[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...

Digital classification methods of remotely sensed images have acquired a growing importance in the automatic recognition of the land cover patterns. The enormous quantity of images that are being generated from an increasing number of highly sophisticated sensor systems require the development of innovative classification methodologies, which allow an automatic and efficient detection of the gr...

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...

being very dynamic, natural and artificial land features are changing somewhat rapidly in over lifetime. it is important that such changes be inventoried accurately so that the physical and human processes at work can be more fully understood. change detection is a technique used in remote sensing to determine the changes in a particular object of study between two or more time periods. this re...

Traditional spectral classi®cation of remotely sensed images applied on a pixel-by-pixel basis ignores the potentially useful spatial information between the values of proximate pixels. For some 30 years the spatial information inherent in remotely sensed images has been employed, albeit by a limited number of researchers, to enhance spectral classi®cation. This has been achieved primarily by ®...

The emergence of force feedback haptic devices that can remotely interact with virtual environments presents a number of challenges to the underlying networks that have to support their interactions. One important issue concerns the characterisation of haptic traffic, particularly whenever multiple users remotely interact over a network such as the Internet. Previous research has characterised ...

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...