Boreal forest fires in Russia in 1998 may have covered a much larger area than originally reported and may have been mostly crown fires, releasing more greenhouse gases into the atmosphere than surface fires. These conclusions are based on analysis of Advanced Very High Resolution Radiometer (AVHRR) data and discussions with Russian fire officials. A more complete analysis of AVHRR data collected since 1980 is underway to determine overall fire patterns in Russia's boreal forests. The year 1998 was an extreme fire year throughout the boreal forest regions of both North America and Eurasia. Over 11 million hectares burned. In Alaska and Canada alone, 4.7 million hectares of boreal forests burned in 1998, according to estimates by national fire monitoring systems in those places.
This paper presents two multispectral enhancement techniques for distinguishing between regions of cloud and snow cover using optical spectrum passive radiometer satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). Fundamental to the techniques are the 1.6- and 2.2-μm shortwave infrared bands that are useful in distinguishing between absorbing snow cover (having low reflectance) and less absorbing liquid-phase clouds (higher reflectance). The 1.38-μm band helps to overcome ambiguities that arise in the case of optically thin cirrus. Designed to provide straightforward, stand-alone environmental characterization for operational forecasters (e.g., military weather forecasters in the context of mission planning), these products portray the information that is contained within complex scenes as value-added, readily interpretable imagery at the highest available spatial resolution. Their utility in scene characterization and quality control of digital snow maps is demonstrated.
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.
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