or orientation of the slope, which is measured clockwise in degrees from $0$ to $360$; it is a `float` between $0$ and $1$
|
| 43 |
+
* `s2_num_days` : the date of acquisition of the Sentinel-2 product, calculated as the number of days since the start of the GEDI mission (April 17th, 2019); it is an `int`
|
| 44 |
+
* `s2_doy_cos`, `s2_doy_sin` : the sine and cosine encoded corresponding day of the year (DOY); it is a `float` between $0$ and $1$
|
| 45 |
+
* `gedi_num_days` : the date of acquisition of the GEDI footprint, calculated as the number of days since the start of the GEDI mission (April 17th, 2019); it is a `uint`
|
| 46 |
+
* `gedi_doy_cos`, `gedi_doy_sin` : the sine and cosine encoded corresponding day of the year (DOY); it is a `float` between $0$ and $1$
|
| 47 |
+
* The `load_dataset()` function now provides the following configuration options:
|
| 48 |
+
* `norm_strat` (default = `'pct'`) : the strategy to apply to process the input features. Valid options are: `'pct'`, which applies min-max scaling with the $1$-st and $99$-th percentile of the data; and `'mean_std'` which applies mean/variance standardization`.
|
| 49 |
+
* `encode_strat` (default = `'onehot'`) : the encoding strategy to apply to the land classification (LC) data. Valid options are: `'onehot'`, one-hot encoding; `'sin_cos'`, sine-cosine encoding; `'cat2vec'`, cat2vec transformation based on embeddings pre-computed on the train set.
|
| 50 |
+
* `input_features` (dict) : the input features to be included in the data, the default values being:
|
| 51 |
+
```
|
| 52 |
+
{'S2_bands': ['B01', 'B02', 'B03', 'B04', 'B05', 'B06', 'B07', 'B08', 'B8A', 'B09','B11', 'B12'],
|
| 53 |
+
'S2_dates' : False, 'lat_lon': True, 'GEDI_dates': False, 'ALOS': True, 'CH': True, 'LC': True,
|
| 54 |
+
'DEM': True, 'topo': False}
|
| 55 |
+
```
|
| 56 |
+
* `additional_features` (list, default = `[]`) : the metadata to include in the data. Possible values are:
|
| 57 |
+
```
|
| 58 |
+
['s2_num_days', 'gedi_num_days', 'lat', 'lon', 'agbd_se', 'elev_lowes', 'leaf_off_f', 'pft_class', 'region_cla', 'rh98', 'sensitivity', 'solar_elev', 'urban_prop']
|
| 59 |
+
```
|
| 60 |
+
This metadata can later be accessed as such:
|
| 61 |
+
```
|
| 62 |
+
from datasets import load_dataset
|
| 63 |
+
|
| 64 |
+
dataset = load_dataset('AGBD.py',trust_remote_code=True,streaming=True)
|
| 65 |
+
for sample in dataset['train']:
|
| 66 |
+
lat = sample['lat']
|
| 67 |
+
break
|
| 68 |
+
```
|
| 69 |
+
|
| 70 |
+
#### Fixed
|
| 71 |
+
* Statistics: there was in bug in the computation of the percentiles, and the statistics were fixed accordingly.
|
| 72 |
+
* Latitude and longitude: while the latitude and longitude in the raw `.h5` files are absolutely correct, there was a bug in the generation of the `.parquet` files for HuggingFace, resulting in offsetted `lat` and `lon` in the additional features. We've now corrected this.
|
| 73 |
+
|
| 74 |
+
#### Removed
|
| 75 |
+
* The `load_dataset()` function does not provide the `normalize_data` configuration anymore, as it was replaced by the `norm_strat` configuration, giving users more flexibility regarding the processing of the input feature.
|