Researchers at the University of Arizona are investigating the potential of remotely sensed data, using aerial video, to enhance existing data sources and therefore to improve traffic management. This research has developed new methods for both data collection and image processing of remotely sensed data. While the use of remotely sensed data to monitor traffic flows is not new, this research i...

a r t i c l e i n f o Keywords: Band 4 Foliage-height diversity Horizontal vegetation structure Image texture Infrared air photo Landsat NDVI Wildlife habitat Ecologists commonly collect data on vegetation structure, which is an important attribute for characterizing habitat. However, measuring vegetation structure across large areas is logistically difficult. Our goal was to evaluate the degre...

We present the design of and performance results for an image database system for remotely sensed imagery. The system stores and serves level 1B remotely sensed data, providing users with a exible and eecient means for specifying and obtaining image-like products on either a global or a local scale. We have developed both parallel and sequential versions of the system; the parallel version uses...

Different models driven by remotely sensed vegetation indexes (VIs) and incident photosynthetically active radiation (PAR) were developed to estimate gross primary production (GPP) in a subalpine grassland equipped with an eddy covariance flux tower. Hyperspectral reflectance was collected using an automatic system designed for high temporal frequency acquisitions for three consecutive years, i...

Satellite technology produces data at an enormous rate. Most of the database research on the analysis of remotely sensed images concentrated on data retrieval and simple queries that involved spatial joins and spatial selections. For example, the Sequoia 2000 project [13] aimed at the retrieval of raster data, while the Sloan Digital Sky Survey [14] poses the need for the creation of multiterab...

We present the design of and performance results for an image database system for remotely sensed imagery. The system stores and serves level 1B remotely sensed data, providing users with a exible and e cient means for specifying and obtaining image-like products on either a global or a local scale. We have developed both parallel and sequential versions of the system; the parallel version uses...

Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we...

Remote sensing can provide estimates of spatially distributed actual evapotranspiration (ET) at different spatial scales. Methods that combine remotely sensed observations with other ground-based information on land and atmospheric properties usually allow improved estimates of spatially distributed evapotranspiration (ET) than when remotely sensed data are used alone. Spatial resolution of rem...