Agricultural SandboxNL: A national-scale database of parcel-level processed Sentinel-1 SAR data

Agricultural SandboxNL: A national-scale database of parcel-level processed Sentinel-1 SAR data

Synthetic Aperture Radar (SAR) data handling, processing, and interpretation are barriers preventing a rapid uptake of SAR data by application specialists and non-expert domain users in the field of agricultural monitoring. To improve the accessibility of Sentinel-1 data, we have generated a reduced...

Full description

Saved in:
Bibliographic Details
Published in:Scientific data Vol. 9; no. 1; pp. 402 - 14
Main Authors: Kumar, Vineet, Huber, Manuel, Rommen, Björn, Steele-Dunne, Susan C.
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 13-07-2022
Nature Publishing Group
Nature Portfolio
Subjects:
706/1143
706/648
Crops
Data Descriptor
Drought
Grasslands
Humanities and Social Sciences
multidisciplinary
Parameter estimation
Remote sensing
Science
Science (multidisciplinary)
Netherlands
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Synthetic Aperture Radar (SAR) data handling, processing, and interpretation are barriers preventing a rapid uptake of SAR data by application specialists and non-expert domain users in the field of agricultural monitoring. To improve the accessibility of Sentinel-1 data, we have generated a reduced-volume, multi-year Sentinel-1 SAR database. It includes mean and standard deviation of VV, VH and VH/VV backscatter, pixel counts, geometry, crop type, local incidence angle and azimuth angle at parcel-level. The database uses around 3100 Sentinel-1 images (5 TB) to produce a 12 GB time series database for approximately 770,000 crop parcels over the Netherlands for a period of three years. The database can be queried by Sentinel-1 system parameters (e.g. relative orbit) or user application-specific parameters (e.g. crop type, spatial extent, time period) for parcel level assessment. The database can be used to accelerate the development of new tools, applications and methodologies for agricultural and water related applications, such as parcel-level crop bio-geophysical parameter estimation, inter-annual variability analysis, drought monitoring, grassland monitoring and agricultural management decision-support. Measurement(s) parcel-level backscatter • cross-ratio Technology Type(s) SAR remote sensing • Sentinel-1 • Google Earth Engine Sample Characteristic - Location The Netherlands
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-022-01474-4