Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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 изданиях › статья › Рецензирование
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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