Lithological mapping of Northwest Argentina with remote sensing data using tonal, textural and contextual features

Tonal, textural and contextual properties are used in manual photointerpretation of remotely sensed data. This study has used these three attributes to produce a lithological map of semi arid northwest Argentina by semi automatic computer classification procedures of remotely sensed data. Three different types of satellite data were investigated, these were LANDSAT MSS, TM and SIR-A imagery. Supervised classification procedures using tonal features only produced poor classification results. LANDSAT MSS produced classification accuracies in the range of 40 to 60%, while accuracies of 50 to 70% were achieved using LANDSAT TM data. The addition of SIR-A data produced increases in the classification accuracy. The increased classification accuracy of TM over the MSS is because of the better discrimination of geological materials afforded by the middle infra red bands of the TM sensor. The maximum likelihood classifier consistently produced classification accuracies 10 to 15% higher than either the minimum distance to means or decision tree classifier, this improved accuracy was obtained at the cost of greatly increased processing time. A new type of classifier the spectral shape classifier, which is computationally as fast as a minimum distance to means classifier is described. However, the results for this classifier were disappointing, being lower in most cases than the minimum distance or decision tree procedures. The classification results using only tonal features were felt to be unacceptably poor, therefore textural attributes were investigated. Texture is an important attribute used by photogeologists to discriminate lithology. In the case of TM data, texture measures were found to increase the classification accuracy by up to 15%. However, in the case of the LANDSAT MSS data the use of texture measures did not provide any significant increase in the accuracy of classification. For TM data, it was found that second order texture, especially the SGLDM based measures, produced highest classification accuracy. Contextual post processing was found to increase classification accuracy and improve the visual appearance of classified output by removing isolated misclassified pixels which tend to clutter classified images. Simple contextual features, such as mode filters were found to out perform more complex features such as gravitational filter or minimal area replacement methods. Generally the larger the size of the filter, the greater the increase in the accuracy. Production rules were used to build a knowledge based system which used tonal and textural features to identify sedimentary lithologies in each of the two test sites. The knowledge based system was able to identify six out of ten lithologies correctly.

Silica promoted self-assembled mesoporous aluminas. Impact of the silica precursor on the structural, textural and acidic properties

This paper investigates the effect of silica addition on the structural, textural and acidic properties of an evaporation induced self-assembled (EISA) mesoporous alumina. Two silica addition protocols were applied while maintaining the EISA synthesis route. The first route is based on the addition of a Na-free colloidal silica suspension (Ludox®), and the second method consists of the co-hydrolysis of tetraethyl orthosilicate (TEOS) with aluminium tri-sec-butoxide, to favour a more intimate mixing of the Al- and Si-hydrolysed species. The properties of the so derived materials were compared to the SiO2-free counterpart. The SiO2 addition was always beneficial from a structural and textural standpoint. TEOS appears to have a truly promoting effect; the ordering, surface area and pore volume are all improved. For Ludox®, the enhancement comes from the formation of smaller pores by a densification of the structure. The crystallization of γ-alumina depends on the interaction between the Al- and Si-species in the mesophase. Ludox®-based materials achieved crystallization at 750 °C but the intimate mixing in the TEOS-based mesophases shows a suppression of the phase transformation by 50-100 °C, with respect to the SiO2-free counterpart. This reduces the textural features substantially. For all SiO2-modified materials, the enhancement in the surface area is not accompanied by a concomitant improvement of total acidity, and the formation of weak Lewis acid sites was promoted. These effects were ascribed to SiO2 migration to the surface that blocks part of the acidity.

Towards sea surface pollution detection from visible band images

This paper presents a novel approach to water pollution detection from remotely sensed low-platform mounted visible band camera images. We examine the feasibility of unsupervised segmentation for slick (oily spills on the water surface) region labelling. Adaptive and non adaptive filtering is combined with density modeling of the obtained textural features. A particular effort is concentrated on the textural feature extraction from raw intensity images using filter banks and adaptive feature extraction from the obtained output coefficients. Segmentation in the extracted feature space is achieved using Gaussian mixture models (GMM).

Thermal stability of porous sol-gel phosphosilicates and their surface area stabilisation by lanthanum addition

The thermal stability of porous sol-gel phosphosilicates was studied by comparing the textural features upon calcination between 400 and 550 °C. A significant loss of surface area and pore volume were observed; the first is due to thermal coarsening of the nanoparticles, and the pore volume reduction was ascribed to sintering of the most external nanoparticles producing less void volume. Lanthanum addition was investigated as thermal stabilizer. For the mesoporous phosphosilicate composition, lanthanum addition enhanced the surface area, showing a 45% and 50% improvement with respect to the La-free counterpart; the effect was much less visible for the macroporous composition.

Modifying the hierarchical porosity of SBA-15 via mild-detemplation followed by secondary treatments

Fenton-chemistry-based detemplation combined with secondary treatments offers options to tune the hierarchical porosity of SBA-15. This approach has been studied on a series of SBA-15 mesophases and has been compared to the conventional calcination. The as-synthesized and detemplated materials were studied with regard to their template content (TGA, CHN), structure (SAXS, TEM), surface hydroxylation (Blin-Carterets approach), and texture (high-resolution argon physisorption). Fenton detemplation achieves 99% of template removal, leading to highly hydroxylated materials. The structure is better preserved when a secondary treatment is applied after the Fenton oxidation, due to the intense capillary forces during drying in water. Two successful approaches are presented: drying in a low-surface-tension solvent (such as n-BuOH) and a hydrothermal stabilization to further condense the structure and make it structurally more robust. Both approaches give rise to remarkably low structural shrinkage, lower than calcination and the direct water-dried Fenton. Interestingly, the derived textural features are remarkably different. The n-BuOH exchange route gives rise to highly hierarchical structures with enhanced interconnecting pores and the highest surface areas. The hydrothermal stabilization produces large-pore SBA-15 structures with high pore volume, intermediate interconnectivity, and minimal micropores. Therefore, the hierarchical texture can be fine-tuned in these two fashions while the template is removed under mild conditions.