Document Type
Article
Publication Date
5-2024
Abstract
This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to match natural cloud shapes. This model is intended to run quickly, and it can run in about 700 ms per cloud type. This model generates clouds that appear to match large-scale satellite imagery, and it reproduces natural small-scale shapes. This should enable future versions of ASSET to generate scenarios where the same scene is consistently viewed from both GEO and LEO satellites from multiple perspectives.
DOI
10.3390/rs16091622
Source Publication
Remote Sensing
Recommended Citation
Schinder, A. M., Young, S. R., Steward, B. J., Dexter, M., Kondrath, A., Hinton, S., & Davila, R. (2024). Deterministic Global 3D Fractal Cloud Model for Synthetic Scene Generation. Remote Sensing, 16(9), 1622. https://doi.org/10.3390/rs16091622
Included in
Algebraic Geometry Commons, Atmospheric Sciences Commons, Earth Sciences Commons, Longitudinal Data Analysis and Time Series Commons, Optics Commons, Ordinary Differential Equations and Applied Dynamics Commons, Remote Sensing Commons, Statistical Models Commons
Comments
© 2024 by the authors. Licensee MDPI, Basel, Switzerland.
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