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Presence of expansive soils in construction sites has serious implications on planning, design, construction, maintenance, and overall performance especially of lightweight engineering infrastructures. Such soils are particularly susceptible to considerable volume changes in response to moisture content fluctuations following seasonal climatic variations. This property can cause severe damages to infrastructures unless proper measures are taken in their design. Identification of expansive soils and characterization of their anticipated behavior is thus important for site selection, design, and construction. In this study, specific expansive soil engineering parameters; consistency limits (liquid limits (LL), plastic limits (PL) and plasticity indices (PI)), free swell (FS), cation exchange capacity (CEC) and California bearing strength (CBR) were measured in a soil mechanics laboratory. Reflectance spectra of each soils sample were acquired in a remote sensing laboratory using ASD fieldspec full range spectrometer. A multivariate calibration method, partial least squares regression (PLSR) analysis, was used to relate engineering parameters and spectral parameters extracted from the reflectance spectra of expansive soils. Correlation coefficients obtained showed that a large portion of the variation in the engineering parameters (e.g. r=0.85, 0.86 for CEC and LL respectively) could be accounted for by the spectral parameters. The results indicate potential of spectroscopy in providing estimates of engineering parameters of expansive soils (e.g. subgrade characteristics), which can be useful in site selection, route planning and search for construction materials (borrow, subbase etc).

This study presents a novel approach in combining textural information from the panchromatic band with spectral information from the multispectral bands for improved image classification. Firstly, we develop a texture measure based on wavelet coefficients of the panchromatic band that can be aggregated to the resolution of the multispectral bands. Secondly, we combine the texture measures with the spectral information in the multispectral bands in a fuzzy classification framework. Thirdly, we illustrate our approach with a case study of vegetation and land cover classification based on a Quickbird image of subantarctic Macquarie Island.

Expansive soils are major geotechnical hazards that pose several problems on engineering structures causing billions of dollars of damage in many parts of the world especially at places where there are significant climatic differences between dry and wet periods (Gourley et al., 1993; Nelson and Miller, 1992). Such soils expand or swell when moistened and shrink and crack when dried which involves tremendous volume changes. Thus, they are of significant concern in the construction sector. Identification of expansive soils and characterization of their anticipated behavior should be done exhaustively for proper site selection, design, and construction of civil engineering infrastructures. Particular attention is required especially when dealing with lightweight structures like road infrastructures, airfields, and small buildings, etc. since the uplift pressure from the soil swell exceeds the downward pressure exerted from such structures. However, the conventional standard methods of assessing the geotechnical properties of expansive soils are expensive, labor intensive and time consuming. In addition it is not possible to get continuous representation of soil masses in space. Thus, the presence and spatial distribution of these soils can be overlooked and their types might not be precisely determined. This can lead to under-sampling of sites and subsequent inadequate design specifications. Hence, there is a need to identify and characterize expansive soils in a cheaper, rapid and continuous method as compared to the conventional methods of assessing the geotechnical properties of these soils. For this study a total of 80 disturbed soil samples were collected from the eastern part of Addis Ababa city. Much construction activities are taking place in the study area and problems due to expansive soils are frequently reported. Stratified random sampling was used to obtain the required samples, and disturbed soil samples were taken from each sampling location trough hand augering and digging. We measured specific expansive soil engineering parameters namely; Atterberg limits (liquid limits, plastic limits and plasticity indices), free swell and cation exchange capacities in a soil mechanics laboratory. We also acquired the reflectance spectra of each soil sample using the ASD fieldspec spectrometer that covers the 350 nm to 2500 nm wavelength region of the electromagnetic spectrum to establish a relationship between the engineering parameters and the soil reflectance spectra. Analyzing the engineering parameters as well as the spectral characteristics of the soil samples has revealed that the soil samples have a large variation in their expansion potential. Statistical links were established between engineering parameters of expansive soils and absorption feature parameters at specific wavelength regions (~1400 nm, ~1900 nm and ~2200 nm). A Multivariate calibration method, partial least squares regression (PLSR) analysis was used to construct empirical prediction models to enable the estimation of engineering parameters of expansive soils from absorption feature parameters calculated from those specific wavelength regions. Correlation coefficients (r) obtained showed that large portions of the variation in the engineering parameters could be accounted for by the spectral parameters (r = 0.85, 0.86, 0.68, 0.83 and 0.64) for CEC, LL, PL, PI and FS respectively). Apart from the high correlation coefficients, small root mean square errors of calibration (RMSEC) and prediction (RMSEP), standard error of calibration (SEC) and prediction (SEP) and minimum bias were obtained indicating the potential of spectroscopy in deriving engineering parameters of expansive soils from their respective reflectance spectra, and hence its potential applicability in supporting the geotechnical investigations of such soils. Results indicate that spectroscopy can be used to identify and subsequently characterize expansive soils and their engineering behaviors that can be explained by the measured engineering parameters. This contribution of spectroscopic methods (cheaper, fast and yet capable of covering large area) at the reconnaissance stage of site investigation will assist to tailor the detailed field investigation into site-specific needs in an effort to assess the feasibility of intended projects.