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Ionic and isotopic ratios for identification of salinity sources and missing data in the Gaza aquifer
Groundwater is the only source of fresh water in the Gaza Strip. However, it is severely polluted and requires immediate effort to improve its quality and increase its usable quantity. IntensiveExpand
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Multiobjective particle swarm optimization for parameter estimation in hydrology
[1] Modeling of complex hydrologic processes has resulted in models that themselves exhibit a high degree of complexity and that require the determination of various parameters through calibration.Expand
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Applicability of statistical learning algorithms in groundwater quality modeling
[1] Four algorithms are outlined, each of which has interesting features for predicting contaminant levels in groundwater. Artificial neural networks (ANN), support vector machines (SVM), locallyExpand
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Multi-time scale stream flow predictions: The support vector machines approach
TLDR
We present new data-driven models based on Statistical Learning Theory that were used to forecast flows at two time scales: seasonal flow volumes and hourly stream flows. Expand
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Estimating chlorophyll with thermal and broadband multispectral high resolution imagery from an unmanned aerial system using relevance vector machines for precision agriculture
TLDR
A relevance vector machine with a thin plate spline kernel type and kernel width of 5.4, having LAI, NDVI, thermal and red bands as the selected set of inputs, can be used to spatially estimate chlorophyll concentration from remotely sensed data at 15-cm resolution. Expand
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Band-reconfigurable Multi-UAV-based Cooperative Remote Sensing for Real-time Water Management and Distributed Irrigation Control
Abstract This paper presents an overview of ongoing research on small unmanned autonomous vehicles (UAVs) for cooperative remote sensing for real-time water management and irrigation control. SmallExpand
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Downscaling and Forecasting of Evapotranspiration Using a Synthetic Model of Wavelets and Support Vector Machines
TLDR
This paper presents an algorithm that provides a means to downscale and forecast dependent variables such as ET images. Expand
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Soil Moisture Prediction Using Support Vector Machines
ABSTRACT: Herein, a recently developed methodology, Support Vector Machines (SVMs), is presented and applied to the challenge of soil moisture prediction. Support Vector Machines are derived fromExpand
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Assessment of Surface Soil Moisture Using High-Resolution Multi-Spectral Imagery and Artificial Neural Networks
TLDR
An artificial neural network (ANN) model was developed to quantify the effectiveness of using spectral images to estimate surface soil moisture using remotely sensed data at such a fine spatial resolution and readily available temporal resolution. Expand
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Low-cost UAV-based thermal infrared remote sensing: Platform, calibration and applications
TLDR
We introduce AggieAir-TIR, a small, low-cost, flexible TIR remote sensing platform, which was accomplished at the Center for Self Organizing and Intelligent Systems (CSOIS). Expand
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