Abstract
A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.
Highlights
The simulation of image collection for airborne and satellite sensors has many applications
The simulated cloud fields were compared to observed cloud occurrence from the Active Remote Sensing of Clouds (ARSCL) product [28], which is based on vertically pointing radar and lidar at the Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) site
The larger difference at upper levels suggest that the quality of the simulation could be improved by better large-scale forcing and ice microphysics, which are responsible for the cloud generation at the upper levels
Summary
The simulation of image collection for airborne and satellite sensors has many applications. Simulated video and image products make it possible to measure the value of potential imagery collections before they are carried out. Accurate simulations can help mission planners use collection platforms more efficiently, safely, and effectively, and predict the detection and visibility of targets and other scene features under anticipated collection conditions [1,2]. Simulation is useful for prototyping sensors [3] and for testing algorithms in the imaging chain [4]. Simulation can be used to predict, analyze, and reverse engineer artifacts and system issues that degrade image and video quality. Simulations can generate large quantities of annotated training data for computer vision machine learning systems
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