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Occurrence 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 large volume changes in response to moisture content fluctuations following seasonal climatic variations. This can lead to deformation of structures built up on them. For this study, soil samples were collected from the eastern part of Addis Ababa. Specific expansive soil engineering parameters namely; Atterberg limits (LL, PL and PI), free swell and cation exchange capacity were measured in a soil mechanics laboratory. Reflectance spectra of each soil sample were acquired in a remote sensing laboratory using ASD fieldspec full range spectrometer. A multivariate calibration method, partial least squares regression (PLSR) analysis, through simple wavelength approach, was used to construct empirical prediction models for estimating engineering parameters of expansive soils from their respective reflectance spectra. Correlation coefficients of 0.90, 0.87, 0.71, 0.81 and 0.71 for CEC, LL, PL, PI and FS respectively were obtained. The correlation coefficients showed that large portion of variations in engineering parameters of expansive soils could be accounted for by spectral parameters. Apart from these 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. The results indicate potential of spectroscopy in deriving engineering parameters of expansive soils from their respective reflectance spectra and hence, its potential applicability in supporting geotechnical investigations of such soils.

Natural gas leakage from underground pipelines is known to affect vegetation adversely, probably by displacement of the soil oxygen needed for respiration. This causes changes in plant and canopy reflectance, which may serve as indicators of gas leakage. In this study, a covariance analysis was performed between reflectance indices of maize (Zea mays) and wheat (Triticum aestivum) canopies and oxygen concentrations in a simulated natural gas leak. Twenty-nine days after oxygen shortage occurred, the reflectance indices had the highest correlation with oxygen concentrations in the soil, for both species. The effect was consistent within species but the absolute values varied between the species. Normalization by adding a constant value to the control index of one species resulted in significant linear regression models for several indices. The indices with the highest regression coefficients were used to predict the oxygen concentration in the soil. This showed that the gas leakage caused reflectance changes up to 0.5 m from the source. As it could not be proven that oxygen shortage was the cause of the reflectance changes, further work is needed to study the side-effects of gas leakage, such as bacterial oxygen depletion, on plant growth and reflectance.

A common challenge in remote sensing is the classification of objects that are spectrally similar but represent physically different types of ground cover. In this paper, we describe and apply three complementary shape measures to classify morphologically different waterbodies in a Landsat image. Image segmentation was used to create objects of image pixels containing water, and shape measures were calculated for all obtained objects. A shape-based, a spectra-based and a combined spatial-spectral classification were carried out on a subset of the image using endmembers acquired outside the subset. The spectral classification was based on Euclidean distance. The shape-based and combined spectral-shape classification were based on vector angle, as the chosen shape measures are influenced by the image lattice and could only be used as a relative measure. The results of this approach are discussed and compared to an expert interpretation of the same dataset. Results show that shape measures are affected by image resolution and should be used as a relative measure when objects consist of 500 pixels or less. Although the combined spectral-shape classification was not satisfactory and needs more research, the classification that is solely based on shape measures can distinguish spectrally identical waterbodies and had a score of 94% compared to the expert classification.

This study focuses on the use of laboratory spectroscopy to recognize the presence and abundance of salts in soils. To create soil samples with large variations in soil salinity, six different saline solutions in various densities were prepared (containing either MgCl 2 , NaCl, KCl, K 2 SO 4 , MgSO 4 or Na 2 SO 4 ). The saline solution were used to sub-irrigate three sets of soil samples with silty clay loam ( n obs = 65), sandy loam ( n obs = 41) and sand textures ( n obs = 41). After sub-irrigation, soil spectra and soil salinity were measured for each of the 147 samples. Statistical techniques were used to detect and characterise diagnostic absorption bands and to develop predictive regression models between the spectral signature and soil salinity levels. Spectral analyses revealed that salt-affected soil samples do not exhibit all of the diagnostic absorption features that were found in the spectra of salt minerals used to treat them. It also showed that the number and clearness of diagnostic bands reduces as the salt concentration in the samples decreases. Amongst the investigated salts, MgCl 2 and MgSO 4 were estimated with the highest accuracies (cross-validated R 2 CV ≥ 0.80 and PRMSE CV R 2 CV = 0.65 with PRMSE CV = 50.3%). Only weak relations could be established to quantify KCl and Na 2 SO 4 . The results show that the observed absorption features at further than 1300 nm were broaden, the position of maximum reflectance were shifted toward shorter wavelengths and overall reflectance were changed proportionally as salts concentration were increased in soil. The continuum-removed (CR) spectra indicate a strong negative correlation between increase of soil EC and changes in absorption bands parameters (depth, width and area).

Conceptual modeling and predictive mapping of potential for geothermal resources at the regional-scale in West Java are supported by analysis of the spatial distribution of geothermal prospects and thermal springs, and their spatial associations with geologic features derived from publicly available regional-scale spatial data sets. Fry analysis shows that geothermal occurrences have regional-scale spatial distributions that are related to Quaternary volcanic centers and shallow earthquake epicenters. Spatial frequency distribution analysis shows that geothermal occurrences have strong positive spatial associations with Quaternary volcanic centers, Quaternary volcanic rocks, quasi-gravity lows, and NE-, NNW-,WNW-trending faults. These geological features, with their strong positive spatial associations with geothermal occurrences, constitute spatial recognition criteria of regional-scale geothermal potential in a study area. Application of data-driven evidential belief functions in GIS-based predictive mapping of regional-scale geothermal potential resulted in delineation of high potential zones occupying 25% of West Java, which is a substantial reduction of the search area for further exploration of geothermal resources. The predicted high potential zones delineate about 53–58% of the training geothermal areas and 94% of the validated geothermal occurrences. The results of this study demonstrate the value of regional-scale geothermal potential mapping in: (a) data-poor situations, such as West Java, and (b) regions with geotectonic environments similar to the study area.

It is known that natural gas in the soil affects vegetation health, which may be detected through analysis of reflectance spectra. Since natural gas is invisible, changes in the vegetation could potentially indicate gas leakage. Although it is known that gas in soil affects plant reflectance, the relationship between natural gas and the development and reflectance properties of plants has not been studied. The objective of this study was to test whether natural gas and its two main components, methane and ethane, affect vegetation reflectance in the chlorophyll and water absorption regions. An experiment was carried out in which maize (Zea mays) plants were grown in pots that were flushed with 10 l of gas per day for 39 ±4 days. Leaf reflectance was measured once a week with a spectrophotometer. The reflectance was analysed using continuum removal of the blue (400–550 nm), red (550–750 nm) and two water absorption features (1370–1570 nm and 1870–2170 nm), after which the band depths and normalized band depths were analyzed for each treatment. The band depth analysis showed that ethane caused an initial increase of 10% in reflectance between 560 and 590 nm, followed by a decrease during the course of the experiment. Normalized band depth analysis showed that ethane caused a reflectance shift of 1 to 5 nm towards longer wavelengths compared to the control reflectance in the visible region. All gases caused an increase in reflectance in the water absorption bands. The physiological reflectance index, PRI, which has previously linked water stress to photosynthetic activity, suggested that the hydrocarbon gases (particularly ethane) decreased the photosynthetic activity of the plants. The combination of reduced band depths in the chlorophyll and water absorption regions and the increased PRI suggests that ethane gas in the soil hampered a normal water uptake by maize plants in an early stage of their growth. Although further research is necessary to upscale the results from the laboratory to the field, the increased reflectance in the 560–590 nm region caused by ethane together with the increased PRI are promising indicators for gas leakage.

Objective comparison of classification performance of earth observation images, acquired at different spatial resolutions (e.g. NOAA-AVHRR, IRS-MOS, IRS-WiFS, Landsat-TM, IRS-LISS), is complicated because both class definition and training site selection are hampered by the inherent scale differences. This paper presents a new, generic method to compare the information content of such a set of images, the “Stained Glass Procedure”. It overcomes the stated problems by computing the scale-dependent, internal spectral variation in an image and by using this as an indicator for land cover information. The Stained Glass Procedure creates segments in the images and calculates the internal spectral variation in a high-spatial-resolution image for each segment. For each image from the set the average variance, weighted to area, is calculated. The Stained Glass Procedure can be used to predict the performance of sensors that are not available, yet, or to roughly determine the optimal spatial resolution for the classification of a specific area. The procedure was applied to images with pixel sizes ranging from 23 to 1100 m. Classification detail of Envisat-MERIS (300 m pixel size), not included in the image set, could be predicted accurately using the Stained Glass Procedure. The Stained Glass Procedure applies one procedure to all images, without any subjective decision during the analysis, thus offering a method to compare images with different pixel sizes in terms of classification detail that is truly objective.

Monitoring of three-dimensional floodplain vegetation structure is essential for ecological studies, as well as for hydrodynamic modelling of rivers. Height and density of submerged vegetation and density of emergent vegetation are the key characteristics from which roughness parameters in hydraulic models are derived. Airborne laser scanning is a technique with broad applications in vegetation structure mapping, which therefore may be a promising tool in monitoring floodplain vegetation for river management applications. This paper first provides an introduction to the laser scanning technique, and reviews previous studies on the extraction of vegetation height and density of forests, low vegetation and meadows or unvegetated areas. Reliable predictions using laser scan data have been reported for forest height (R2=0.64–0.98), parameters related to forest density, such as stem number, stem diameter, biomass, timber volume or basal area (R2=0.42–0.93), and herbaceous vegetation height (summer condition; R2=0.75–0.89). No empirical relations have been reported on density of herbaceous vegetation. Laser data of meadows and unvegetated areas show too much noise to predict vegetation structure correctly. In a case study for the lower Rhine river, the potential of laser scan mapping of vegetation structure was further explored for winter conditions. Three laser-derived metrics that are often reported in the literature have been applied to characterize local vertical distributions of laser reflections. The laser data clearly show the large structural differences both between and within vegetation units that currently are the basis of floodplain vegetation and roughness mapping. The results indicate that airborne laser scanning is a promising technique for extraction of 3Dstructure of floodplain vegetation in winter, except for meadows and unvegetated areas.

Arsenic occurs naturally in the earth's crust and is widely distributed in the environment. Natural mineralization and activities of microorganisms enhance arsenic mobilization in the environment but human intervention has exacerbated arsenic contamination. Although arsenic is useful for industrial, agricultural, medicinal and other purposes, it exerts a toxic effect in a variety of organisms, including humans. Arsenic exposure may not only affect and disable organs of the body, especially the skin, but may also interfere with the proper functioning of the immune system. This paper, therefore, generally highlights the toxic effects of arsenic as well as its mobilization in the natural environment and possible controls. It also briefly attempts to outline the impact of arsenic on the immune system, whose alteration could lead to viral/bacterial infections. Keywords: Arsenic, Immune system, Anthropogenic, Microorganisms, Season

Spatially distributed, process-based erosion models have been built to predict both erosion and deposition rates and patterns. However, predictions by these models often do not meet our expectations. There are several possible reasons for this, which can be subdivided into three groups: (i) process descriptions within the models may be incomplete or incorrect, leading to structural errors (model error); (ii) parameterization is difficult leading to a high degree of uncertainty regarding model inputs (input error); and (iii) the spatial implementation of the model (the spatial discretization and the routing methods used) may be inadequate. Hitherto, most studies of erosion model performance have focused on input parameter uncertainty: the effects of process description and spatial implementation of the model have often been neglected. In this study an attempt is made to compare some aspects of the effects of process description, parameter uncertainty and model implementation on model performance. A series of model runs was carried out to evaluate to what extent the predictions of the spatially distributed erosion model LISEM are affected by the description of the hydraulic resistance, the parameter values used to characterize hydraulic resistance as well as the routing algorithm used to generate the runoff pattern. The process description used for overland flow resistance and velocity has a clear effect on the erosion and deposition rates predicted by the model. However, relatively minor variations in a single parameter value (hydraulic roughness) appear to affect model output more strongly than variations in the process description itself. The use of different routing algorithms leads to notably different erosion and deposition patterns, but total erosion and deposition rates are much less affected. Copyright © 2005 John Wiley & Sons, Ltd.

Erosion hazard has been studied under existing conditions in 12 sites, representative of physiographic landscape units in the Likhu Khola watershed which is located 50 km northwest of Katmandu, Nepal. For this purpose the accumulated effect of erosion has been recorded as expressed by microtopographic erosion features formed in a rainy period. Seven types of microtopographic features are used: resistant clods, eroding clods, flow paths, prerills, rills, depressions and basal plant cover. As a measure of erosion hazard, the observed erosion intensity was expressed by an indicator using the percentage of shallow flow features and the more heavily weighted features of incision. Soil erosion hazard on the maize-wheat sites was found to be various, partly due to different soil surface texture of the sites. The hazard was lower on sites of dense sal forest. Crown canopy, a seasonal litter layer and a good permeability limit the erosion. The erosion hazard is lower still on sites with degraded Sal forest. These sites have a substantial basal plant cover. The erosion intensity derived from microtopographic features did not correlate with results of the Bouyoucos test, but had a good correlation with the crusting index.

The paper evaluates spreading of observations in feature and geographical spaces as a key to sampling optimisation for spatial prediction by correlation with auxiliary maps. Although auxiliary data are commonly used for mapping soil variables, problems associated with the design of sampling strategies are rarely examined. When generalised least-squares estimation is used, the overall prediction error depends upon spreading of points in both feature and geographical space. Allocation of points uniformly over the feature space range proportionally to the distribution of predictor (equal range stratification, or ER design) is suggested as a prudent sampling strategy when the regression model between the soil and auxiliary variables is unknown. An existing 100-observation sample from a 50 by 50 km soil survey in central Croatia was used to illustrate these concepts. It was re-sampled to 25-point datasets using different experimental designs: ER and 2 response surface designs. The designs were compared for their performance in predicting soil organic matter from elevation (univariate example) using the overall prediction error as an evaluation criterion. The ER design gave overall prediction error similar to the minmax design, suggesting that it is a good compromise between accurate model estimation and minimisation of spatial autocorrelation of residuals. In addition, the ER design was extended to the multivariate case. Four predictors (elevation, temperature, wetness index, and NDVI) were transformed to standardised principal components. The sampling points were then assigned to the components in proportion to the variance explained by a principal component analysis and following the ER design. Since stratification of the feature space results in a large number of possible points in each cluster, the spreading in geographical space can also be maximised by selecting the best of several realisations.

The Medium Resolution Imaging Spectrometer (MERIS) is a payload component of Envisat-1. MERIS will be operated over land with a standard 15 band setting acquiring images with a 300 m spatial resolution. The red-edge position (REP) is a promising variable for deriving foliar chlorophyll concentration, which plays an important role in ecosystem processes. The objectives of this paper are: (1) to study which factors effect the REP of vegetation, (2) to study whether this REP can be derived from the MERIS standard band setting and (3) to show what REP represents at the scale of MERIS data. Two different data sets were explored for simulating the REP using MERIS bands: (1) simulated data using reflectance models and (2) airborne reflectance spectra of an agricultural area obtained by the airborne visible-infrared imaging spectrometer (AVIRIS). A “linear method”, assuming a straight slope of the reflectance spectrum around the midpoint of the slope, was a robust method for determining the REP and the MERIS bands at 665, 708.75, 753.75 and 778.75 nm could be used for applying the “linear method” for REP estimation. Results of the translation to the scale of MERIS data were very promising for applying MERIS at, for instance, the ecosystem level.

In agricultural areas, tillage-induced roughness may have large impacts on runoff patterns and therefore on the effective slope, local contributing areas and erosion patterns. A model was developed to create a runoff pattern with flow in the direction of the plough-lines for all tilled fields within a catchment. The model needs a digital elevation model (DEM), a landuse map and the major tillage orientation per tilled field as input. Optionally, the flow direction of roads and/or channels can be superimposed on the drainage network. The model calculates flow directions along parcel borders and creates headlands along borders that are not parallel to the tillage orientation. The model also calculates the slope gradient in flow direction. The created tillage-controlled runoff pattern can be combined with the topographic runoff pattern, if decision rules are available to choose between topographic or tillage direction. The tillage runoff pattern can be very different from the topographic pattern, leading to totally different patterns of slope and contributing area. The use of the tillage-controlled runoff pattern rather than the topographically controlled runoff pattern in a deterministic, event-based model (LISEM), results in a much better agreement of the predicted runoff and erosion pattern with field observations. However, accurate model predictions can only be obtained if the input DEM is sufficiently accurate to represent local topographic variations in the fields.

During Hurricane Mitch in 1998, a debris avalanche occurred at Casita volcano, Nicaragua, resulting in a lahar that killed approximately 2500 people. The failure that initiated the avalanche developed at a pre-existing cliff, part of the headwall of a gravitational slide of approximately 1.8 km 2 in plan view that cuts the southern flank of the volcano. Structural analysis, primarily based on a high-resolution DEM, has shown that this slide is caused by edifice deformation. Casita's eastern side is spreading radially outwards, forming a convex–concave profile and steepening original slopes. This deformation is possibly facilitated by millennia of persistent hydrothermal alteration of the volcano's core. The gravity slide has some typical features of smaller slumps, such as steep headwalls, an inner flatter area and a pronounced basal bulge fronted by thrusts. The headwall is the source of the 1998 avalanche, as well as several previous mass movements. Edifice deformation has led to extensive fracturing of the hydrothermally altered andesitic source rock, increasing instability further. Field evidence indicates that the gravity slide is still actively deforming, and with steep headscarps remaining, the hazard of future avalanches is increasing. The analysis presented here shows how small but highly damaging landslides can occur during the deformation of a volcanic edifice. We show that identification of instability is possible with remote sensing data and minimal reconnaissance work, implying the possibility of similar efficient and cost-effective analysis at other volcanoes known to host extensive hydrothermal systems. We demonstrate this with a simple structural analysis of two similar stratovolcanoes, Orosi (Costa Rica) and Maderas (Nicaragua).

Within the framework of ESA's Earth Observation Program, the Medium Resolution Imaging Spectrometer (MERIS) is developed as one of the payload components of the ENVISAT‐1. MERIS is a fully programmable imaging spectrometer, however a standard 15 channel band set will be transmitted for each 300 m. pixel (over land) covering the visible and near‐infrared wavelength range. Since MERIS is a multidisciplinary sensor providing data that can be input into ecosystem models at various scales, we studied MERIS performance relative to the scale of observation using simulated data sets degraded to various resolutions in the range of 12m. to 300m. Algorithms to simulate MERIS data using airborne imaging spectrometer data sets are presented, including a case study from GERIS 63 channel data over a agricultural site in central Spain (the Almaden test site). Through a pixel purity analysis, end members are derived from the MERIS‐type data and subsequently used as input to a spectral unmixing analysis yielding f...

Spectra of wheat measured in the field in an oil-bearing area north of Changyi, south of the Yellow River delta in eastern China, were analysed to study the relations between spectral characteristics and hydrocarbon microseepage. Along two transects over known petroleum reservoirs, ethane gas contents measured in soil show high values above the oil-water contacts and faults. Delta carbonate contents also showed high values at these contacts. Both features are indicative of hydrocarbon microseepage. The red-edge positions of wheat spectra were calculated and found to be positioned at 744.43nm in areas of microseepage and 738.26nm in areas with no microseepage; a 7nm shift to longer wavelength (red shift). Furthermore, a regression analysis of the red-edge inflection point positions versus delta carbonate and ethane shows a statistically significant correlation indicating a possible relation between microseepage and spectral properties of wheat. This research demonstrates that at a field scale remote sensin...

Swelling soils are soils containing clay minerals that change volume with water content. The original volume of natural soils may change up to 150 percent with increasing water content, which creates major geological hazards that cause extensive damage worldwide. Current engineering practice for delineating areas of potential high swell builds on extensive laboratory analysis, including X-ray diffraction analysis for establishing clay mineralogy and Atterberg limits for deriving the swelling index. This is labour-intensive and thus expensive. Of key importance in assessing the swelling potential of soils is accurate mapping of clay mineralogy and amount (particularly of high swelling smectite and low swelling kaolinite-group minerals) and mapping of soil moisture. For applications related to slope instability processes, surface height and surface deformation need to be examined. Results from spectral analysis of clay mineral spectra presented in this paper show that careful examination of absorption bands allows the characterization and mapping of the clay mineralogy of the soil, which, in conjunction with spectral unmixing, may lead to surface fractions of the various clay minerals. This can potentially be empirically linked with current engineering tests. Remote sensing perspectives for spatial reproduction of these results are further examined in this paper. Imaging spectrometry (ie, data acquisition in many narrow spectral bands that allow images of reflectance spectra to be derived) may provide insight in surface mineralogy, while microwave remote sensing could deliver soil moisture information. Interferometric SAR (InSAR) is one method of remotely sensed elevation mapping; other remote sensing approaches include radar and laser altimetry and the derivation of digital terrain data from stereoscopic imagery (ie, Spot, MOMS, etc). This paper could form the basis for formulating a number of research projects within a framework of mapping swelling potential of soils from space.

Accurate prediction of the shape, location, size and properties of the solid rock materials to be extracted during mining is essential for reliable technical and financial planning. This is achieved through geological modelling of the three-dimensional (3D) shape and properties of the materials present in mineral deposits, and the presentation of results in a form which is accessible to mine planning engineers. In recent years the application of interactive graphics software, offering 3D database handling, modelling and visualisation, has greatly enhanced the options available for predicting the subsurface limits and characteristics of mineral deposits. A review of conventional 3D geological interpretation methods, and the model struc- tures and modelling methods used in reserve estimation and mine planning software packages, illustrates the importance of such approaches in the modern mining industry. Despite the widespread introduction and acceptance of computer hardware and software in mining applications, in recent years, there has been little fundamental change in the way in which geology is used in orebody modelling for predictive purposes. Selected areas of current research, aimed at tackling issues such as the use of orientation data, quantification of morphological differences, incorporation of geological age relationships, multi-resolution models and the application of virtual reality hardware and software, are discussed.

Slope instability hazard assessment is based on the analysis of the terrain conditions at sites where slope failures occurred in the past. For the analysis of the causative factors the application of geographic information systems (GIS) is an essential tool in the data analysis and subsequent hazard assessment. Three scale levels of hazard mapping are defined. A direct experience-driven mapping at reconnaissance level, a statistical approach to determine the causative factors in a quantitative susceptibility mapping and a methodology at large-scale making using of deterministic models.

The scale and shape of areas and volumes of contamination at and below the Earth's surface are summarized. It is argued that in terms of their anomalous chemical composition, spatial distribution and relation with the host matrix, analogies can be drawn between bodies of contamination and deposits of metalliferous minerals. It is recommended that bodies of contamination are explored in much the same ways as mineral deposits. Additional attention must be given to their greater chemical complexity and degree of mobility. Characterization of clays and other sorbents is particularly important in contaminated soils and sediments. The scavenging property of clays means that they act as natural immobilizers of contaminants and can be employed as contaminant containment barriers. Clays are, however, vulnerable to alteration and degradation of their sorption capacity, which can lead to the release of absorbed contaminants.

Five years of research have increased our understanding of the effects of disturbances on some forest processes and given directions for forest management in Guyana. At present most logging concentrates on Chlorocardium rodiei (greenheart) and current practices are damaging, but they may have little effect on the overall water balance and nutrient cycle if some simple rules are adhered to. The basic research results do not lead to a fully documented sustainable forest management system, as translation to prac- tical management is not always simple. In general it would appear that applied research may give fast results in an often quick and dirty approach. Basic research, if directed at the right forest processes, may provide answers when the quick and dirty approach does not fulfil its objectives. As such they are complementary. In tropical forest management we cannot wait until basic research provides all answers leading to proper forest man- agement, and a combination of the two would probably provide most answers in the long term.

Results of quantitative analysis of subsidence data from 20 wells covering six major basement blocks from the Sirte Basin (Libya) are presented. Following the Late Cretaceous onset of extension and associated collapse of the Sirte Arch, the tectonic history post-dating this event can be separated into four distinct phases: 1. (1) minor subsidence during the Late Cretaceous; 2. (2) differential fault tectonics and reactivation of basement faults during latest Cretaceous to Paleocene; 3. (3) regional uplift and subsidence during the Eocene; 4. (4) minor subsidence during the Early Oligocene and Early Miocene. A Late Cretaceous-Paleocene stretching phase of finite duration can explain the overall patterns of observed tectonic subsidence during the syn- and post-rift evolution of the Sirte Basin. Strong short-term deviations from thermally induced long-term subsidence observed during the Eocene can be explained by intraplate compression and subsequent stress release related to changes in Atlantic flowline geometry. Modelling of the observed tectonic subsidence for the Sirte Basin yields estimates of extension in excess of estimates inferred from displacements along high-angle normal faults. The effect of late-stage intraplate compression on tectonic subsidence may cause part of the observed discrepancy between estimates of crustal extension.

Even though natural hazard threats are present in most parts of the world, according to the data collected in the International Disaster Database, most of them occur in developing countries, and remain a major obstacle to sustainable development and the achievement of the Millennium Development Goals. The trend during the last decades shows an increase in the number of natural hazard events and their consequences. Natural hazards cannot be avoided, but understanding and measuring the factors that make up vulnerability, the main factor in the risk equation that can be managed, is an important research task. In this endeavor, information is a key factor in vulnerability reduction. Most planning authorities rely on hazard maps to define risk management plans and projects, but these maps only depict the threat and not the whole picture of what and who can be affected by these hazards. Information, or rather the availability of useful information, is a critical element for effectively tackling vulnerability. Defining the fitness for use of municipal geo-information for earthquake vulnerability assessment is the main topic of this research. A methodology was developed to establish whether and to what extent the vulnerability indicators calculated using this municipal geo-information are suitable for decision making. This is done by understanding the different types of vulnerability, and re-defining it in terms of the three disaster stages: impact, relief and recovery. The main proposal of the general analysis model is the analysis of vulnerability of a region for the 3 stages of a disaster (1- Impact, 2- Relief, and 3- Recovery), that follow each other in time and require different municipal strategies to cope with them. Considering this, the availability of data for the analysis of vulnerability in each phase starts with the identification of the required information -indicators- and their specific attributes. A list of indicators exists for each phase (required information) that in turn will be rated in importance according to different attributes. Some indicators are common to different evaluation phases, but their application to the analysis and/or solution proposals or plans is different. The indicators are assessed in terms of five attributes: availability, completeness, integrity and reliability, scale, and shelf-life.

The paper describes a novice method for sampling geochemicals to characterize mine tailings. We model the spatial relationships between a multi-element signature and, as covariates, abundance estimates of secondary iron-bearing minerals in mine tailings dumps. The covariates of interest, are readily, but less accurately obtainable by using airborne hyperspectral data and estimated through spectral unmixing. Via simulated annealing an optimal prospective sampling scheme for a new unvisited area is derived based on the variogram model of a previously sampled area.

Coal fires worldwide are causing enormous economic loss and environmental pollution, prompting a need to develop the methodology to map, analyse, and monitor them. Coal fire-related land cover mapping yields the knowledge of the distribution of coal, which is crucial for the delineation of potential coal fires and coal fire risk areas. The conventional pixel-based method does not make use of spatial relationships, whereas object-based image analysis (OBIA) has the potential to consider not only objects' spectral but spatial information, in terms of size, shape, texture and relations to other image objects. This article reports on coal fire-related land cover mapping with OBIA using multi-resolution segmentation and hierarchical classification. Both spectral and spatial information were used in the classification. It yielded an overall accuracy of 12.3% higher than that by the pixel-based method (70.67%), and the difference is significant (p = 0.05) by McNemar's test.

Leakage of hydrocarbon has a large economic and environmental impact. Traditional methods for investigating leakage and resulting pollution, such as drilling, are destructive, time consuming and expensive. Remote sensing is an alternative that is non-destructive and has been been tested extensively for exploration of onshore hydrocarbon reservoirs and detection of hydrocarbons at the Earth’s surface. In this research, a leaking pipeline is investigated through field reflectance spectrometry and the findings are validated with traditional drilling and geophysical measurements. The measurements show a significant increase of vegetation anomalies on the pipeline with respect to areas further away. The observed anomalies are positively related to hydrocarbon pollution through chemical analysis of drillings. Subsurface geophysical measurements show a large correlation with observed surface vegetation stress, enhancing the identification of hydrocarbon-related vegetation stress through spectroscopy.