Datasets:
field_id
string | date
string | NDVI
float64 | EVI
float64 | TCG
float64 | valid
float64 | B2
float64 | B3
float64 | B4
float64 | B5
float64 | B6
float64 | B7
float64 | B8
float64 | B8A
float64 | B9
float64 | B11
float64 | B12
float64 |
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2019-01-01
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2019-01-01
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2019-01-01
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2019-01-01
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2019-01-01
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2019-01-01
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2019-01-01
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2019-01-01
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2019-01-01
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2019-01-01
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2019-01-01
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End of preview. Expand
in Data Studio
Description
This dataset contains Sentinel-2 raw bands and reanalysis (NDVI, EVI, TCG) with valid pixel fractions per field.
Each parquet file contains multiple sunflower crop fields (identified as field_id).
Each field has 36 time stamps per year which is 10-day interval aggregation of the values of scaled and filtered bands and reanalysis.
Shape files of field polygons were loaded from Google Earth Engine (GEE) project assets.
Content
- Country: Hungary
- Fields: Sunflower
- Regions: ["Bacs-kiskun","Baranya","Bekes","Borsod-abauj-zemplen","Budapest", "Csongrad","Fejer","Gyor-moson-sopron","Hajdu-bihar","Heves", "Jasz-nagykun-szolnok","Komarom-esztergom","Nograd","Pest","Somogy", "Szabolcs-szatmar-bereg","Tolna","Vas","Veszprem","Zala"]
Parameters used
POLY_YEAR = 2022 # polygons are fixed to EUCROPMAP 2022
YEARS = [2019, 2020, 2021, 2022, 2023, 2024, 2025] # data (Sentinel-2) years to export
CROP_NAME = "sunflower"
SCALE = 10 # 10m resolution
STEP_DAYS = 10 # 10-day interval
TILESCALE = 4
MAX_ACTIVE = 3 # GEE usually allows ~1–3 concurrent tasks
SLEEP = 30
SCALE_FACTOR = ee.Number(10_000.0) # convert Sentinel-2 bands integer to [-1,1]
SCL_BAD = [3, 8, 9, 10, 11] # shadow, cloud med/high, cirrus, snow/ice
REFL_BANDS = ["B2","B3","B4","B5","B6","B7","B8","B8A","B9","B11","B12"]
OUT_BANDS = ["NDVI","EVI","TCG","valid"] + REFL_BANDS
hungary = (ee.FeatureCollection("FAO/GAUL/2015/level0") .filter(ee.Filter.eq("ADM0_NAME","Hungary")).geometry())
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