13 Access to Near Real Time Soil Moisture Data – Earth Observation Datascience

Downloading, Reading and Working with H SAF Surface Soil Moisture 6.25 km

13.1 Overview

13.2 Imports

import os
from datetime import datetime, timedelta

import cartopy.crs as ccrs
import hvplot.pandas  # noqa
from ascat.download.interface import hsaf_download
from ascat.swath import SwathGridFiles
from dotenv import dotenv_values

credentials = {
    "user": dotenv_values(".env")["USER_HSAF"],
    "password": dotenv_values(".env")["PASS_HSAF"],
}
local_path = "h130"
remote_path = "h130/h130_cur_mon_data"
start_date = datetime.now() - timedelta(days=15)
end_date = datetime.now()

%%time

if not os.path.isdir(local_path):
    os.mkdir(local_path)

hsaf_download(credentials, remote_path, local_path, start_date, end_date, limit=5)

2025-08-13 14:31:42,648 INFO: FTP connection successfully established

2025-08-13 14:32:31,602 INFO: FTP disconnected

CPU times: user 484 ms, sys: 282 ms, total: 766 ms
Wall time: 49.6 s

h130_nrt = SwathGridFiles.from_product_id(local_path, product_id="H130")

df = h130_nrt.read(date_range=(start_date, end_date)).to_dataframe()
df

	location_id	as_des_pass	swath_indicator	surface_flag	surface_flag_source	surface_soil_moisture	surface_soil_moisture_noise	backscatter40	slope40	curvature40	...	processing_flag	snow_cover_probability	frozen_soil_probability	wetland_fraction	topographic_complexity	subsurface_scattering_probability	sat_id	latitude	longitude	time
obs
0	2261676	1.0	0.0	1.0	9.0	NaN	NaN	NaN	NaN	NaN	...	3.0	NaN	NaN	0.0	0.0	0.0	5	20.164428	-129.765640	2025-07-29 19:00:00.399000064
1	2264260	1.0	0.0	1.0	9.0	NaN	NaN	NaN	NaN	NaN	...	3.0	NaN	NaN	0.0	0.0	0.0	5	20.188432	-129.827941	2025-07-29 19:00:00.399000064
2	2266844	1.0	0.0	1.0	9.0	NaN	NaN	NaN	NaN	NaN	...	3.0	NaN	NaN	0.0	0.0	0.0	5	20.212438	-129.890243	2025-07-29 19:00:00.399000064
3	2267831	1.0	0.0	1.0	9.0	NaN	NaN	NaN	NaN	NaN	...	3.0	NaN	NaN	0.0	0.0	0.0	5	20.221609	-130.053359	2025-07-29 19:00:00.399000064
4	2269428	1.0	0.0	1.0	9.0	NaN	NaN	NaN	NaN	NaN	...	3.0	NaN	NaN	0.0	0.0	0.0	5	20.236448	-129.952545	2025-07-29 19:00:00.399000064
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
4015495	4064358	1.0	1.0	1.0	9.0	NaN	NaN	NaN	NaN	NaN	...	3.0	NaN	NaN	0.0	0.0	0.0	5	38.197776	139.121109	2025-07-29 23:59:59.298999808
4015496	4064968	1.0	1.0	1.0	9.0	NaN	NaN	NaN	NaN	NaN	...	3.0	NaN	NaN	0.0	4.0	0.0	5	38.204509	139.385040	2025-07-29 23:59:59.298999808
4015497	4065955	1.0	1.0	1.0	9.0	NaN	NaN	NaN	NaN	NaN	...	3.0	NaN	NaN	0.0	0.0	0.0	5	38.215400	139.221923	2025-07-29 23:59:59.298999808
4015498	4066942	1.0	1.0	1.0	9.0	NaN	NaN	NaN	NaN	NaN	...	3.0	NaN	NaN	0.0	0.0	0.0	5	38.226299	139.058807	2025-07-29 23:59:59.298999808
4015499	4069526	1.0	1.0	1.0	9.0	NaN	NaN	NaN	NaN	NaN	...	3.0	NaN	NaN	0.0	0.0	0.0	5	38.254829	138.996505	2025-07-29 23:59:59.298999808

4015500 rows × 23 columns

%run ./src/ssm_cmap.py

df.hvplot.points(
    x="longitude",
    y="latitude",
    c="surface_soil_moisture",
    x_sampling=0.16,
    y_sampling=0.16,
    rasterize=True,
    crs=ccrs.PlateCarree(),
    tiles=True,
    cmap=SSM_CMAP,  # noqa
    clim=(0, 100),
    frame_width=500,
    clabel="Surface soil moisture (%)",
)