The long-wave infrared reflectance of in situ disturbed and undisturbed soils will often have distinct spectral characteristics that are dependent on the soil's physical and spectral constitutive properties. This study examines how rainfall alters the measured directional-hemispherical thermal infrared (8-14 μm) spectral reflectance of a disturbed soil with a specified sand/silt ratio using a calibrated rainfall simulator. For an accumulated rainfall of 8.0 cm, the mean disturbed soil thermal infrared spectral reflectance within 8.1-9.2-μm waveband increases from an initial reflectance of 13% to a maximum reflectance of 31%. Sixty percent of this reflectance change occurred with only 1.0-cm accumulated rainfall. This study shows that, for this described disturbed sand/silt soil mixture, small accumulated rainfall amounts significantly alter the directional-hemispherical thermal infrared spectral reflectance.Index Terms-Disturbed soil, long-wave infrared (LWIR) soil reflectance, rainfall.

In this paper, we present our first results towards understanding high temporal frequency thermal infrared response from a dense grass canopy. The model is driven by slowly varying, time-averaged meteorological conditions and by high frequency measurements of local and within canopy profiles of relative humidity and wind speed, and compared to high frequency thermal infrared observations. Previously, we have employed three-dimensional ray tracing to compute the intercepted and scattered solar and IR radiation fluxes and for final scene rendering. For the turbulent fluxes, simple resistance models for latent and sensible heat with one-dimensional profiles of relative humidity and wind speed are used. Our modeling approach has proven successful in capturing the directional and diurnal variation in background thermal infrared signatures. We hypothesize that at these scales, where the model is typically driven by time-averaged, local meteorological conditions, the primary source of thermal variance arises from the spatial distribution of sunlit and shaded foliage elements within the canopy and the associated radiative interactions.In recent experiments, we have begun to focus on the high temporal frequency response of plant canopies in the thermal infrared at 1 sec to 5 min intervals. At these scales, we hypothesize turbulent mixing plays a more dominant role. Our results indicate that in the high frequency domain, the vertical profile of temperature change is tightly coupled to the within canopy wind speed. In the results reported here, the canopy cools from the top down with increased wind velocities and heats from the bottom up at low wind velocities.

Finding explosive threats in complex environments is a challenge. Benign objects (e.g. rocks, plants and rubbish), ground surface variation, heterogeneous soil properties and even shadows can create anomalies in remotely sensed imagery, often triggering false alarms. The overarching goal is to dissect these complex sensor images to extract clues for reducing false alarms and improve threat detection. Of particular interest is the effect of soil properties, particularly hydrogeological properties, on physical temperatures at the ground surface and the signatures they produce in infrared imagery. Hydrogeological variability must be considered at the scale of the sensor's image pixels, which may be only a few centimetres. To facilitate a deeper understanding of the components of the energy distribution, a computational testbed was developed to produce realistic, process-correct, synthetic imagery from remote sensors operating in the visible and infrared portions of the electromagnetic spectrum. This tool is being used to explore near-surface process interaction at a fine scale to isolate and quantify the phenomena behind the detection physics. The computational tools have confirmed the importance of hydrogeology in the exploitation of sensor imagery for threat detection. However, before this tool's potential becomes a reality, several technical and organizational problems must be overcome.