links-ads/insar-regional-snow-mapping

InSAR Regional Snow Mapping Dataset

The dataset pairs Sentinel-1 InSAR stacks with IT-SNOW snow products and ERA5-derived weather variables over the Italian Alps, for the purpose of pixel-wise regression of Snow Depth (HS) and Snow Water Equivalent (SWE).

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Dataset overview

Property	Value
Area	Italian Alps (Trentino region)
Bounding box	9.80°E – 10.87°E, 45.93°N – 46.40°N
CRS	EPSG:4326 (WGS84)
Raster size	93 × 211 pixels
Spatial resolution	~500 m (≈ 0.005°)
Time windows	64 (12-day Sentinel-1 repeat cycle)
Date range	January 2021 – March 2023
InSAR bands per window	7
Weather bands per window	2
Targets	HS (snow depth, cm) · SWE (snow water equivalent)

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Archive structure

The dataset is distributed as a single archive, data.tar.gz:

Dataset_icip2026/
├── INSAR/                   # 64 × 7 = 448 GeoTIFF files  (+ filtered raw intensity)
│   ├── YYYY-MM-DD_YYYY-MM-DD_coh_IW1_VV_*.tif
│   ├── YYYY-MM-DD_YYYY-MM-DD_displacement_VV.tif
│   ├── YYYY-MM-DD_YYYY-MM-DD_elevation_VV.tif
│   ├── YYYY-MM-DD_YYYY-MM-DD_Intensity_ifg_IW1_VV_*_db.tif
│   ├── YYYY-MM-DD_YYYY-MM-DD_localIncidenceAngle.tif
│   ├── YYYY-MM-DD_YYYY-MM-DD_Phase_ifg_IW1_VV_*.tif
│   └── YYYY-MM-DD_YYYY-MM-DD_Unw_Phase_ifg_*_VV.tif
├── ITSNOW/                  # IT-SNOW snow products
│   ├── HS/                  # 64 GeoTIFFs  –  YYYY-MM-DD_to_YYYY-MM-DD_hs.tif
│   └── SWE/                 # 64 GeoTIFFs  –  YYYY-MM-DD_to_YYYY-MM-DD_swe.tif
├── S3/                      # Weather rasters
│   ├── YYYY-MM-DD_YYYY-MM-DD_meanTemp.tif   (mean air temperature, °C)
│   └── YYYY-MM-DD_YYYY-MM-DD_pdd.tif        (positive degree days)
└── master_mask.tif          # Binary valid-area mask  (1 = valid, 0 = excluded)

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Data fields

INSAR/

Seven Sentinel-1 IW-mode, VV-polarisation interferometric products, one raster per band per 12-day window. All rasters are float32, co-registered to the same 93×211 WGS84 grid. Values outside the valid area and known no-data sentinels (≤ −9000, 0) are NaN.

Band	Description
coh_IW1_VV	Interferometric coherence (0–1)
displacement_VV	Line-of-sight surface displacement (m)
elevation_VV	Digital elevation model co-registered to SAR geometry (m)
Intensity_ifg_IW1_VV_*_db	Interferometric intensity in decibels (dB)
localIncidenceAngle	Local incidence angle (degrees)
Phase_ifg_IW1_VV	Wrapped interferometric phase (rad, −π to π)
Unw_Phase_ifg_*_VV	Unwrapped interferometric phase (rad)

The raw linear-scale intensity file (Intensity_ifg_IW1_VV_*.tif, without _db) is included in the archive but is excluded from training by the data-loading code.

ITSNOW/

Interpolated IT-SNOW products resampled to the same 93×211 grid.

Variable	Unit	Description
HS	cm	Snow depth
SWE	cm	Snow water equivalent

S3/

ERA5-derived weather aggregates over each 12-day InSAR window, resampled to the same grid.

Variable	Description
meanTemp	Mean air temperature over the window (°C)
pdd	Positive degree days accumulated over the window

master_mask.tif

uint8 raster (93×211). Pixel value 1 = within the study area; 0 = excluded (glacier boundaries, cloud shadow, or no-data regions). Normalization statistics and evaluation metrics are computed only over masked pixels.

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Splits

The 64 time windows are sorted chronologically and split as follows (fixed, not randomised):

Split	Windows	Notes
Train + validation	57	Rolling 5-train / 1-val pattern
Test	7 (last)	2022-12-30 → 2023-03-24

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Usage

Download and extract:

mkdir -p data
wget -O data/Dataset_icip2026.tar.gz \
  https://huggingface.co/datasets/links-ads/insar-regional-snow-mapping/resolve/main/Dataset_icip2026.tar.gz
tar -xzf data/Dataset_icip2026.tar.gz -C data/

Load a single sample with the accompanying code repository:

from pathlib import Path
from rsm.io import match_insar_to_targets, stack_insar_bands, stack_weather_bands, load_mask

root = Path("data/Dataset_icip2026")
samples = match_insar_to_targets(
    root / "INSAR", root / "ITSNOW", root / "S3"
)
mask = load_mask(root / "master_mask.tif")

sample = samples[0]
print(sample["key"])          # e.g. '2021-01-09_to_2021-01-21'

insar, _  = stack_insar_bands(sample["band_files"])    # (93, 211, 7)
weather, _ = stack_weather_bands(sample["weather_files"])  # (93, 211, 2)

See the code repository for full training and evaluation scripts.

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Source data

Source	Description
Copernicus Sentinel-1	C-band SAR, IW mode, VV polarisation; processed with SNAP and SNAPHU
IT-SNOW	National daily snow depth and SWE product for Italy (ISPRA)
ERA5	ECMWF reanalysis used to derive mean temperature and positive degree days

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License

This dataset is released under the MIT License. Sentinel-1 data © ESA / Copernicus Programme. IT-SNOW data © ISPRA. ERA5 data © ECMWF (Copernicus Climate Change Service).