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Tien-Hao Liao
Division Office Geological and Planetary Sciences, California Institute of Technology, 6469 Pasadena, California, United States, 91125-0002

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Journal article
Published: 25 March 2021 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Slow-moving landslides are destabilized by accumulated precipitation and consequent soil moisture. Yet the continuous high-resolution soil moisture measurements needed to aid understanding of landslide processes are generally absent in steep terrain. Here we produce soil moisture time-series maps for a seasonally active grassland landslide in the northern California Coast Ranges, USA using backscattering coefficients from NASAs Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) at 6-m resolution. A physically based radar scattering model is used to retrieve the near-surface (5-cm depth) soil moisture for the landslide. Both forward modelling (backscattering estimation) and the retrieval (soil moisture validation) show good agreement. The root mean square errors (RMSE) for VV and HH polarizations in forward model comparison are 1.93 dB and 1.88 dB, respectively. The soil moisture retrieval shows unbiased RMSE (ubRMSE) of 0.054 m3/m3. Our successful retrieval benefits from surface and double-bounce scattering, which is common in grasslands. The retrieved maps show saturated wetness conditions within the active landslide boundaries. We also performed sensitivity tests for incidence angle and found that the retrieval is weakly dependent on the angle especially while using HH and VV together. Using the two co-pol inputs, the retrieval is also not sensitive to the change of orientation angles of grass cylinders. The physical model inversion presented here can be generally applied for soil moisture retrieval in areas with the same vegetation cover types in California.

ACS Style

Tien-Hao Liao; Seung-Bum Kim; Alexander L. Handwerger; Eric Fielding; Michael Cosh; William H Schulz. High-Resolution Soil-Moisture Maps Over Landslide Regions in Northern California Grassland Derived From SAR Backscattering Coefficients. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021, 14, 4547 -4560.

AMA Style

Tien-Hao Liao, Seung-Bum Kim, Alexander L. Handwerger, Eric Fielding, Michael Cosh, William H Schulz. High-Resolution Soil-Moisture Maps Over Landslide Regions in Northern California Grassland Derived From SAR Backscattering Coefficients. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021; 14 (99):4547-4560.

Chicago/Turabian Style

Tien-Hao Liao; Seung-Bum Kim; Alexander L. Handwerger; Eric Fielding; Michael Cosh; William H Schulz. 2021. "High-Resolution Soil-Moisture Maps Over Landslide Regions in Northern California Grassland Derived From SAR Backscattering Coefficients." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14, no. 99: 4547-4560.

Journal article
Published: 25 June 2020 in Remote Sensing
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We introduce a multiscale superpixel approach that leverages repeat-pass interferometric coherence and sparse AGB estimates from a simulated spaceborne lidar in order to extend the NISAR mission’s applicable range of aboveground biomass (AGB) in tropical forests. Airborne and spaceborne L-band radar and full-waveform airborne lidar data are used to simulate the NISAR and GEDI mission, respectively. In addition to UAVSAR data, we use spaceborne ALOS-2/PALSAR-2 imagery with 14-day temporal baseline, which is comparable to NISAR’s 12-day baseline. Our reference AGB maps are derived from the airborne LVIS data during the AfriSAR campaign for three sites (Mondah, Ogooue, and Lope). Each tropical site has mean AGB of at least 125 Mg/ha in addition to areas with AGB exceeding 700 Mg/ha. Spatially sampling from these LVIS-derived AGB reference maps, we approximate GEDI AGB estimates. To evaluate our methodology, we perform several different analyses. First, we partition each study site into low (≤100 Mg/ha) and high (>100 Mg/ha) AGB areas, in conformity with the NISAR mission requirement to provide AGB estimates for forests between 0 and 100 Mg/ha with a RMSE below 20 Mg/ha. In the low AGB areas, this RMSE requirement is satisfied in Lope and Mondah and it fell short of the requirement in Ogooue by less 3 Mg/ha with UAVSAR and 6 Mg/ha with PALSAR-2. We note that our maps have finer spatial resolution (50 m) than NISAR requires (1 hectare). In the high AGB areas, the normalized RMSE increases to 51% (i.e., <90 Mg/ha), but with negligible bias for all three sites. Second, we train a single model to estimate AGB across both high and low AGB regimes simultaneously and obtain a normalized RMSE that is <60% (or <100 Mg/ha). Lastly, we show the use of both (a) multiscale superpixels and (b) interferometric coherence significantly improves the accuracy of the AGB estimates. The InSAR coherence improved the RMSE by approximately 8% at Mondah with both sensors, lowering the RMSE from 59 Mg/ha to 47.4 Mg/h with UAVSAR and from 57.1 Mg/ha to 46 Mg/ha. This work illustrates one of the numerous synergistic relationships between the spaceborne lidars, such as GEDI, with L-band SAR, such as PALSAR-2 and NISAR, in order to produce robust regional AGB in high biomass tropical regions.

ACS Style

Charlie Marshak; Marc Simard; Laura Duncanson; Carlos Silva; Michael Denbina; Tien-Hao Liao; Lola Fatoyinbo; Ghislain Moussavou; John Armston. Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels. Remote Sensing 2020, 12, 2048 .

AMA Style

Charlie Marshak, Marc Simard, Laura Duncanson, Carlos Silva, Michael Denbina, Tien-Hao Liao, Lola Fatoyinbo, Ghislain Moussavou, John Armston. Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels. Remote Sensing. 2020; 12 (12):2048.

Chicago/Turabian Style

Charlie Marshak; Marc Simard; Laura Duncanson; Carlos Silva; Michael Denbina; Tien-Hao Liao; Lola Fatoyinbo; Ghislain Moussavou; John Armston. 2020. "Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels." Remote Sensing 12, no. 12: 2048.

Journal article
Published: 19 June 2020
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This paper provides the innovative approach of using a spatial extract, transform, load (ETL) solution for 3D building modelling, based on an unmanned aerial vehicle (UAV) photogrammetric point cloud. The main objective of the paper is to present the holistic workflow for 3D building modelling, emphasising the benefits of using spatial ETL solutions for this purpose. Namely, despite the increasing demands for 3D city models and their geospatial applications, the generation of 3D city models is still challenging in the geospatial domain. Advanced geospatial technologies provide various possibilities for the mass acquisition of geospatial data that is further used for 3D city modelling, but there is a huge difference in the cost and quality of input data. While aerial photogrammetry and airborne laser scanning involve high costs, UAV photogrammetry has brought new opportunities, including for small and medium-sized companies, by providing a more flexible and low-cost source of spatial data for 3D modelling. In our data-driven approach, we use a spatial ETL solution to reconstruct a 3D building model from a dense image matching point cloud which was obtained beforehand from UAV imagery. The results are 3D building models in a semantic vector format consistent with the OGC CityGML standard, Level of Detail 2 (LOD2). The approach has been tested on selected buildings in a simple semi-urban area. We conclude that spatial ETL solutions can be efficiently used for 3D building modelling from UAV data, where the data process model developed allows the developer to easily control and manipulate each processing step.

ACS Style

Urška Drešček; Mojca Kosmatin Fras; Jernej Tekavec; Anka Lisec; Charlie Marshak; Marc Simard; Laura Duncanson; Carlos Alberto Silva; Michael Denbina; Tien-Hao Liao; Lola Fatoyinbo; Ghislain Moussavou; John Armston. Spatial ETL for 3D Building Modelling based on Unmanned Aerial Vehicle Data in Semi-Urban Areas. 2020, 12, 1 .

AMA Style

Urška Drešček, Mojca Kosmatin Fras, Jernej Tekavec, Anka Lisec, Charlie Marshak, Marc Simard, Laura Duncanson, Carlos Alberto Silva, Michael Denbina, Tien-Hao Liao, Lola Fatoyinbo, Ghislain Moussavou, John Armston. Spatial ETL for 3D Building Modelling based on Unmanned Aerial Vehicle Data in Semi-Urban Areas. . 2020; 12 (12):1.

Chicago/Turabian Style

Urška Drešček; Mojca Kosmatin Fras; Jernej Tekavec; Anka Lisec; Charlie Marshak; Marc Simard; Laura Duncanson; Carlos Alberto Silva; Michael Denbina; Tien-Hao Liao; Lola Fatoyinbo; Ghislain Moussavou; John Armston. 2020. "Spatial ETL for 3D Building Modelling based on Unmanned Aerial Vehicle Data in Semi-Urban Areas." 12, no. 12: 1.

Journal article
Published: 18 September 2019 in IEEE Transactions on Electromagnetic Compatibility
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In this article, we apply the broadband Green's function for fast full-wave simulations of the radiated emissions from the printed circuit boards (PCBs) of irregular shape. Changes were made on the previous version that improve the computational efficiency and accuracies of the solutions. The improvements include imaginary wavenumber extractions for the acceleration of convergence of modal expansions without the need of high-order quadrature, and the fast-exact normalization of modes. Results of the radiated fields are illustrated over a broad frequency range up to 10 GHz and for irregular shaped PCB up to 4 in in sizes. The results are in good agreement with the method of moment for both the modal solutions and the radiated emissions. The results are shown to be more accurate than the previous version of broadband Green's functions with low wavenumber extractions. The significant computational efficiency makes this technique useful for electronic design automation to electromagnetic interference/electromagnetic compatibility applications.

ACS Style

Tien-Hao Liao; Leung Tsang; Weilun Kwek. Broadband Green's Function (BBGFL) Method With Imaginary Wavenumber Extractions for Simulations of Radiated Emissions From Irregular Shaped Printed Circuit Board. IEEE Transactions on Electromagnetic Compatibility 2019, 62, 2209 -2216.

AMA Style

Tien-Hao Liao, Leung Tsang, Weilun Kwek. Broadband Green's Function (BBGFL) Method With Imaginary Wavenumber Extractions for Simulations of Radiated Emissions From Irregular Shaped Printed Circuit Board. IEEE Transactions on Electromagnetic Compatibility. 2019; 62 (5):2209-2216.

Chicago/Turabian Style

Tien-Hao Liao; Leung Tsang; Weilun Kwek. 2019. "Broadband Green's Function (BBGFL) Method With Imaginary Wavenumber Extractions for Simulations of Radiated Emissions From Irregular Shaped Printed Circuit Board." IEEE Transactions on Electromagnetic Compatibility 62, no. 5: 2209-2216.

Journal article
Published: 26 April 2019 in Water
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Floodplain water flows have large volumetric flowrates and high complexity in space and time that are difficult to understand using water level gauges. We here analyze the spatial and temporal fluctuations of surface water flows in the floodplain of the Atrato River, Colombia, in order to evaluate their hydrological connectivity. The basin is one of the rainiest areas of the world with wetland ecosystems threatened by the expansion of agriculture and mining activities. We used 16 Differential Interferometric Synthetic Aperture Radars (DInSAR) phase observations from the ALOS-PALSAR L-band instrument acquired between 2008–2010 to characterize the flow of surface water. We were able to observe water level change in vegetated wetland areas and identify flooding patterns. In the lower basin, flow patterns are conditioned by fluctuations in the levels of the main river channel, whereas in the middle basin, topography and superficial channels strongly influence the flow and connectivity. We found that the variations in water level in a station on the main channel 87 km upstream explained more than 56% of the variations in water level in the floodplain. This result shows that, despite current expansion of agriculture and mining activities, there remain significant hydrological connectivity between wetlands and the Atrato River. This study demonstrates the use of DInSAR for a spatially comprehensive monitoring of the Atrato River basin hydrology. For the first time, we identified the spatiotemporal patterns of surface water flow of the region. We recommend these observations serve as a baseline to monitor the potential impact of ongoing human activities on surface water flows across the Atrato River basin.

ACS Style

Sebastián Palomino-Ángel; Jesús A. Anaya-Acevedo; Marc Simard; Tien-Hao Liao; Fernando Jaramillo. Analysis of Floodplain Dynamics in the Atrato River Colombia Using SAR Interferometry. Water 2019, 11, 875 .

AMA Style

Sebastián Palomino-Ángel, Jesús A. Anaya-Acevedo, Marc Simard, Tien-Hao Liao, Fernando Jaramillo. Analysis of Floodplain Dynamics in the Atrato River Colombia Using SAR Interferometry. Water. 2019; 11 (5):875.

Chicago/Turabian Style

Sebastián Palomino-Ángel; Jesús A. Anaya-Acevedo; Marc Simard; Tien-Hao Liao; Fernando Jaramillo. 2019. "Analysis of Floodplain Dynamics in the Atrato River Colombia Using SAR Interferometry." Water 11, no. 5: 875.

Journal article
Published: 04 April 2018 in Remote Sensing
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Soil surface roughness and above-ground vegetation water content (VWC) are estimated by inverting physical models for L-band scattering and absorption at 40° incidence angle using ground, airborne and Soil Moisture Active Passive (SMAP) radar data. The spatial resolution varies from field scale (airborne and ground) to 3 km (SMAP). The temporal resolution is defined by the length and interval of observation time windows (weeks to three months for surface roughness, and three to seven days for VWC). The validation of the roughness estimates shows an accuracy of 25% (bare surface) and 29 to 46% (croplands and pasture). The correlation degrades as vegetation becomes thicker, indicating the stronger scattering and absorption by thicker vegetation. The roughness retrievals with the SMAP data are within the physical range of 0.5 cm to 4 cm. They show larger values in croplands than in natural terrain. The VWC estimate modifies a ‘first guess’ (in situ values for the airborne experiment; and 16-daily climatology for SMAP). The VWC retrievals correctly follow the full growth of crops and the RMSE is smaller than 20% in the airborne retrievals: the correlation ranges from 0.57 to 0.91. These results demonstrate that the forward model inversion has a potential to retrieve VWC for the four major crops over the entire phase of the crop growth. The VWC retrievals from the SMAP data revised the climatology first guess more in the croplands, where the climatology is more likely to depart from the contemporaneous condition than in natural landcover. The value of this work lies in the fact that the surface roughness at the footprint scale is difficult to characterize and a global VWC product at SMAP’s spatial scale from microwave observations is rare, and that this paper presents a plausible pathway towards such products. The estimates at these temporal and spatial scales derived from microwave observations will be useful for studies of climate, agriculture, and soil moisture.

ACS Style

Seung-Bum Kim; Huanting Huang; Tien-Hao Liao; Andreas Colliander. Estimating Vegetation Water Content and Soil Surface Roughness Using Physical Models of L-Band Radar Scattering for Soil Moisture Retrieval. Remote Sensing 2018, 10, 556 .

AMA Style

Seung-Bum Kim, Huanting Huang, Tien-Hao Liao, Andreas Colliander. Estimating Vegetation Water Content and Soil Surface Roughness Using Physical Models of L-Band Radar Scattering for Soil Moisture Retrieval. Remote Sensing. 2018; 10 (4):556.

Chicago/Turabian Style

Seung-Bum Kim; Huanting Huang; Tien-Hao Liao; Andreas Colliander. 2018. "Estimating Vegetation Water Content and Soil Surface Roughness Using Physical Models of L-Band Radar Scattering for Soil Moisture Retrieval." Remote Sensing 10, no. 4: 556.