@inproceedings{db539f5afe3c4465b90dc52468c875af,
title = "Optimal Spatial Resolution of Sentinel-1 Surface Soil Moisture Evaluated Using Intensive in Situ Observations",
abstract = "Space-borne SAR instruments can provide backscatter on a high spatial resolution, and with the introduction of the Sentinel-1 satellites, these can co-exist with relatively high temporal resolutions. Here, we use a combination of active microwave Sentinel-1 and optical Sentinel-2 data in the MULESME algorithm to estimate soil moisture on a field in Southeastern Luxembourg. Satellite data were compared to data gathered in the field and semi-continuous measurements from a nearby permanent station. Our results indicate that the accuracy of MULESME soil moisture estimates increases with a decrease in spatial resolution, but that this increase stagnates rather soon after the first few spatial aggregations, thus confirming the value of high resolution data. Future endeavours will focus on the analysis of soil moisture variation in time, compared to soil moisture measurements from a nearby permanent station.",
keywords = "Microwave measurement, Satellite constellations, Uncertainty, Satellites, Soil measurements, Moisture measurement, Soil moisture",
author = "\{van Hateren\}, \{Theresa C.\} and Marco Chini and Patrick Matgen and Luca Pulvirenti and Nazzareno Pierdicca and Teuling, \{Adriaan J.\}",
year = "2021",
month = oct,
day = "12",
doi = "10.1109/IGARSS47720.2021.9553041",
language = "English",
isbn = "9781665447621",
series = "International Symposium on Geoscience and Remote Sensing",
publisher = "IEEE",
pages = "6311--6314",
booktitle = "2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS",
address = "United States",
note = "2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS ; Conference date: 11-07-2021 Through 16-07-2021",
}