J.P. Rigol-Sánchez

Artificial neural networks as a tool for mineral potential mapping with GIS

A back-propagation artificial neural network (ANN) model is proposed to discriminate zones of high mineral potential in the Rodalquilar gold field, south-east Spain, using remote sensing and mineral exploration data stored in a GIS database. A neural network model with three hidden units was selected by means of the k -fold cross-validation method. The trained network estimated a gold potential map efficiently, indicating that both previously known and unknown potentially mineralized areas can be detected. These initial results suggest that ANN can be an effective tool for mineral exploration spatial data modelling.

ArcGeomorphometry: A toolbox for geomorphometric characterisation of DEMs in the ArcGIS environment

Abstract A software tool is described for the extraction of geomorphometric land surface variables and features from Digital Elevation Models (DEMs). The ArcGeomorphometry Toolbox consists of a series of Python/Numpy processing functions, presented through an easy-to-use graphical menu for the widely used ArcGIS package. Although many GIS provide some operations for analysing DEMs, the methods are often only partially implemented and can be difficult to find and used effectively. Since the results of automated characterisation of landscapes from DEMs are influenced by the extent being considered, the resolution of the source DEM and the size of the kernel (analysis window) used for processing, we have developed a tool to allow GIS users to flexibly apply several multi-scale analysis methods to parameterise and classify a DEM into discrete land surface units. Users can control the threshold values for land surface classifications. The size of the processing kernel can be used to identify land surface features across a range of landscape scales. The pattern of land surface units from each attempt at classification is displayed immediately and can then be processed in the GIS alongside additional data that can assist with a visual assessment and comparison of a series of results. The functionality of the ArcGeomorphometry toolbox is described using an example DEM.

A comparative assessment of different methods for Landsat 7/ETM+ pansharpening

This article compares a set of relevant methods, based on different mathematical approaches, for Landsat 7 Enhanced Thematic Mapper Plus (ETM+) pansharpening. These are classical procedures such as principal component analysis and fast intensity hue saturation; methods based on wavelet transforms, such as wavelet à trous, additive wavelet luminance proportional and multidirectional–multiresolution methods; a method of a geostatistical nature, called downscaling cokriging (DCK); and finally, a Bayesian method (1cor). The comparison of the fused images is based on the qualitative and quantitative evaluation of their spatial and spectral characteristics by calculating statistical indices and parameters that measure the quality and coherence of the images. Moreover, the quality of the spectral information is studied indirectly by means of the Iterative Self-Organizing Data Analysis Technique (ISODATA) classification of the products of fusion. The results show that DCK and 1cor methods yielded better results than the wavelet-based methods. Particularly, DCK does not introduce artefacts in the estimation of the digital numbers corresponding with the source multispectral image and, therefore, it can be considered as the most coherent method.

Impacts of agricultural irrigation on groundwater salinity

Agricultural irrigation represents the main use of global water resources. Irrigation has an impact on the environment, and scientific evidence suggests that it inevitably leads to salinization of both soil and aquifers. The effects are most pronounced under arid and semi-arid conditions. In considering the varied impacts of irrigation practices on groundwater quality, these can be classed as either direct—the direct result of applying water and accompanying agrochemicals to cropland—or indirect—the effects of irrigation abstractions on groundwater hydrogeochemistry. This paper summarizes and illustrates through paradigmatic case studies the main impacts of irrigation practices on groundwater salinity. Typically, a diverse range of groundwater salinization processes operating concomitantly at different time scales (from days to hundreds of years) is involved in agricultural irrigation. Case studies suggest that the existing paradigm for irrigated agriculture of focusing mainly on crop production increases has contributed to widespread salinization of groundwater resources.