相关论文: Sensitivity-Informed Parameter Selection for Impro…
Radio experiments trying to detect the global $21$~cm signal from the early Universe are very sensitive to the electrical properties of their environment. For ground-based experiments with the antenna above the soil it is critical to…
High quality Quantitative Precipitation Estimation at high spatiotemporal resolution is crucial to many hydrologic/hydro-meteorological designs. Optimal Quantitative Precipitation Estimation of rainfall improves the accuracy of river and…
Remote sensing (RS) technique, enabling the non-contact acquisition of extensive ground observations, is a valuable tool for crop yield predictions. Traditional process-based models struggle to incorporate large volumes of RS data, and most…
Utilizing the information in observations of a complex system to make accurate predictions through a quantitative model when observations are completed at time $T$, requires an accurate estimate of the full state of the model at time $T$.…
Reducing soil salinization of croplands with optimized irrigation and water management is essential to achieve land degradation neutralization. The effectiveness and sustainability of various irrigation and water management measures to…
Proximal gamma-ray spectroscopy supported by adequate calibration and correction for growing biomass is an effective field scale technique for a continuous monitoring of top soil water content dynamics to be potentially employed as a…
We present a sensing system that determines soil moisture via RF using backscatter tags paired with a commodity ultra-wideband RF transceiver. Despite decades of research confirming the benefits, soil moisture sensors are still not widely…
Microclimate models are essential for linking climate to ecological processes, yet most physically based frameworks estimate temperature independently for each spatial unit and rely on simplified representations of lateral heat exchange. As…
With growing concern for the depletion of soil resources, conventional soil data must be updated to support spatially explicit human-landscape models. Three US soil point datasetswere combined with a stack of over 200 environmental datasets…
The estimation of spatiotemporal data from limited sensor measurements is a required task across many scientific disciplines. The sensor selection problem, which aims to optimize the placement of sensors, leverages innovations in greedy…
Soil thermal conductivity is an important physical parameter in modeling land surface processes. Previous studies on evaluations of parameterization schemes of soil thermal conductivity are mostly based on specific experimental conditions…
Precision agriculture system is an arising idea that refers to overseeing farms utilizing current information and communication technologies to improve the quantity and quality of yields while advancing the human work required. The…
In this work we propose a software platform for the collection, visualization, management and analysis of heterogeneous and multisource data for soil characteristics estimation. The platform is designed in such a way that it can easily…
An analytical solution of the nonlinear Richards equation is presented, for one-dimensional infiltration into a soil of uniform initial moisture content subject to a constant depth of surface ponded water. Adopted mathematical forms of the…
This paper discusses the performance of electrical spectroscopy using a RESPER probe to measure the salinity s and volumetric content {\theta}W of the water in concrete or terrestrial soil. The RESPER probe is an induction device for…
Given the growing environmental challenges, accurate monitoring and prediction of changes in water bodies are essential for sustainable management and conservation. The Continuous Monitoring of Land Disturbance (COLD) algorithm provides a…
Many remote sensing applications employ masking of pixels in satellite imagery for subsequent measurements. For example, estimating water quality variables, such as Suspended Sediment Concentration (SSC) requires isolating pixels depicting…
We developed a method to infer the calibration parameters of multichannel measurement systems, such as channel variations of sensitivity and noise amplitude, from experimental data. We regard such uncertainties of the calibration parameters…
We study the robustness of system estimation to parametric perturbations in system dynamics and initial conditions. We define the problem of sensitivity-based parametric uncertainty quantification in dynamical system estimation. The main…
In this paper, we first propose a coupled numerical model of unsaturated flow in soils and plant root water uptake. The Richards equation and different formulations are used in the developed numerical model to describe infiltration in root…