Pedotransfer functions to estimate soil water content at field capacity and permanent wilting point in hot Arid Western India

Characterization of soil water retention, e.g., water content at field capacity (FC) and permanent wilting point (PWP) over a landscape plays a key role in efficient utilization of available scarce water resources in dry land agriculture; however, direct measurement thereof for multiple locations in the field is not always feasible. Therefore, pedotransfer functions (PTFs) were developed to estimate soil water retention at FC and PWP for dryland soils of India. A soil database available for Arid Western India (N=370) was used to develop PTFs. The developed PTFs were tested in two independent datasets from arid regions of India (N=36) and an arid region of USA (N=1789). While testing these PTFs using independent data from India, root mean square error (RMSE) was found to be 2.65 and 1.08 for FC and PWP, respectively, whereas for most of the tested ‘established’ PTFs, the RMSE was >3.41 and >1.15, respectively. Performance of the developed PTFs from the independent dataset from USA was comparable with estimates derived from ‘established’ PTFs. For wide applicability of the developed PTFs, a user-friendly soil moisture calculator was developed. The PTFs developed in this study may be quite useful to farmers for scheduling irrigation water as per soil type.     

Relative Radiometric Normalisation - performance testing of selected techniques and impact analysis on vegetation and water bodies

In this paper, six image-based Relative Radiometric Normalization (RRN) techniques were applied to normalize the bi-temporal Landsat 5 TM data-set. RRN techniques do not require any atmospheric and ground information at the time of image acquisition. The target image for the year 2009 was normalized in such a way that it resembled the atmospheric and sensor conditions similar to those under which the reference image of the same season for the year 1990 was acquired. Among the selected methods applied, it was found that the Iteratively Reweighted Multivariate Alteration Detection (IR-MAD) method performed better, based on the error statistic. The IR-MAD technique was found to be advantageous as it identified a large set of true time-invariant pixels automatically from the change background using iterative canonical component analysis. The technique also stretches the values of Normalized Difference Vegetation Index and Normalized Difference Water Index and may help to distinguish different vegetation and water bodies better.     

A Comparative Study of Tasselled Cap Transformation of DMC and ETM+ Images and their Application in Forest Classification

In this paper, an attempt has been made to derive the tasselled cap coefficients manually following the rigorous mathematical computations for the three-band Disaster Monitoring Constellation (DMC) data. Considering ten DMC images of same season, it has been found that the first two transformation components, namely brightness and greenness can capture on an average 94.44 % of the three band variance of the DMC image. The coefficients of TC transformation equations for DMC image were derived considering the above mentioned ten DMC images. For the application purpose the TC images were applied to classify the forest types of the New Forest area of UK. For the comparison purpose, the tasselled cap images generated after the automated transformation of the Landsat 7 ETM+ image of the same area were considered to classify the forest types. A series of statistical intra-image and inter-image comparisons were conducted to find out the intra and inter-relationships between the brightness and greenness images obtained from the two different sensors. Finally, the accuracies of both the classified images were assessed based on the field collected GPS data. It was estimated that the overall accuracies of the classified DMC and ETM+ images were 77.44 % and 81.43 % respectively.     

Mapping the distribution of iron ore minerals and spatial correlation with environmental variables in hilltop mining areas

The prime contribution of this assignment was to examine the hyperspectral remote sensing, based on iron ore minerals identification using spectral angle mapper (SAM) technique. Correlation analyses between field iron contents and environmental variables (soil, water, and vegetation) have been performed. Spectral feature fitting (SFF) and multi-range spectral feature fitting (MRSFF) methods were used for accuracy assessment in extracting iron ore minerals from Hyperion EO-1 data. Spectral inspections as a reference were used in SAM technique for image classification for iron ore minerals: Hematite (24.26%), Goethite (32.98%) and Desert (42.76). Iron ore minerals classification is justified by the United States Geological Survey (USGS) spectral library and field sample points. The regression analysis of USGS and Hyperion reflectance spectra has shown the moderate positive correlation. The regression analyses between iron ore contents and environmental parameters (soil, water, and vegetation) have shown the moderate negative correlation. The examination was significantly effectual in extracting iron ore minerals: Hematite (SFF RMSE?≤?0.51 MRSFF RMSE?≤?0.48), Goethite (SFF RMSE?≤?0.047 MRSFF RMSE?≤?0.438) and Desert (SFF RMSE?≤?0.63 and MRSFF RMSE?≤?0.50); and the MRSFF RMSE histograms indicate the above result likened to a conventional SFF RMSE. MRSFF RMS error result is best because multiple absorption features typically characterize spectral signatures. This analysis demonstrates the potential applicability of the methodology for iron minerals identification framework and iron minerals impact on environmental parameters.     

Spatial analysis software testing tool based on object-oriented techniques

Object-oriented (OO) programming and system design have become the scalable methodology for large-scale enterprise and technology system designs. Spatial and geographic information system (GIS)-based systems are not exempt from this trend and have widely adopted object-oriented methodology. Testing strategies for systems developed with OO technologies need to be carefully evaluated. Specific features of OO technologies such as information hiding and close tying of data structures with class structures and the natural peculiarities of the spatial data require revisiting of test strategies for spatial applications built on OO technology. This article focuses on object-oriented testing trends and the development of associated tools in the GIS industry.     

Spatial prediction of soil properties in a watershed scale through maximum likelihood approach

Surface map of soil properties plays an important role in various applications in a watershed. Ordinary kriging (OK) and regression kriging (RK) are conventionally used to prepare these surface maps but generally need large number of regularly girded soil samples. In this context, REML-EBLUP (REsidual Maximum Likelihood estimation of semivariogram parameters followed by Empirical Best Linear Unbiased Prediction) shown capable but not fully tested in a watershed scale. In this study, REML-EBLUP approach was applied to prepare surface maps of several soil properties in a hilly watershed of Eastern India and the performance was compared with conventionally used spatial interpolation methods: OK and RK. Evaluation of these three spatial interpolation methods through root-mean-squared residuals (RMSR) and mean squared deviation ratio (MSDR) showed better performance of REML-EBLUP over the other methods. Reduction in sample size through random selection of sampling points from full dataset also resulted in better performance of REML-EBLUP over OK and RK approach. The detailed investigation on effect of sample number on performance of spatial interpolation methods concluded that a minimum sampling density of 4/km² may successfully be adopted for spatial prediction of soil properties in a watershed scale using the REML-EBLUP approach.     

X-ray active galactic nuclei in the core of the Perseus cluster

We present a study of the X-ray emission from the nuclei of galaxies observed in the core of the Perseus cluster in a deep exposure with Chandra . Point sources are found coincident with the nuclei of 13 early-type galaxies, as well as the central galaxy NGC 1275. This corresponds to all galaxies brighter than M _B > −18 in the Chandra field. All of these sources have a steep power-law spectral component and four have an additional thermal component. The unabsorbed power-law luminosities in the 0.5–7.0 keV band range from 8 × 10³⁸ to 5 × 10⁴⁰ erg s⁻¹. We find no simple correlations between the K -band luminosity, or the FUV and NUV AB magnitudes of these galaxies and their X-ray properties. We have estimated the black hole masses of the nuclei using the K -band   M _BH– L _{K bol}  relation and again find no correlation between black hole mass and the X-ray luminosity. Bondi accretion on to the black holes in the galaxies with minihaloes should make them much more luminous than observed.     

Delineation of hydrologically similar units in a watershed based on fuzzy classification of soil hydraulic properties

Evaluation of flow and transport processes in a watershed‐scale requires that the watershed be divided into homogenous spatial units referred to as hydrologically similar units (HSUs). Although a few discretization schemes are already in use, a universally acceptable method of obtaining HSUs is yet to emerge. In this study, we developed a fuzzy inference system (FIS) to classify the saturated hydraulic conductivity (K_s) and two water‐retention parameters α and n into fuzzy logic‐based soil hydrologic classes (FSHCs). Analysis of these classes showed that soil properties within an FSHC have less variability and those between two FSHCs have large variability. This result suggested that soils belonging to a specific FSHC may be more similar than those across different FSHCs and may be grouped together to represent an HSU. Soils within a specific hydrologic class were aggregated to delineate HSUs within the watershed. For the Dengei Pahad micro‐watershed (DPW), this approach showed five distinct regions representing a discretized zone having similar soil hydraulic properties. Application of this approach on a larger international database of soil hydraulic properties revealed that the developed hydrologic classes are quite comparable across different databases. The delineated HSUs based on these FSHCs were also better than the soil series map of the watershed in maintaining the soil heterogeneity of the watershed. Moreover, this new discretization scheme using the SWAT modelling environment showed better performance than the soil series‐based discretization approach. Copyright © 2010 John Wiley & Sons, Ltd.     

Recycled concrete aggregate coated with quaternary ammonium compounds for water disinfection

Growing demand for point-of-use water treatment including greywater recycling as well as appropriate disinfection without formation of harmful disinfection byproducts (DBPs) calls for new methods of efficient microbial control. In recent years, antimicrobial nanomaterials (NMs) have been widely studied as a potential alternative to traditional chlorine disinfection, yet concerns over their releases to environments and subsequent impacts have limited their use on a large scale. In this work, recycled concrete aggregate (RCA) was proposed as a sustainable and environmentally friendly disinfecting substrate for water disinfection by coating with a composite of silica-quaternary ammonium compound (Fixed-Quat). Two different types (gel and particle) of Fixed-Quat were applied to RCA, and their adherence and antimicrobial activities were compared each other. When using E. Coli as a model bacterial pathogen, the Fixed-Quat gel and particle coated RCA materials showed similar and effective microbial inactivation performance with a rate of 2.0 × 10^?3 (gel) and 1.82 × 10^?3 (particle) log reduction cm^?2 min^?1. By potentially eliminating regulated DBPs formation and minimizing release of NMs into the environment, the antimicrobial coated RCA would be a promising and sustainable alternative to conventional disinfection methods in engineered aquatic systems.