Article
Environmental Sciences
Susan C. Steele-Dunne, Sebastian Hahn, Wolfgang Wagner, Mariette Vreugdenhil
Summary: The study utilized a kernel smoother to estimate coefficients for soil moisture retrieval, distinguishing between their use for backscatter normalization and vegetation correction. Results showed that using the kernel smoother can improve uncertainty caused by interannual variability in vegetation.
Article
Environmental Sciences
Seung-Bum Kim, Tien-Hao Liao
Summary: Surface soil moisture can be accurately estimated by inverting physical scattering models for low-crops using L-band airborne SAR data, with high robustness and applicability across different incidence angle ranges.
REMOTE SENSING OF ENVIRONMENT
(2021)
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, Civil
Peng Bai, Changxin Cai
Summary: Remotely sensed evapotranspiration (ET) models are commonly used to estimate ET over large areas, but one challenge is the lack of reliable soil moisture (SM) constraints. In this study, five proxy algorithms for SM constraints were evaluated in China, and it was found that the fdrying algorithm performed the best at flux sites.
JOURNAL OF HYDROLOGY
(2023)
Article
Geochemistry & Geophysics
Philipp L. Bykov, Vladimir A. Gordin, Lydia L. Tarasova, Evgenii V. Vasilenko
Summary: This study proposes a combined objective analysis method for available water content based on measurements from agrometeorological stations and remote sensing data. Two neural networks are used for analysis, and optimal interpolation is used for assimilation of ground-based data.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Multidisciplinary Sciences
Majid Amiri, Mehran Abolhasan, Negin Shariati, Justin Lipman
Summary: This paper introduces a soil moisture sensor based on metamaterial perfect absorber, which achieves high accuracy and continuous detection of soil moisture by designing high-precision and low-profile radio frequency passive sensors. High resolution sensing is achieved through the creation of physical channels in the substrate integrated waveguide cavity, and accurate detection of water content is achieved by correlating with the percentage of water content in the three absorption bands.
SCIENTIFIC REPORTS
(2021)
Article
Environmental Sciences
Wanshu Nie, Sujay Kumar, Rajat Bindlish, Pang-Wei Liu, Shugong Wang
Summary: This study demonstrates the potential of using remotely sensed vegetation and soil moisture observations to constrain irrigation estimation, improving the accuracy of model parameterization and understanding of the spatial patterns of irrigation impact. This has significant implications for water management in data-sparse regions.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Geochemistry & Geophysics
Pinjun Tang, Rong Zhao, Jianjun Zhu, Qinghua Xie, Jun Hu
Summary: This letter extends a method proposed by Kweon et al. to retrieve soil moisture by using neighborhood pixels of single-polarization SAR data. The results demonstrate that the proposed method has acceptable accuracy and high resolution.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Hanne Haugen, Olivier Devineau, Jan Heggenes, Kjartan Ostbye, Arne Linlokken
Summary: This study examines the prediction of ground vegetation cover, soil moisture, and pH using remote sensing data, proposing that causal models can improve prediction accuracy and transferability while recommending to focus on causally related variables and include additional variables for testing in quality control studies.
Article
Environmental Sciences
Veena Shashikant, Abdul Rashid Mohamed Shariff, Aimrun Wayayok, Md Rowshon Kamal, Yang Ping Lee, Wataru Takeuchi
Summary: The study evaluated the sensitivity of SAR signals to oil palm crops using synthetic aperture radar (SAR) and in-situ observations. The results showed that HV polarization effectively simulated backscatter coefficient as compared to HH polarization with the best fit obtained by taking the LAI as a vegetation descriptor. HV polarization with the LAI indicator was able to retrieve soil moisture content with an accuracy of at least 80%.
Article
Environmental Sciences
Yinglan A, Guoqiang Wang, Peng Hu, Xiaoying Lai, Baolin Xue, Qingqing Fang
Summary: Root-zone soil moisture is a crucial factor in eco-hydrological processes. In this study, the ConvLSTM model, combined with remote sensing-based variables, was used to estimate root-zone soil moisture. The model showed significantly higher fitting coefficients compared to existing products, especially for deep layers.
ENVIRONMENTAL RESEARCH
(2022)
Article
Agronomy
Hao Sun, Jinhua Gao
Summary: Soil evaporative efficiency (SEE) is estimated by the relative difference between soil temperature (Ts) and its maximum (Ts(max)) and minimum (Ts(min)) values at 'minimum and maximum' soil moisture (SM). This thermal indicator of SM has been proven effective in downscaling satellite microwave SM in some local areas. However, the determination of Ts(max) and Ts(min) is usually empirical, limiting its wider application.
AGRICULTURAL WATER MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Caixia Su, Yongfeng Cao
Summary: This study used SAR data to study soil moisture in Karst area and successfully inverted soil moisture using different models based on factors such as rocky desertification degree and vegetation. The proposed method accurately inverts soil moisture and provides powerful technical support for the Karst area.
Review
Environmental Sciences
Yuxuan Wang, Hongli Zhao, Jinghui Fan, Chuan Wang, Xinyang Ji, Dingjian Jin, Jianping Chen
Summary: Soil moisture plays a crucial role in agricultural production, eco-environmental protection, water and land resources management, etc. Remote sensing data and mathematical models are the main research methods for monitoring and retrieving soil moisture, but the interference from surface and soil parameters as well as vegetated areas needs to be addressed.
Article
Geosciences, Multidisciplinary
Zhao-Liang Li, Pei Leng, Chenghu Zhou, Kun-Shan Chen, Fang-Cheng Zhou, Guo-Fei Shang
Summary: Soil moisture is a crucial parameter for understanding the interactions between atmosphere and Earth's surface, and its spatiotemporal distribution has long been a challenge in remote sensing. Recent advancements in theories and algorithms for soil moisture retrieval need to be critically reviewed to address the existing issues and scientific challenges.
EARTH-SCIENCE REVIEWS
(2021)
Article
Engineering, Aerospace
Akshar Tripathi, Reet Kamal Tiwari
Summary: This study utilizes SAR data from the Sentinel-1A satellite to estimate Soil Organic Carbon (SOC), and compares the performances of two regression models in agricultural areas of India. The results show that the combination of backscatter from VV and VH polarization channels with field data can provide a good estimation of SOC.
ADVANCES IN SPACE RESEARCH
(2022)
Article
Environmental Sciences
Md. Abdullah Aziz, Md. Moniruzzaman, Akshar Tripathi, Md. Ismail Hossain, Saleh Ahmed, Khan Rubayet Rahaman, Farhana Rahman, Rokib Ahmed
Summary: Delineating a flood map is crucial in Bangladesh to understand the potential risks for diverse communities living in urban and rural areas. Satellite remote sensing and GIS techniques are commonly used, but challenges arise due to cloud cover during the monsoon season. The use of active synthetic aperture radar sensors is recommended to overcome this issue and accurately map the inundated areas.
EARTH SYSTEMS AND ENVIRONMENT
(2022)
Article
Environmental Sciences
Kavita V. Mitkari, Manoj K. Arora, Reet Kamal Tiwari, Sanjeev Sofat, Hemendra S. Gusain, Surya Prakash Tiwari
Summary: This paper presents a method for large-scale glacier cover mapping using remote sensing imagery and OBIA, which can efficiently classify multiple glacier cover classes and accurately map important geomorphological features.
Article
Engineering, Geological
Ankit Tyagi, Reet Kamal Tiwari, Naveen James
Summary: The change in land-use and land-cover significantly affects the landslide susceptibility, but prediction using these changes has not been quantified. This study aims to predict the future landslide susceptibility map in the Tehri region, India, considering future land-use and land-cover change scenarios. The results reveal an increase in built-up area, water body, and agriculture land, a decrease in forest area, and an increase in very high landslide susceptibility zone.
Article
Environmental Sciences
Sartajvir Singh, Reet Kamal Tiwari, Vishakha Sood, Ravneet Kaur, Simrandeep Singh, Shivendu Prashar
Summary: In this study, the scatterometer satellite (SCATSAT-1) was used to estimate and validate the near-real-time snow cover area (SCA) in the Western Himalayas, India. The experimental results showed the potential of SCATSAT-1 in estimating SCA and suggested the use of different MODIS products for reference and validation in different scenarios. The findings indicated that SCATSAT-1 can provide near-real-time mapping and monitoring of large-scale snow extent globally, even under cloudy conditions.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
Arjuman Rafiq Reshi, Md Moniruzzaman, Akshar Tripathi, Reet Kamal Tiwari, Khan Rubayet Rahaman
Summary: During the lockdown in India, the concentration of O-3 pollutant in the atmosphere significantly increased despite the reduction of emissions from other sources. This study demonstrates that the concentration of O-3 gas is influenced by various factors, and combining Sentinel-5P satellite data with ground-based sensor data can provide accurate estimation of O-3 concentrations.
GEOCARTO INTERNATIONAL
(2022)
Article
Green & Sustainable Science & Technology
Md Moniruzzaman, Md Sorof Uddin, Md Abdullah Elias Akhter, Akshar Tripathi, Khan Rubayet Rahaman
Summary: This study evaluates the maturity timeline of several commercial mango varieties in Bangladesh, considering their variations in geographic locations and climatic conditions. The findings indicate that locational variations can result in delays in mango harvesting. This study can contribute to the appropriate planning of mango production and commercialization for a sustainable harvest and production system.
Article
Engineering, Civil
Mohit Kumar, Reet Kamal Tiwari, Kamal Kumar, Kuldeep Singh Rautela
Summary: In this study, a statistical analysis of MODIS snow time series data and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model were applied to accurately measure cyclic snow accumulation and depletion in the Beas river basin in the Himalayan region from 2003 to 2018. The Box-Jenkins methodology was used to forecast snow accumulation and depletion based on seasonality, stationarity, ACF, and PACF plots, as well as maximum likelihood estimation and diagnostic checking. The forecasting models for snow accumulation period (October-February) and snow depletion period (March-September) showed good agreement with observed data, with R-2 values of 0.83 and 0.89, respectively. This research highlights the potential of using satellite data and statistical modeling for monitoring snow cover in remote and inaccessible regions.
AQUA-WATER INFRASTRUCTURE ECOSYSTEMS AND SOCIETY
(2023)
Article
Engineering, Geological
Ankit Tyagi, Reet Kamal Tiwari, Naveen James
Summary: The study predicts future landslide susceptibility for the year 2050 by considering both dynamic and static factors. The results indicate that changes in land use and climate variables will increase landslide susceptibility in the future.
Article
Environmental Sciences
Arjuman Rafiq Reshi, Har Amrit Singh Sandhu, Claudia Cherubini, Akshar Tripathi
Summary: This study utilizes satellite data from PSInSAR and GRACE to understand land subsidence in the Chandigarh tri-city region. With a coarse spatial resolution of 1o by 1o, challenges arise in correlating GRACE data with PSInSAR displacement. Therefore, a DLMLP model is used along with multiple data sources to estimate groundwater storage change at the urban level. The DLMLP model achieves an R-2-statistics value of 0.91 and 0.89 in the training and testing phases, respectively, with a mean absolute error of 1.23 and root mean square error of 0.87.
Article
Geosciences, Multidisciplinary
Ravneet Kaur, Reet Kamal Tiwari, Raman Maini, Sartajvir Singh
Summary: Crop yield prediction is crucial for decision-making in sustainable agriculture. This study proposes a machine learning-based framework utilizing optical and microwave satellite data to generate enhanced-resolution soil moisture products. The framework incorporates image fusion, artificial neural networks, and post-classification-based change detection to generate thematic and change maps. Results show that the proposed framework outperforms other methods in calculating change maps. This study is important for crop yield prediction analysis by providing enhanced-resolution soil moisture products under different weather conditions.
Article
Engineering, Environmental
Ankit Tyagi, Reet Kamal Tiwari, Naveen James
Summary: This study presents a scientific method to identify the most significant landslide-causing parameters for an enhanced LSM analysis, and proposes a LSM model for the Himalayan region to improve landslide prediction accuracy.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2023)
Article
Environmental Sciences
Akshar Tripathi, Kapil Malik, Arjuman Rafiq Reshi, Md Moniruzzaman, Reet Kamal Tiwari
Summary: With the discovery of crude oil and natural gas reserves, the surface subsidence in the Krishna Godavari basin in India has increased. Regular monitoring of the surface subsidence is necessary for timely remedial measures. This study uses multi-temporal SAR interferometry and radar vegetation index to estimate the surface subsidence and vegetation loss in the region. The results show an annual surface subsidence of 80 mm and a loss of 3.21 km2 of cultivable land between 2020 and 2022.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2023)
Article
Environmental Sciences
Supratim Guha, Reet Kamal Tiwari
Summary: Glacier response patterns at the catchment scale in the Sikkim Himalayan region are influenced by various factors, with the terminus type and mean elevation of the glaciers significantly impacting glacier mass balance. The model using these two factors explains 76% of the fluctuation in mass balance. The study also found that lake-terminating glaciers experience approximately 0.40 m.w.e.a(-1) higher mass loss compared to land-terminating glaciers in the same elevation zone, while a thousand meters mean elevation drop is associated with 0.179 m.w.e.a(-1) of mass loss regardless of terminus type.
JOURNAL OF MOUNTAIN SCIENCE
(2023)
