Remote Sensing of Soils
In recent years, technological improvements in spectral sensing systems, have generated widespread enthusiasm among soil scientists to apply these systems to the observations of soils. The attraction is partly due to the potential for new “proximal” soil sensor designs in support of precision agriculture, but also to the potential to significantly increase the amount of information that can be obtained about soils remotely. However, a practical difficulty this technique faces is that soils in the field, unlike the sieved, repacked soil samples used in the laboratory, are generally moist and have uneven surfaces, especially after tillage. IRIS has played a pivotal role in studying the effects of surface roughness, wetness, particle size and pore space on the relationship between a soil and its corresponding spectra.
Tian, Jia, and William Philpot. 2017. “Directional Optical Transmission through a Sand Layer: A Preliminary Laboratory Experiment.” In Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, edited by Christopher M. Neale and Antonino Maltese, 10421:30. Warsaw, Poland, Poland: SPIE. doi:10.1117/12.2278602.
Philpot, William D., and Jia Tian. 2016. “The Hyperspectral Soil Line: A Preliminary Description.” In Hyperspectral Imaging and Sounding of the Environment (HISE). Vol. Part F22-H. Leipzig, Germany: OSA. doi:https://doi.org/10.1364/HISE.2016.HW3E.2.
Philpot, William D., and Jia Tian. 2016. “Spectral Reflectance of Wet Soils: Implications for Modeling.” In RIT/ASD Symposium. https://www.asdi.com/events/current-applications-new-trends-in-spectroscopy.
Baveye, P. and M. Laba. 2015. Visible and near-infared reflectance spectroscopy is of limited practical use to monitor soil contamination by heavy metals. Journal of Hazardous Materials 285: 137-139.
Baveye, P. and M. Laba. 2015. Moving away from the geostatistical lamppost: Why, where, and how does the spatial heterogeneity of soils matter? Ecological Modelling 298: 24-38.
Tian, Jia, and William D. Philpot. 2015. “Relating Water Absorption Features to Soil Moisture Characteristics.” In Imaging Spectrometry XX, Relating Water Absorption Features to Soil Moisture Characteristics, edited by Thomas S. Pagano and John F. Silny, 9611:96110M. San Diego, CA: SPIE-Int. Soc. Optical Engineering, 1000 20th St, PO Box 10, Beillingham, WA 98227-0010 USA. doi:10.1117/12.2188478.
Baveye, P., D. Rangel, A. R. Jacobson, M. Laba, C. Dernault, W. Otten, R. Radulovich, FAO Camargo. 2011. From dust bowl to dust bowl: Soils are still very much a frontier of science. Soil. Sci. Soc. Am. J. 75(6): 2037-2048.
Philpot, W. D. (2019). The soil line: Moisture-independent soil reflectance spectra. Hyperspectral Imaging and Sounding of the Environment - Proceedings Optical Sensors and Sensing Congress (ES, FTS, HISE, Sensors), paper HTu4. https://doi.org/10.1364/HISE.2019.HTu4C.2
Philpot, W., Jacquemoud, S., & Tian, J. (2021). ND-space: Normalized difference spectral mapping. Remote Sensing of Environment, 264, 112622. https://doi.org/10.1016/j.rse.2021.112622