Accession Number : AD1014532


Title :   Image Analysis and Classification Based on Soil Strength


Descriptive Note : Technical Report


Corporate Author : Cold Regions Research and Engineering Laboratory, U.S. Army Engineer Research and Development Center Hanover


Personal Author(s) : Sopher,Ariana M ; Shoop,Sally A ; Stanley,Jesse Jr M ; Tracy,Brian T


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/1014532.pdf


Report Date : 01 Aug 2016


Pagination or Media Count : 32


Abstract : Satellite imagery classification is useful for a variety of commonly used applications, such as land use classification, agriculture, wetland delineation, forestry, geology, and landslide potential. However, image classification for physical properties of surface soils, such as strength or bearing capacity, is often obscured by other surface conditions, such as moisture and vegetation, although these are also indicators of soil strength. This project used remote methods of terrain analysis to search for areas suitable for vehicle or aircraft maneuverability based on slope, roughness, vegetation, soil type, and wetness and also performed direct classification of imagery based on soil strength. Using a maximum likelihood supervised classification approach, trained by a limited amount of ground-truth strength measurements, a soil strength classification was applied to WorldView-2 multispectral satellite imagery. This paper presents the work done on the imagery classification for soil strength, the apparent relationship between the reflectance and soil strength, and the ongoing work to expand the technique to new imagery by using existing training sets.


Descriptors :   SOIL CLASSIFICATION , Shear strength , DIGITAL IMAGES , satellite imaging , supervised machine learning , probability , hyperspectral imagery , geographic information systems , algorithms , INFORMATION PROCESSING , MULTISPECTRAL


Distribution Statement : APPROVED FOR PUBLIC RELEASE