The long-term goal of the work described here is to develop and test a general methodology for predicting unmeasured river characteristics using a variety of potentially incomplete remotely sensed data sets. Rather than addressing the problem using various geostatistical techniques to interpolate and extrapolate the remotely sensed data, we are developing two physically based techniques, each o...

We are entering a new era of computing technology, the era of Internet of Things (IoT). An important element for this popularization is the large use of off-the-shelf sensors. Most of those sensors will be deployed by different owners, generally common users, creating what we call the Collaborative IoT. This collaborative IoT helps to increase considerably the amount and availability of collect...

[1] Accurate prediction of snowpack status is important for a range of environmental applications, yet model estimates are typically poor and in situ measurement coverage is inadequate. Moreover, remote sensing estimates are spatially and temporally limited due to complicating effects, including distance to open water, presence of wet snow, and presence of thick snow. However, through assimilat...

A novel methodology is introduced for quantifying the added value of remotely sensed soil moisture products for global land surface modeling applications. The approach is based on the assimilation of soil moisture retrievals into a simple surface water balance model driven by satellite-based precipitation products. Filter increments (i.e., discrete additions or subtractions of water suggested b...

The prime purpose of the research study was to elucidate the potential of remotely sensed data for estimation of water quality parameters (WQPs) in inland and coastal waters. The useful application of remotely sensed data for operational monitoring of water bodies demand for improved algorithms and methodology. The in situ hyperspectral Spectroradiometer data, water quality data and Airborne Im...

Culicoides imicola is the main vector of the bluetongue virus in theMediterranean Basin. Spatial distribution models for this species traditionally employ either climatic data or remotely sensed data, or a combination of both. Until now, however, no studies compared the accuracies of C. imicola distribution models based on climatic versus remote sensing data, even though remotely sensed dataset...

Using remotely sensed satellite products is the most efficient way to monitor global land, water, and forest resource changes, which are believed to be the main factors for understanding global climate change and its impacts. A reliable remotely sensed product should be retrieved quantitatively through models or statistical methods. However, producing global products requires a complex computin...

Passive microwave sensors have many advantages including the ability to directly measured soil moisture at large spatial scales regardless of weather conditions or time of day. However, microwave-sensed soil moisture’s inevitable limitation is that it cannot describe hydrology at the watershed because its retrieved soil moisture scale is too large. Thus, microwave-sensed soil moisture requires ...

During plant defense against bacterial pathogens, the hypersensitive response (HR) functions to restrict pathogen growth and spread. The mechanisms driving this growth restriction are poorly understood. We used a water stress-responsive transcriptional fusion to quantify the water potential sensed by individual Pseudomonas syringae pv. tomato DC3000 cells during infection of Arabidopsis thalian...

Wireless Sensor Networks (WSNs) have been substituting for human senses to make human lives better by monitoring the environ­ ment and providing intelligence. Collected sensor data are used to make decisions as a human does. Therefore, providing trustworthy sensor data is crucial to make correct decisions. However, faulty sensors can give in­ correct information. In addition, since sensors are ...