TY - JOUR
T1 - Near-surface soil moisture retrieval from ASAR Wide Swath imagery using a Principal Component Analysis
AU - Kong, Xin
AU - Dorling, Steve
PY - 2008
Y1 - 2008
N2 - The new ENVISAT Advanced Synthetic Aperture Radar (ASAR) Wide Swath Mode (WSM) data provide good potential for routinely monitoring near surface soil moisture due to the increased temporal revisit capability compared with ERS2 SAR. In this paper, we propose a Principal Components Analysis (PCA) to retrieve near‐surface soil moisture from ASAR WSM data. The results demonstrate that PCA transformation can at least partially separate or group the effect factors, such as surface roughness, land cover, vegetation, and topography within the limitations of our datasets. The second principal component which was consistent with soil moisture and rainfall‐runoff dynamics was representative of the soil moisture Saturation Potential Index over a large area. Validation against field measurements and against the UK Met Office Surface Exchange Scheme shows the retrieval performs with reasonable accuracy.
AB - The new ENVISAT Advanced Synthetic Aperture Radar (ASAR) Wide Swath Mode (WSM) data provide good potential for routinely monitoring near surface soil moisture due to the increased temporal revisit capability compared with ERS2 SAR. In this paper, we propose a Principal Components Analysis (PCA) to retrieve near‐surface soil moisture from ASAR WSM data. The results demonstrate that PCA transformation can at least partially separate or group the effect factors, such as surface roughness, land cover, vegetation, and topography within the limitations of our datasets. The second principal component which was consistent with soil moisture and rainfall‐runoff dynamics was representative of the soil moisture Saturation Potential Index over a large area. Validation against field measurements and against the UK Met Office Surface Exchange Scheme shows the retrieval performs with reasonable accuracy.
U2 - 10.1080/01431160701442088
DO - 10.1080/01431160701442088
M3 - Article
SN - 0143-1161
VL - 29
SP - 2925
EP - 2942
JO - INTERNATIONAL JOURNAL OF REMOTE SENSING
JF - INTERNATIONAL JOURNAL OF REMOTE SENSING
IS - 10
ER -