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ABSTRACT

The digital imaging and remote sensing image generation model is a physics-based image and data simulation model that is primarily used to generate synthetic imagery across the visible to thermal infrared regions using engineering-driven descriptions of remote sensing systems. The model recently went through a major redesign and reimplementation effort to address changes in user requirements and numerical computation trends that have emerged in the 15 years since the last major development effort. The new model architecture adopts some of the latest light transport algorithms matured by the computer graphics community and features a framework that is easily parallelized at the microscale (multithreading) and macroscale (cluster-based computing). A detailed description of the framework is provided, including a novel method for efficiently storing, evaluating, integrating, and sampling spherical and hemispherical datasets appropriate for the representation of modeled or measured bidirectional scattering, reflectance, and transmission distribution functions. The capabilities of the model are then briefly demonstrated and cross-verified with scenarios of interest to the remote sensing community.

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The Landsat Data Continuity Mission (LDCM) focuses on a next generation global coverage, imaging system to replace the aging Landsat 5 and Landsat 7 systems. The major difference in the new system is the migration from the multi-spectral whiskbroom design employed by the previous generation of sensors to modular focal plane, multi-spectral pushbroom architecture. Further complicating the design shift is that the reflective and thermal acquisition capability is split across two instruments spatially separated on the satellite bus. One of the focuses of the science and engineering teams prior to launch is the ability to provide seamless data continuity with the historic Landsat data archive. Specifically, the challenges of registering and calibrating data from the new system so that long-term science studies are minimally impacted by the change in the system design. In order to provide the science and engineering teams with simulated pre-launch data, an effort was undertaken to create a robust end-to-end model of the LDCM system. The modeling environment is intended to be flexible and incorporate measured data from the actual system components as they were completed and integrated. The output of the modeling environment needs to include not only radiometrically robust imagery, but also the meta-data necessary to exercise the processing pipeline. This paper describes how the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model has been utilized to model space-based, multi-spectral imaging (MSI) systems in support of systems engineering trade studies. A mechanism to incorporate measured focal plane projections through the forward optics is described. A hierarchal description of the satellite system is presented including the details of how a multiple instrument platform is described and modeled, including the hierarchical management of temporally correlated jitter that allows engineers to explore impacts of different jitter sources on instrument-to-instrument and band-to-band registration. The capabilities of a new, non-imaging instrument to simulate the measurement of platform ephemeris is also introduced. Finally, the geometric and radiometric foundations for modeling clouds in the DIRSIG model will be described and demonstrated as one of the more significant challenges in registering multi-spectral pushbroom sensor data products.

This work describes a visualization tool and sensor testbed that can be used for assessing the performance of both instruments and human observers in support of port and harbor security. Simulation and modeling of littoral environments must take into account the complex interplay of incident light distributions, spatially correlated boundary interfaces, bottom-type variation, and the three-dimensional structure of objects in and out of the water. A general methodology for a two-pass Monte Carlo solution called Photon Mapping has been adopted and developed in the context of littoral hydrologic optics. The resulting tool is an end-to-end technique for simulating spectral radiative transfer in natural waters. A modular design allows arbitrary distributions of optical properties, geometries, and incident radiance to be modeled effectively. This tool has been integrated as part of the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. DIRSIG has an established history in multi and hyperspectral scene simulation of terrain targets ranging from the visible to the thermal infrared (0.380 -20.0 microns). This tool extends its capabilities to the domain of hydrologic optics and can be used to simulate and develop active/passive sensors that could be deployed on either aerial or underwater platforms. Applications of this model as a visualization tool for underwater sensors or divers are also demonstrated.

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