Article
Geochemistry & Geophysics
Shiyu Luo, Kamal Sarabandi, Ling Tong, Leland E. Pierce
Summary: This article proposes a new quantitative method for rainfall-induced landslide probability assessment based on safety factors (SFs) using soil moisture estimation from synthetic aperture radar (SAR) images. The effectiveness of the method is tested qualitatively and quantitatively through instrument verification and field investigation, showing that observed landslides are located in the unstable areas, indirectly verifying the proposed method.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Simon H. Yueh, Rashmi Shah, Xiaolan Xu, Bryan Stiles, Xavier Bosch-Lluis
Summary: The study analyzed the spaceborne aperture radar (SAR) technique based on a combination of signals from the United States Navy's Mobile User Objective System and P-hand signals of opportunity with a sparse array of receivers at low earth orbits. The design focused on forward-looking geometry near the specular direction to achieve high surface reflectivity and adequate signal-to-noise ratio. Utilizing a sparse array sharpened the resolution, reduced ambiguity, and showed promise for high-resolution remote sensing of land surfaces.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Dong Fan, Tianjie Zhao, Xiaoguang Jiang, Huazhu Xue, Sitthisak Moukomla, Kittiwet Kuntiyawichai, Jiancheng Shi
Summary: In this study, a dual-temporal dual-channel (DTDC) algorithm was proposed to retrieve soil moisture using Sentinel-1 SAR data. By utilizing ancillary information from optical images and assuming constant surface roughness, the algorithm could solve for two consecutive soil moisture values and one roughness parameter simultaneously. The algorithm was tested on croplands in Northeast Thailand and demonstrated good performance in capturing temporal soil moisture changes and achieving similar patterns as a reference mission. This suggests that Sentinel-1 can be a suitable tool for agricultural water management.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Geochemistry & Geophysics
Terhikki Manninen, Emmihenna Jaaskelainen, Annalea Lohila, Mika Korkiakoski, Aleksi Rasanen, Tarmo Virtanen, Filip Muhic, Hannu Marttila, Pertti Ala-Aho, Mira Markovaara-Koivisto, Pauliina Liwata-Kenttala, Raimo Sutinen, Pekka Hanninen
Summary: A soil moisture estimation method has been developed for Sentinel-1 SAR data, utilizing PIMSAR nonlocal mean filtering and GBT machine learning for algorithm development, with successful results.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Davide Palmisano, Giuseppe Satalino, Anna Balenzano, Francesco Mattia
Summary: This study proposes a hybrid incoherent-coherent change detection approach to retrieve surface soil moisture from Sentinel-1 data. It combines time-series observations of SAR backscatter and interferometric closure phase without external calibration. The results show good performance for bare soils and poor results for vegetated surfaces.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Geosciences, Multidisciplinary
Jianjun Wang, Fei Wu, Jiali Shang, Qi Zhou, Irshad Ahmad, Guisheng Zhou
Summary: This study investigates the potential of using Sentinel-1A SAR imagery and Machine Learning Algorithms for soil moisture (SM) mapping in China's east coast. The newly developed SVR model provides more accurate SM estimation than the RFR and MLR models, and can effectively map SM even without information on soil surface roughness, soil salinity, and land cover types.
Article
Geochemistry & Geophysics
William Maslanka, Keith Morrison, Kevin White, Anne Verhoef, Joanna Clark
Summary: The spatiotemporal distribution of soil moisture is important for hydrometeorological and agricultural applications. This study monitored the relative surface soil moisture (rSSM) in the Thames Valley, U.K., using Sentinel-1 data and the TU-Wien Change Detection Algorithm. The study explored the effects of normalization factors and spatial averaging on rSSM values at different spatial resolutions. Comparisons with in situ soil moisture data showed temporal trends agreement but difficulties in comparison due to measurement depth and vegetation impacts. The study found that rSSM trends can be retrieved at resolutions as low as 100 m and RMSE decreases with increasing spatial resolution. The study also highlighted the impact of vegetation on rSSM.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Electrical & Electronic
Sadegh Ranjbar, Mehdi Akhoondzadeh, Brian Brisco, Meisam Amani, Mehdi Hosseini
Summary: This study investigated the impact of soil moisture changes on different crops and analyzed the relationship between ΔM-v and φ through regression techniques, suggesting that UAVSAR is more accurate for monitoring ΔM-v compared to Sentinel-1. The results demonstrate promising potential for using φ information from Sentinel-1 data in the early stages of crop growth, but recommend the use of L-band SAR data and shorter temporal baselines as crop biomass increases.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Mehmet Kurum, Seung-Bum Kim, Ruzbeh Akbar, Michael H. Cosh
Summary: Surface soil moisture retrieval using L-band airborne synthetic aperture radar (SAR) data with physical scattering models was accurate and showed high correlation in detecting soil moisture levels within forests with varying vegetation water content. The inversion of scattering model proved to be effective for estimating forest soil moisture, offering systematic correction of vegetation effects and precise retrieval of dynamic ranges of soil moisture values in unbiased root mean square error.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Hontao Shi, Juan M. Lopez-Sanchez, Jie Yang, Pingxiang Li, Lingli Zhao, Jinqi Zhao
Summary: This study investigates how fully polarimetric data and multiple incidence angles can enhance the accuracy of the alpha approximation method for soil moisture estimation. Results show that the inclusion of polarimetric decomposition and multi-incidence observations significantly improves the retrieval accuracy, with the best performance achieved when combining both methods.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Nuno Cirne Mira, Joao Catalao, Giovanni Nico, Pedro Mateus
Summary: A methodology using C-band SAR images processed by InSAR technique is proposed to generate calibrated maps of soil moisture. By utilizing APD maps from Sentinel-1 interferograms, the methodology separates APD and soil moisture contributions, resulting in improved soil moisture estimation accuracy. The study demonstrates the effectiveness of the approach through comparison with in situ soil moisture data collected in an experimental field, showing a significant increase in correlation coefficient.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Aerospace
Michael Inggs
Summary: This document summarizes the achievements in synthetic aperture radar (SAR) technology during the 50-year existence of the Aerospace and Electronic Systems Society. Advances in radar technology, driven by the digital revolution, have led to the widespread application of SAR in various fields. The development of coherent radar during World War II enabled the formation of large synthetic apertures, resulting in microwave images with high resolution that are unaffected by time and weather. The article traces the history of SAR technology from airborne platforms to satellites and discusses its achievements. SAR technology has now entered the phase of commercial exploitation, with a significant increase in available systems.
IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE
(2023)
Article
Environmental Sciences
Julian Dann, Katrina E. Bennett, W. Robert Bolton, Cathy J. Wilson
Summary: This study analyzed the factors controlling summer root-zone soil moisture in a 4500 km(2) area on the Seward Peninsula of Alaska, showing that vegetation primarily controls soil moisture in shallow soil layers, while topography and meteorological factors play a larger role in deeper layers. The random forest model developed accounted for 40% to 60% of the observed variation, indicating the importance of secondary factors in influencing root-zone soil moisture distribution.
Article
Geochemistry & Geophysics
Hongyang An, Junjie Wu, Kah Chan Teh, Zhichao Sun, Zhongyu Li, Jianyu Yang
Summary: This article proposes an efficient video formation method for video SAR systems with reduced data, modeling the observed scene as a sum of low-rank and sparse tensors and using a tensor alternating direction method of multiplier. Compared to traditional imaging methods, the proposed approach greatly reduces the amount of data samples.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Hassan Bazzi, Nicolas Baghdadi, Ghaith Amin, Ibrahim Fayad, Mehrez Zribi, Valerie Demarez, Hatem Belhouchette
Summary: This study presents an operational methodology for mapping irrigated areas at plot scale using SAR and optical time series data. The method was successfully applied over four years, with a newly developed irrigation classification model achieving high overall accuracy. Validation using real in situ data showed that the proposed approach had similar accuracy to classifiers built directly from field data. Analysis revealed that classification accuracy was influenced by precipitation levels during the growing season.
Article
Engineering, Electrical & Electronic
Andreas Colliander, Rolf Reichle, Wade Crow, Michael Cosh, Fan Chen, Steven Chan, Narendra Narayan Das, Rajat Bindlish, J. Chaubell, Seungbum Kim, Qing Liu, Peggy OaNeill, Scott Dunbar, Land Dang, John S. Kimball, Thomas Jackson, Hala Al-Jassar, Jun Asanuma, Bimal Bhattacharya, Aaron Berg, David Bosch, Laura Bourgeau-Chavez, Todd Caldwell, Jean-Christophe Calvet, Chandra Collins, Karsten Jensen, Stan Livingston, Ernesto Lopez-Baeza, Jose Martinez-Fernandez, Heather McNairn, Mahta Moghaddam, Carsten Montzka, Claudia Notarnicola, Thierry Pellarin, Isabella Greimeister-Pfeil, Jouni Pulliainen, Judith Ramos, Judith Gpe. Ramos Hernandez, Mark Seyfried, Patrick Starks, Bob Su, R. van der Velde, Yijian Zeng, Marc Thibeault, Mariette Vreugdenhil, Jeffrey Walker, Mehrez Zribi, Dara Entekhabi, Simon Yueh
Summary: The National Aeronautics and Space Administration's Soil Moisture Active Passive (SMAP) mission has been validating its soil moisture products since 2015. The results show that the SMAP products meet the mission requirements and are generally consistent with other satellite products. The validation program will continue and plans to expand to forested and high-latitude regions.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Ruzbeh Akbar, Samuel Prager, Agnelo R. Silva, Mahta Moghaddam, Dara Entekhabi
Summary: This paper presents an optimization-based UAV path planning methodology aimed at maximizing UAV flight coverage over areas where a complementing WSN yields upscaled soil moisture estimates with high uncertainty, in order to gradually capture the true mean soil moisture of the region. A series of numerical simulations are conducted to demonstrate the algorithm's basic function under real-world and feasible operational scenarios.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Qianyu Chang, Simon Zwieback, Ben DeVries, Aaron Berg
Summary: This study evaluated the sensitivity of ALOS-2 data to vegetation in the Northwest Territories of Canada, finding a strong sensitivity of the VH/VV ratio to aboveground biomass and LAI of dwarf birch. Results showed that dwarf birch intercepted a significant portion of incoming rainfall in the watershed, highlighting the importance of shrub rainfall interception for regional water balance. These findings demonstrate the untapped potential of L-band SAR observations for quantifying the impact of shrub expansion on Arctic ecosystem processes.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Mohamed Abdelkader, Marouane Temimi, Andreas Colliander, Michael H. Cosh, Vicky R. Kelly, Tarendra Lakhankar, Ali Fares
Summary: This study assessed the temporal variability of SMAP soil moisture retrievals throughout the seasons using in-situ soil moisture observations. The results indicated that SMAP retrievals showed different performance levels in different seasons, with the highest accuracy in September and lower accuracy in March to June. Further enhancement of SMAP retrieval over forest sites is needed based on the findings.
Article
Environmental Sciences
John C. Hammond, Caelan Simeone, Jory S. Hecht, Glenn A. Hodgkins, Melissa Lombard, Greg McCabe, Dave Wolock, Michael Wieczorek, Carolyn Olson, Todd Caldwell, Rob Dudley, Adam N. Price
Summary: Understanding the spatiotemporal patterns of streamflow droughts is crucial for managing future water resources. The study found that drought duration and deficit have increased in the southern and western regions of the US, which may intensify the impact on water availability.
WATER RESOURCES RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Yonghong Yi, Kazem Bakian-Dogaheh, Mahta Moghaddam, Umakant Mishra, John S. Kimball
Summary: Surface soil organic carbon (SOC) content plays a crucial role in the thawing of Arctic permafrost. However, current SOC estimates in the Arctic tundra show a large discrepancy due to limited measurements. This study explores the potential of multitemporal Sentinel-1 C-band SAR data for mapping SOC in the Arctic tundra using principal component analysis (PCA). The results show that the first principal component (PC1) of radar backscatter time series is strongly correlated with surface SOC concentration and bulk density, suggesting the effectiveness of satellite-based methods for Arctic SOC mapping.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Dileep Kumar Gupta, Prashant K. Srivastava, Dharmendra Kumar Pandey, Sumit Kumar Chaudhary, Rajendra Prasad, Peggy E. O'Neill
Summary: The present study aims to parameterize the single channel soil moisture active passive (SMAP) passive soil moisture (SM) retrieval algorithm for Indian conditions. MODIS data products and soil texture data were used to improve the parameterization of the algorithm. The algorithm was calibrated using vegetation and roughness parameters to minimize the error between the model retrieved and ground measured SM. The performance of the new parameterized model was evaluated and compared with other SM products, showing significant improvements.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Computer Science, Interdisciplinary Applications
Yuan Fang, Kazem Bakian-Dogaheh, Mahta Moghaddam
Summary: In this paper, a new variational Born iterative method (VBIM) is proposed for real-time microwave imaging (MWI) applications. The S-parameter volume integral equation and waveport vector Green's function are utilized to utilize the measured signal of the MWI system. The VBIM-RIS method requires less computational time and implements the graphics processing unit based acceleration technique for real-time imaging.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Article
Multidisciplinary Sciences
Todd G. Caldwell, Michael H. Cosh, Steven R. Evett, Nathan Edwards, Heather Hofman, Bradley G. Illston, Tilden Meyers, Marina Skumanich, Kent Sutcliffe
Summary: Soil moisture has a direct impact on operational hydrology, food security, ecosystem services, and the climate system. However, its adoption has been slow due to inconsistent data collection and poor standardization. This paper attempts to establish a community-based standard of practice for in situ soil moisture sensors to provide consistent guidance for future research and applications.
JOVE-JOURNAL OF VISUALIZED EXPERIMENTS
(2022)
Article
Environmental Sciences
Amer Melebari, James D. Campbell, Erik Hodges, Mahta Moghaddam
Summary: This paper presents improvements to an existing GNSS-R DDM model by accounting for short-wave diffraction due to small-scale ground surface roughness and signal attenuation due to vegetation. The improved model, called IGOT, accurately predicts CYGNSS DDMs at two validation sites and enables retrieval of geophysical parameters such as soil moisture.
Article
Environmental Sciences
Lixin Dong, Shihao Tang, Fuzhou Wang, Michael Cosh, Xianxiang Li, Min Min
Summary: This paper utilizes the thermal infrared data from the FY-4A geostationary meteorological satellite to retrieve hourly land surface temperature (LST) and evaluates seven different algorithms. The Ulivieri (1985) algorithm is determined to be the most optimal for the FY-4A LST official products. Refined coefficients for distinguishing between dry and moist atmospheres are established, and the official LST products are successfully produced under clear-sky conditions. Validation results demonstrate that the preferred algorithm exhibits good accuracy and meets the required precision for the FY-4A mission.
Article
Soil Science
Daniel D. Saurette, Richard J. Heck, Adam W. Gillespie, Aaron A. Berg, Asim Biswas
Summary: Digital soil mapping (DSM) requires georeferenced samples, environmental covariates, and a model. Sample design, particularly the determination of sample size and locations, has often been overlooked. This study evaluated different divergence metrics and normalized variance to determine the optimal sample size for predicting total soil carbon.
Article
Engineering, Electrical & Electronic
Kazem Bakian-Dogaheh, Yuan Fang, Mahta Moghaddam
Summary: This paper presents a new quad-band tapered patch transmit-receive antenna array designed for a multistatic microwave imaging cavity system. The reverberating cube-shaped chamber is filled with a matching fluid emulsion and encompasses 64 antenna elements mounted on its sidewalls (16 per panel). Four resonant frequencies in the range of 0.5-3 GHz are achieved. The design procedure takes into account system constraints and performance requirements, including the near-field nature of the electromagnetic wave and wave propagation into the immersion fluid.
IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS
(2023)
Article
Environmental Sciences
Jacob Mardian, Catherine Champagne, Barrie Bonsal, Aaron Berg
Summary: Drought is a costly natural disaster that affects economies and ecosystems globally. Monitoring and communicating drought impacts are crucial for mitigation, adaptation, and decision-making. This research presents a machine learning framework to predict and understand the Canadian Drought Monitor. The framework demonstrates the potential to effectively monitor drought impacts without constant ground support and provides valuable insights through the SHAP variable importance metric.
WATER RESOURCES RESEARCH
(2023)
Article
Geochemistry & Geophysics
Erik Hodges, James D. Campbell, Amer Melebari, Alexandra Bringer, Joel T. Johnson, Mahta Moghaddam
Summary: Lidar elevation maps are compared with results generated using SRTM in a scattering model, showing the importance of surface roughness and the shortcomings of using SRTM. High-resolution lidar maps also reveal surface roughness at finer length scales. Improvements are observed when a lidar DEM is used.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
