Bill Philpot

Biography

Engineering was not an initial career choice. My first degree was a B.A. in Music from New York University in 1969. While an undergraduate I was performing professionally in and around NY City with a wide variety of musical groups, fully expecting to continue with music as a career. After graduation, two years in the Army, and a more objective look at my abilities and interests, I returned to school with a different perspective and altered goals, obtaining a B.S. degree in Physics from the State University of New York at Stony Brook. Continuing on to graduate school in oceanography, specializing in ocean optics and remote sensing, I obtained M.S. (1987) and Ph.D. degrees (1981) in Marine Studies at the University of Delaware. Upon graduation I was delighted to join the faculty of the Department of Civil and Environmental Engineering at Cornell University, where I have conducted research in remote sensing that has involved a broad range of applications of remote sensing - from ocean optics to vegetation monitoring to beach trafficability, and most recently in characterization of soil. Sabbatical leaves in academia (RIT, University of Southern Mississippi), industry (WRI) and government (NASA, Naval Research Laboratory) have resulted in a broad perspective and knowledge base in remote sensing and radiative transfer while broadening my contact base. I continue to conduct research in a variety of aspects of remote sensing and teaches courses in Remote Sensing and Digital Image Processing.

Research Interests

My research deals with remote sensing of the earth, focusing on mathematical modeling of the physical interactions of light with the earth's atmosphere and surface, and the way those interactions affect the view of the earth and water as seen from satellite. Rather than being primarily concerned with the cultural or geographic patterns displayed in an image, my focus has been on the spectral and spatial patterns at the pixel level and what that implies about the earth's surface and the intervening atmosphere. For example, in my early career the emphasis was on problems related to sensing of water properties in the coastal zone (bathymetry, water quality, bottom type, etc.) That required an understanding the optical properties of the water, the bottom, and any materials suspended in the water column, and led to modeling how all of those properties affect the observed reflectance of the water. In recent years I have been drawn to more land- and atmosphere-based problems, although still with a primary focus on radiative transfer/physical interaction. Most recently, I have been involved in modeling reflectance from soils as they change from saturated to air-dry, with the intent of relating the spectral reflectance to the both the amount and distribution (i.e., pore water, adsorbed water, surface water) of water in the soil, and the effects of the particle size distribution and bulk density of the soil sample. As with the ocean applications, this involves understanding the optical properties (scattering and absorption) of soils in order to more effectively make remote measurements. The goal is to retrieve details related to the compositional and mechanical properties of the soil, as well as the water content. Another aspect of my research has been in the analysis of digital imagery and LIDAR data. Data analysis in this case encompasses topics ranging from geometric and radiometric correction to spatial and spectral pattern recognition and includes general processes as well as specific applications. In image processing the emphasis is on spectral data retrieval and modeling of the spectral-directional reflectance of the earth's surface. For lidar, the emphasis has been on the characterization and interpretation of full waveform lidar, with particular emphasis on the interplay of a bathy metric lidar pulse with different materials on the ocean bottom. Regardless of the sensing system or specific application, the overall goal is to understand the interaction of light with the earth surface in order to improve the interpretation of the remote signal.

• Remote Sensing
• Image Analysis
• Signal and Image Processing