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Mapping the total phosphorus concentration of biosolid amended surface soils using LANDSAT TM data
Authors:BB Maruthi Sridhar  Robert K Vincent  Alison L Spongberg
Affiliation:a Department of Geology, Bowling Green State University, Bowling Green, OH 43403, United States
b Department of Environmental Sciences, University of Toledo, Toledo, OH 43606, United States
Abstract:Conventional methods for soil sampling and analysis for soil variability in chemical characteristics are too time-consuming and expensive for multi-seasonal monitoring over large-scale areas. Hence, the objectives of this study are: 1) to determine changes in chemical concentrations of soils that are amended with treated sewage sludge; and 2) to determine if LANDSAT TM data can be used to map surface chemical characteristics of such amended soils. For this study, we selected two fields in NW Ohio, designated as F34 and F11, that had been applied with 34 and 11 ton acre− 1 of biosolids, respectively. Soil samples from a total of 70 sampling locations across the two fields were collected one day prior to LANDSAT 5 overpass and were analyzed for several elemental concentrations. The accumulation of Ba, Cd, Cu, S and P were found to be significantly higher in the surface soils of field F34, compared to field F11. Regression equations were established to search for algorithms that could map these five elemental concentrations in the surface soils using six, dark-object-subtracted (DOS) LANDSAT TM bands and the 15 non-reciprocal spectral ratios derived from these six bands for the May 20, 2005, LANDSAT 5 TM image. Phosphorus (P) had the highest R2 adjusted value (67.9%) among all five elements considered, and the resulting algorithm employed only spectral ratios. This model was successfully tested for robustness by applying it to another LANDSAT TM image obtained on June 5, 2005. Our results enabled us to conclude that LANDSAT TM imagery of bare-soil fields can be used to quantify and map the spatial variation of total phosphorous concentration in surface soils. This research has significant implications for identification and mapping of areas with high P, which is important for implementing and monitoring the best phosphorous management practices across the region.
Keywords:Biosolids  Soil  Phosphorus  Remote sensing  LANDSAT  Spectral reflectance
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