Dr. Scott Nowicki Contact   Home On a planetary scale, there is a lack of information about the spatial distribution and areal extent of surface materials and climatically-generated landforms. For example, we have no idea how much land area currently generates dust due to wind erosion of degraded soil, but even more importantly how much more land is susceptible to dust-generation with a small change in climate. And dust is just one of the components of the system, and dust generation just one of the processes. Paleoclimatic surfaces like desert pavements have been stable and exposed to the atmosphere for over a million years. What is the susceptibility of these surfaces to changes in the hydrologic cycle. Or, alternatively, do these surfaces evolve to buffer the landscape as climate changes? But this is getting into the details and drivers. At the moment, we simply need to quantify the distribution of materials (soil, sediments, rock, dust) alongside vegetation cover. At that point we can start to apply the models of surface processes on a large scale. My research is the further development of what I started with TES and THEMIS data, but now applied to Earth data and processes. It was the combination of a number of complex models (atmospheric radiative transfer, solar thermal cycling, compositional deconvolution) that allowed us to map the distrubution of sediments on Mars from space. I took the spatial distribution of rocks, sand, and dust to interpret what are the most recent processes at work, and how they have changed older surfaces. Using diurnal temperatures to determine the mechanical composition of surface materials and relate these properties to environmental conditions, we are able to build a global 3-D view of the surface, and interpret the history. Earth and Mars are similar enough that the lessons we learned from one can guide the plan for investigating the other. Starting on a regional scale, I am working on generating a map of the planet (Earth) showing the materials and processes, using the same methods we used on Mars. The applications of such a dataset are numerous. A map of surfaces and processes can be used as an input into climate models, determining the scale and potential for feedback mechanisms. Second, in combination with climate models, we can generate a map of regions and surfaces that are likely to cause problems such as what occurred during the 1930's dust bowl, or wide-spread erosion due to drought. The processes and surface characteristics are currenly fairly well-understood, and the climate models are pretty advanced. The big thing that is lacking is the spatial quantification and map of these things. MODIS and ASTER have been collecting data for a number of years now and provide a complete global view of the planet at all the right wavelengths. One problem is that only geological remote sensing magicians can get the information out. Thus, there needs to be a concerted effort to turn the mutispectral data into a GIS-based series of products that modelers, engineers, and economists can actually use. Thanks to the efforts we put into TES and THEMIS, there is a model for how to do this. I am in the process of developing prosals to do just that: 1) refine and apply the thermophysical models to determine surface mechanical composition on Earth; 2) turn these models and observations into geologically interpretable information that is useful for others to use; 3) calibrate, rectify, and mosaic the global ASTER dataset into a useful product; and 4) generate the maps of surface properties and processes that can be directly interpreted and used in GIS' for climate modeling, land management, and disaster mitigation. Science Plan: Development of a comprehensive model of physical properties of natural surfaces as a function of mode of emplacement, envionment, and age. Practical Objectives: 1) To characterize a series of primary (volcanic, depositional) surfaces based on remotely sensed measurements, and quantitatively link these measurements to physical properties and environmental conditions. 2) To characterize of a series of modified (fluvial, mass-wasting, and glacial) surfaces based on remotely-sensed measurements, and quantitatively link these measurements to physical properties and environmental conditions. 3) Development of an empirical model of surface property (thermal conductivity, clast size-frequency distribution, reflectivity, composition, scale-dependent roughness, slope) and bulk property evolution (density, morphometry, clast distribution) as a function of process and time to determine zones of convergence of properties from remote sensing. Page Last Updated: 1/08