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Soil Moisture Estimation Using Atmospherically Corrected C-Band InSAR Data. / Mira, Nuno Cirne; Catalao, Joao; Nico, Giovanni; Mateus, Pedro.

в: IEEE Transactions on Geoscience and Remote Sensing, Том 60, 01.01.2022.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

Harvard

Mira, NC, Catalao, J, Nico, G & Mateus, P 2022, 'Soil Moisture Estimation Using Atmospherically Corrected C-Band InSAR Data', IEEE Transactions on Geoscience and Remote Sensing, Том. 60. https://doi.org/10.1109/TGRS.2021.3109450

APA

Mira, N. C., Catalao, J., Nico, G., & Mateus, P. (2022). Soil Moisture Estimation Using Atmospherically Corrected C-Band InSAR Data. IEEE Transactions on Geoscience and Remote Sensing, 60. https://doi.org/10.1109/TGRS.2021.3109450

Vancouver

Mira NC, Catalao J, Nico G, Mateus P. Soil Moisture Estimation Using Atmospherically Corrected C-Band InSAR Data. IEEE Transactions on Geoscience and Remote Sensing. 2022 Янв. 1;60. https://doi.org/10.1109/TGRS.2021.3109450

Author

Mira, Nuno Cirne ; Catalao, Joao ; Nico, Giovanni ; Mateus, Pedro. / Soil Moisture Estimation Using Atmospherically Corrected C-Band InSAR Data. в: IEEE Transactions on Geoscience and Remote Sensing. 2022 ; Том 60.

BibTeX

@article{e8a74d5d980c48249cdc099b204215d0,
title = "Soil Moisture Estimation Using Atmospherically Corrected C-Band InSAR Data",
abstract = "A methodology to generate calibrated maps of soil moisture from C-band synthetic aperture radar (SAR) images processed by SAR interferometry (InSAR) technique is presented. The proposed methodology uses atmospheric phase delay (APD) maps obtained from a time series of Sentinel-1 interferograms, to disentangle the APD and soil moisture contributions to Sentinel-1 interferograms. We show how the high spatial resolution and short temporal baseline of Sentinel-1 image can help to estimate soil moisture using a daisy chain InSAR processing. The estimated soil moisture maps are compared with in situ data collected by five soil moisture sensors installed in an experimental field, characterized by bare soil, located close to Lisbon, Portugal. Results show that after removing the APD effects in SAR interferogram, there is a correction of the bias in the soil moisture estimation and an improvement in the correlation coefficient with the soil moisture measurements, from 0.38 to 0.78. Soil moisture changes were measured during a sequence of rain events in the winter season. A root-mean-square (rms) error less than 0.04 m3/m3 was found over a variety of meteorological conditions.",
keywords = "Atmospheric phase delay (APD), SAR interferometry (InSAR), soil moisture, synthetic aperture radar (SAR)",
author = "Mira, {Nuno Cirne} and Joao Catalao and Giovanni Nico and Pedro Mateus",
year = "2022",
month = jan,
day = "1",
doi = "10.1109/TGRS.2021.3109450",
language = "English",
volume = "60",
journal = "IEEE Transactions on Geoscience and Remote Sensing",
issn = "0196-2892",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

RIS

TY - JOUR

T1 - Soil Moisture Estimation Using Atmospherically Corrected C-Band InSAR Data

AU - Mira, Nuno Cirne

AU - Catalao, Joao

AU - Nico, Giovanni

AU - Mateus, Pedro

PY - 2022/1/1

Y1 - 2022/1/1

N2 - A methodology to generate calibrated maps of soil moisture from C-band synthetic aperture radar (SAR) images processed by SAR interferometry (InSAR) technique is presented. The proposed methodology uses atmospheric phase delay (APD) maps obtained from a time series of Sentinel-1 interferograms, to disentangle the APD and soil moisture contributions to Sentinel-1 interferograms. We show how the high spatial resolution and short temporal baseline of Sentinel-1 image can help to estimate soil moisture using a daisy chain InSAR processing. The estimated soil moisture maps are compared with in situ data collected by five soil moisture sensors installed in an experimental field, characterized by bare soil, located close to Lisbon, Portugal. Results show that after removing the APD effects in SAR interferogram, there is a correction of the bias in the soil moisture estimation and an improvement in the correlation coefficient with the soil moisture measurements, from 0.38 to 0.78. Soil moisture changes were measured during a sequence of rain events in the winter season. A root-mean-square (rms) error less than 0.04 m3/m3 was found over a variety of meteorological conditions.

AB - A methodology to generate calibrated maps of soil moisture from C-band synthetic aperture radar (SAR) images processed by SAR interferometry (InSAR) technique is presented. The proposed methodology uses atmospheric phase delay (APD) maps obtained from a time series of Sentinel-1 interferograms, to disentangle the APD and soil moisture contributions to Sentinel-1 interferograms. We show how the high spatial resolution and short temporal baseline of Sentinel-1 image can help to estimate soil moisture using a daisy chain InSAR processing. The estimated soil moisture maps are compared with in situ data collected by five soil moisture sensors installed in an experimental field, characterized by bare soil, located close to Lisbon, Portugal. Results show that after removing the APD effects in SAR interferogram, there is a correction of the bias in the soil moisture estimation and an improvement in the correlation coefficient with the soil moisture measurements, from 0.38 to 0.78. Soil moisture changes were measured during a sequence of rain events in the winter season. A root-mean-square (rms) error less than 0.04 m3/m3 was found over a variety of meteorological conditions.

KW - Atmospheric phase delay (APD)

KW - SAR interferometry (InSAR)

KW - soil moisture

KW - synthetic aperture radar (SAR)

UR - http://www.scopus.com/inward/record.url?scp=85114728919&partnerID=8YFLogxK

U2 - 10.1109/TGRS.2021.3109450

DO - 10.1109/TGRS.2021.3109450

M3 - Article

AN - SCOPUS:85114728919

VL - 60

JO - IEEE Transactions on Geoscience and Remote Sensing

JF - IEEE Transactions on Geoscience and Remote Sensing

SN - 0196-2892

ER -

ID: 114329351