The present effort (Phase 3) builds on our previously published prior efforts (Phases 1 and 2), which examined methods of determining the probability of detection and false alarm rates using thermal infrared for buried object detection. Environmental phenomenological effects are often represented in weather forecasts in a relatively coarse, hourly resolution, which introduces concerns such as exclusion or misrepresentation of ephemera or lags in timing when using this data as an input for the Army’s Tactical Assault Kit software system. Additionally, the direct application of observed temperature data with weather model data may not be the best approach because metadata associated with the observations are not included. As a result, there is a need to explore mathematical methods such as Bayesian statistics to incorporate observations into models. To better address this concern, the initial analysis in Phase 2 data is expanded in this report to include (1) multivariate analyses for detecting objects in soil, (2) a moving box analysis of object visibility with alternative methods for converting FLIR radiance values to thermal temperature values, (3) a calibrated thermal model of soil temperature using thermal IR imagery, and (4) a simple classifier method for automating buried object detection.

Controls on the particle size distribution (PSD) of mineral dust emissions remain poorly understood. Under near‐idealized conditions, dust PSDs can appear invariant with wind friction velocity. However, dryland vegetation attenuates surface friction velocities, and soil crusting reduces the supply of loose erodible material and increases surface resistance to abrasion. Under such conditions, variability in saltation bombardment efficiency and intensity could have a large effect on dust PSDs. We present dust emission measurements from vegetated, supply‐limited aeolian systems that indicate the dependence of emission‐flux PSD on wind friction velocity. We find the fine fraction (<5 μm) of dust particles increases with friction velocity. Results suggest models that assume wind‐invariance of the emission‐flux PSD may not be generalizable for crusted soils with vegetation. There is a need for dust models to represent variability in emission‐flux PSDs for land management, air quality, and climate applications across vegetated and sediment supply‐limited drylands.

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