Groundwater potential characterization is a major component of the developmental strategies required for sustainable management of the water resources of a country. This study explores the potential of Natural

Resources Conservation Service (NRCS-CN) estimated runoff/infiltration to verify a knowledge-based groundwater potential zone mapping methodology using remote sensing and GIS. Eight criteria/factors regarded as positive indicators to the existence of groundwater in the study area were mapped and weighted based on the knowledge of the local geology using analytical hierarchy process (AHP). The results from AHP were integrated using Weighted Index Overlay Analysis in a GIS environment to delineate the groundwater potential map of the area. Five classes consisting of very good, good, moderate, fair and poor groundwater potentials, each occupying 4.6, 53.3, 82.22, 37.47, and 0.43 km2, respectively, were delineated. They were found to be in agreement with the borehole information of the area. Curve number (CN) for the various land cover types was generated using the NRCS-CN approach. CN was used to compute a qualitative, terrain-based, runoff/ infiltration response for rainfall events in the study area, from which a terrain-based runoff map of the area was computed. A comparison between the groundwater potential map and terrain-based runoff map was done using linear regression analysis. The coefficient of determination (R2) obtained was 0.80. The result indicates a high application efficiency of NRCS-CN method in verifying the accuracy of a GIS-based qualitative groundwater potential mapping.

A major challenge in most growing urban areas of developing countries, without a pre-existing land use plan is the sustainable and efficient management of solid wastes. Siting a landfill is a complicated task because of several environmental regulations. This challenge gives birth to the need to develop efficient strategies for the selection of proper waste disposal sites in accordance with all existing environmental regulations. This paper presents a knowledge-based multi-criteria decision analysis using GIS for the selection of suitable landfill site in Ado-Ekiti, Nigeria. In order to identify suitable sites for landfill, seven factors – land use/cover, geology, river, soil, slope, lineament and roads – were taken into consideration. Each factor was classified and ranked based on prior knowledge about the area and existing guidelines. Weights for each factor were determined through pair-wise comparison using Saaty’s 9 point scale and AHP. The integration of factors according to their weights using weighted index overlay analysis revealed that 39.23 km2 within the area was suitable to site a landfill. The resulting suitable area was classified as high suitability covering 6.47 km2 (16.49%), moderate suitability 25.48 km2 (64.95%) and low suitability 7.28 km2 (18.56%) based on their overall weights.

The formation of ore deposit is usually accompanied by hydrothermal alteration of the host rock through which ore bearing fluids circulate. The reactions between these circulating fluids and the host rock result in the formation of new mineral assemblages as the reaction attempts to attain equilibrium. Spectral remote sensing is an effective method for identification of hydrothermal alteration assemblages and has long been adopted by geologists in mineral exploration due to its capability to cover large areas when compared with other conventional mapping techniques [1]. While shortwave infrared (SWIR) hyperspectral remote sensing has been used in mineralogical mapping extensively, the use of hyperspectral thermal infrared (TIR) remote sensing has been limited. Notable mineralogical mapping with TIR hyperspectral has involved the use of SEBASS dataset (e.g.,[2-4]).

The SWIR wavelength range can help identify mineral groups, like hydrated minerals, carbonates and sulfates, while others may be more clearly separable in the TIR wavelength range. With the recent progress in TIR hyperspectral remote sensing it becomes imperative to determine how minerals mapped with TIR can be linked to minerals mapped using SWIR for better understanding of the distribution of alteration minerals and alteration types.

This research examines which minerals can be identified by SWIR and TIR data, and how the information from both wavelength ranges can be combined into effective mineral maps that help the geoscientists on the ground. We use the Yerington district as a test area for two reasons: a) excellent exposure of different alteration systems and zones in one area and b) ongoing economic interests in the area. We determine spatial distribution and patterns of alteration minerals using SWIR and TIR airborne data, relate mineralogy to lithology and alteration, and compare mineral distribution pattern interpreted from SWIR and TIR data to distribution pattern derived from ground samples analysis and “traditional” alteration maps.