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High Resolution Hydric Soil Mapping using LiDAR Digital Terrain Modeling
Author(s) -
Fink Cody M.,
Drohan Patrick J.
Publication year - 2016
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2015.07.0270
Subject(s) - hydric soil , lidar , soil water , digital elevation model , terrain , environmental science , soil science , hydrology (agriculture) , soil map , remote sensing , geology , geography , geotechnical engineering , cartography
Core Ideas Logistic regression model developed to predict hydric soil presence. LiDAR DEM performed better than 10‐m USGS DEM. Model performed better at predicting non‐hydric soils compared with hydric soils. The recent availability of 1‐m laser imaging, detection, and ranging (LiDAR) data in Pennsylvania provides a high resolution digital elevation model (DEM) which could improve on existing USDA‐NRCS Order 2 soil survey mapping. The ability of LiDAR derived terrain indices to predict hydric soil presence was evaluated across the Northern Appalachians. We developed a logistic regression model to predict hydric soil presence using a dataset of 1153‐field data points and several terrain indices derived from LiDAR DEMs. The best performing regression model included slope derived from a 1‐m LiDAR DEM, depressions derived from a 5‐m LiDAR DEM, and physiographic region. This model was able to successfully predict 67% of hydric soils and 73% of non‐hydric soils from a validation dataset. The model performed better at predicting non‐hydric soils compared with hydric soils and was not as effective in low slope areas. This suggests that the 1‐m LiDAR hydrologic variables used in the study cannot completely account for soil hydric status.