Soil, water, and climatic classification systems are reviewed as background for the construction of a classification system for earthen aquaculture ponds. The physical and chemical properties of important soil types are also reviewed because of the critical role that the soil plays in earthen pond systems. A pond classification system is constructed using key elements from established climate, water, and soil classification systems, and its use as a management tool is demonstrated. Additional benefits of pond classification are discussed. Functional relationships pertaining to a particular management practice--the application of lime--are examined for seven classes of acid soils. Theoretical and empirical models of pH-percent base saturation relationships are evaluated using data from United States soils. Selected models are partially validated using an independent set of data and incorporated into a lime requirement determination model. A table of lime requirement estimates based on initial soil pH values is calculated for each soil class. Partial validation of the classification system is achieved by ANOVA for the cation exchange capacities of the soils, by fitting the selected pH-percent base saturation models to data from an independent source, and by comparison of the estimated lime requirements with previously published guidelines. Possible reasons for weaknesses in the classification system, the pH-percent base saturation models, or the approach to lime requirement determination are explored, and areas requiring further research are identified. Additional uses and benefits, and further validation and refinement of the classification system are discussed. It is concluded that the proposed classification is a good first approximation that provides a basis for further work. / Graduation date: 1992

In situ radiometric field data and data simulated with a radiative transfer model were used to evaluate the performance and biophysical interpretation of spectral indices Concurrently with remotely sensed measurements, temporal biophysical measurements for different vegetation types for two semi-arid regions in Niger were made, including leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fAPAR), percent vegetation cover, and biomass. The spectral dynamics of vegetation and soil were characterized at the leaf and canopy scale by optical measurements under many adverse conditions, including variability in vegetation optical and structural properties, soil reflectance properties, sun and view geometry and atmospheric perturbations. The spectral indices evaluated in this research comprised spectral vegetation indices and spectral mixture model indices, computed from spectral reflectances. The performance of different vegetation indices and their sensitivity to green and non-green vegetation and soils were compared and quantified by utilizing estimates of percent relative error in spectral vegetation indices, and estimates of vegetation equivalent noise expressed in terms of biophysical parameters (LAI, fAPAR). The soil adjusted vegetation index (SAVI) and modified normalized vegetation index (MIND VI) were improvements over the normalized difference vegetation index (NDVI), but were still sensitive to many perturbing variables such as soil and vegetation distribution, soil optical properties, litter and green vegetation optical properties and leaf angle distribution. The spectral mixture model indices were designed to be sensitive to vegetation, soil and non-green vegetation components and were shown to provide useful surface information that can aid in minimizing the noise in spectral vegetation indices, and also in improving their biophysical interpretation. Vegetation and soil brightness imagery were created from remotely sensed reflectance data, by calibrating the spectral mixture model with the data generated with a radiative transfer model. The effect of standing litter on spectral indices was shown to possibly cause both an increase and a decrease in the vegetation index, depending on the coupled spectral and structural properties of litter, green vegetation and soil. In situ measurements confirmed the results obtained from the analysis of data sets generated with a radiative transfer model. The implications of the effect of perturbing variables on spectral indices were also discussed.

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