Virtual remote sensing: a holistic modeling approach

The plethora of new satellites that collect vast amounts of imagery in specific bands and multiple view angles has given rise to the enormous task of managing and storing large quantities of data and also to extract meaningful information from it. Efforts are underway to develop methodologies that will query the images by content, provide efficient visualization and perform data mining. While the continuation of deploying such state of the art satellites in the future weighs heavily on the logistics of the space agencies, the user community will be in a quandary to look for data that will enable them to test algorithms and methodologies. This paper describes the development of a virtual remote sensing paradigm of simulating atmosphere, scene, and sensor parameters. This is achieved by the modification of existing models available in these areas and coupling them in a software environment developed in Interactive Data Language (IDL). A graphical user interface enables the user to interactively select different land cover types (e.g. water bodies, agricultural fields, soils etc) from a predefined menu and create a virtual scene. A scene is defined by determining its size x columns by y rows, where each location (x, y) is a square scene cell determined by the resolution corresponding to the sensor selected by the user and is assigned to one of the different land cover classes. A Radiative transfer code, Streamer, has been used to model the atmospheric effects. A number of available kernel models have been incorporated in the software to determine bidirectional reflectance corresponding to a given surface type. Field collected BRDF data by a goniometer has been used to perform model inversion and obtain the model parameters.