Xiaoling Wu

Dr. Xiaoling Wu

Department of Civil Engineering, Monash University, Melbourne, Australia
orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2017 in Remote Sensing of Environment
Verified
Journal Article
Closed access
Andreas CollianderAndreas Colliander
Andreas Colliander
TJT.J. Jackson
T.J. Jackson
RBR. Bindlish
R. Bindlish
SCS. Chan
S. Chan
NDN. Das
N. Das
SYS. Yueh
S. Yueh

25 May 2016 in IEEE Transactions on Geoscience and Remote Sensing
Verified
Journal Article
Closed access
SCSteven K. Chan
Steven K. Chan
RBRajat Bindlish
Rajat Bindlish
POPeggy E. O'NEill
Peggy E. O'NEill
ENEni Njoku
Eni Njoku
TJTom Jackson
Tom Jackson
Yann KERRYann KERR
Yann KERR
The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 km Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 m 3 /m 3 unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 m 3 /m 3 .

28 September 2017 in Journal of Hydrometeorology
Verified
Journal Article
Open access
PDF file
RRRolf Reichle
Rolf Reichle
GLGabrielle J. M. De Lannoy
Gabrielle J. M. De Lannoy
QLQing Liu
Qing Liu
JAJoseph V. Ardizzone
Joseph V. Ardizzone
ACAndreas Colliander
Andreas Colliander
Yijian ZengYijian Zeng
Yijian Zeng
The Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real time) and provides 3-hourly, global, 9-km resolution estimates of surface (0–5 cm) and root-zone (0–100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach, and product assessment versus in situ measurements. Core validation sites provide spatially averaged surface (root zone) soil moisture measurements for 43 (17) “reference pixels” at 9- and 36-km gridcell scales located in 17 (7) distinct watersheds. Sparse networks provide point-scale measurements of surface (root zone) soil moisture at 406 (311) locations. Core validation site results indicate that the L4_SM product meets its soil moisture accuracy requirement, specified as an unbiased RMSE (ubRMSE, or standard deviation of the error) of 0.04 m3 m−3 or better. The ubRMSE for L4_SM surface (root zone) soil moisture is 0.038 m3 m−3 (0.030 m3 m−3) at the 9-km scale and 0.035 m3 m−3 (0.026 m3 m−3) at the 36-km scale. The L4_SM estimates improve (significantly at the 5% level for surface soil moisture) over model-only estimates, which do not benefit from the assimilation of SMAP brightness temperature observations and have a 9-km surface (root zone) ubRMSE of 0.042 m3 m−3 (0.032 m3 m−3). Time series correlations exhibit similar relative performance. The sparse network results corroborate these findings over a greater variety of climate and land cover conditions.

13 March 2013 in IEEE Transactions on Geoscience and Remote Sensing
Verified
Journal Article
Closed access
RPRocco Panciera
Rocco Panciera
JWJeffrey Walker
Jeffrey Walker
TJThomas J. Jackson
Thomas J. Jackson
DGDouglas A. Gray
Douglas A. Gray
MTMihai Andrei Tanase
Mihai Andrei Tanase
JHJorg M. Hacker
Jorg M. Hacker
NASA's Soil Moisture Active Passive (SMAP) mission will carry the first combined spaceborne L-band radiometer and Synthetic Aperture Radar (SAR) system with the objective of mapping near-surface soil moisture and freeze/thaw state globally every 2-3 days. SMAP will provide three soil moisture products: i) high-resolution from radar (~3 km), ii) low-resolution from radiometer (~36 km), and iii) intermediate-resolution from the fusion of radar and radiometer (~9 km). The Soil Moisture Active Passive Experiments (SMAPEx) are a series of three airborne field experiments designed to provide prototype SMAP data for the development and validation of soil moisture retrieval algorithms applicable to the SMAP mission. This paper describes the SMAPEx sampling strategy and presents an overview of the data collected during the three experiments: SMAPEx-1 (July 5-10, 2010), SMAPEx-2 (December 4-8, 2010) and SMAPEx-3 (September 5-23, 2011). The SMAPEx experiments were conducted in a semi-arid agricultural and grazing area located in southeastern Australia, timed so as to acquire data over a seasonal cycle at various stages of the crop growth. Airborne L-band brightness temperature (~1 km) and radar backscatter (~10 m) observations were collected over an area the size of a single SMAP footprint (38 km × 36 km at 35° latitude) with a 2-3 days revisit time, providing SMAP-like data for testing of radiometer-only, radar-only and combined radiometer-radar soil moisture retrieval and downscaling algorithms. Airborne observations were supported by continuous monitoring of near-surface (0-5 cm) soil moisture along with intensive ground monitoring of soil moisture, soil temperature, vegetation biomass and structure, and surface roughness.

1 March 2020 in Remote Sensing of Environment
Verified
Journal Article
Closed access
SSSabah Sabaghy
Sabah Sabaghy
JWJeffrey Walker
Jeffrey Walker
LRLuigi J. Renzullo
Luigi J. Renzullo
RARuzbeh Akbar
Ruzbeh Akbar
SCSteven Chan
Steven Chan
SYSimon Yueh
Simon Yueh

1 June 2018 in Remote Sensing of Environment
Verified
Journal Article
Closed access
NDNarendra N. Das
Narendra N. Das
DEDara Entekhabi
Dara Entekhabi
RDR. Scott Dunbar
R. Scott Dunbar
Andreas CollianderAndreas Colliander
Andreas Colliander
FCFan Chen
Fan Chen
ENEni G. Njoku
Eni G. Njoku