ID: 52372
Title: Detection of antibiotics in hospital effluents in India
Author: Vishal Diwan, Ashok J. Tamhankar, Manjeet Aggarwal, Shanta Sen, Rakesh K.Khandal and Cecilia Stalsby Lundborg
Editor: P.Balaram
Year: 2009
Publisher: Current Sicence Association , Vol 97, No 12, 25 December 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Current Science
Keywords: Antibiotic residues, ceftriaxone, fluoroquinolones, hospital effluents, India
Abstract: Occurence of antibiotics was investigated in water associated with two hopitals in Ujjain district, India. Samples of hospital associated water were subjected to solid phase extraction combined with high pressure liquid chromatography-tandem mass spectrometry (LC-MS/MS), to estimate antibiotics in incoming safe water, hospital wastewater and groundwater. The incoming safe water and groundwater were free of antibiotics; however, metronidazole, norfloxacin, sulphamethoxazole, ceftriaxone, ofloxacin, ciprofloxacin, levofloxacin and tinidazole were detected in the range of 1.4-236.6 ?g-1 in hospital effluents. Contamination of aquatic environment by antibiotic usage in hospitals has serious implications on public health and environment.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 52371
Title: Analysis of seismicity-induced landslides due to the 8 October 2005 earthquake in Kashmir Himalaya
Author: P.K.Champati Ray, I.Parvaiz, R.Jayangondaperumal, V.C.Thakur, V.K.Dadhwal and F.A.Bhat
Editor: P.Balaram
Year: 2009
Publisher: Current Sicence Association , Vol 97, No 12, 25 December 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Current Science
Keywords: Earthquake, landslide, probability density function, satellite images, statistical analysis
Abstract: Widespread landslides were reported in the devastating earthquake of 7.6 Mw
that occurred on 8 October 2005 with epicentre located within Hazara syntaxis, Kashmir Himalaya. As this area covers mostly inaccessible mountains terrain, an attempt was made to detect and map landslides on medium to high resolution satellite data products such as Indian Cartosat-1 (PAN:2.5m resolution), Resourcesat-1 (LISS IV: 5.8 m multi-spectral), Landsat-TM (30m multispectral) and ASTER (15m multispectral). The extent of slope failures and landslides was mapped (776 landslides) based on subpixel registration, image interpretation and field investigation. The ground deformation cum damage survey revealed that the hanging wall side of the causative fault was severely affected and caused numerous earthquake-triggered landslides. The terrain parameters such as surface geology, slope gradient, slope aspect, curvature and relief classes were correlated with actual landslide occurrences and critical classes were identified. The statistical analysis of landslides inventory based on probability density function enabled estimation of earthquake magnitude and size of the largest landslide, which correspond well to the actual data. The study demonstrated extrapolation of total landslide affected area (67.36 km2) from the partial inventory of landslides based on satellite image interpretation. Based on the volumetric estimation, average landslide thickness was determined to be around 6.9-7.7 m and total displaced mass available for erosion was also estimated to be around 0.34-0.52 km3.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 52370
Title: Spatial and temporal variation of water vapour in upper troposphere and lower stratosphere over Indian region
Author: C.J.Johny, S.K.Sarkar and D.Punyaseshudu
Editor: P.Balaram
Year: 2009
Publisher: Current Sicence Association , Vol 97, No 12, 25 December 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Current Science
Keywords: Troposhere and stratosphere transport, upper troposphere and lower stratoshpere, water vapour
Abstract: Spatial and temporal distribution of water vapour in the upper troposphere and lower stratosphere (UTLS) region over India including Arabian Sea and Bay of Bengal is presented using COSMIC/FORMOSAT 3 radio occultation measurements. Water vapour plays a crucial role in many aspects of UTLS chemistry. The influence of Asian summer monsoon can be seen in the seasonal pattern of water vapour in the UTLS region. It is observed that water vapour in the lower stratosphere follows the seasonal cycle in upper tropospheric water vapour with a time lag of one month. The time scale of cross tropopause transport of air mass in the region is also discussed.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 52369
Title: Diatoms: a potential tool to understand past oceanographic settings
Author: Sunil Kumar Shukla, Rahul Mohan and M.Sudhakar
Editor: P.Balaram
Year: 2009
Publisher: Current Sicence Association , Vol 97, No 12, 25 December 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Current Science
Keywords: Diatoms, palaeoceanography, sediment, tracers
Abstract: Diatoms are being potentially used to decipher palaeoceanography and past climatic changes. They are marine primary producers which play an important role in carbon, silica and nutrient budgets of modern oceans. Their importance lies in the role they play for the export of organic carbon to the deep sea and the efficiency of the biological pump for CO2 exchange. They are useful as biostratigraphical zone fossils in marine deposits from high latitudes or at deeper water depths, both of which lack calcareous microfossils. The role of diatoms as tracers of past oceanographic conditions with recent perspectives in diatom research is reviewed in this article .
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 52368
Title: Promoting S & T in rural India - challenges and plausible solutions
Author: Madhav G. Deo
Editor: P.Balaram
Year: 2009
Publisher: Current Sicence Association , Vol 97, No 12, 25 December 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Current Science
Keywords: Outreach programmes, RISER, rural India, S & T
Abstract: Lack of science and technology (S&T) education and research amenities is the root cause of rural backwardness resulting in villages being treated as ' colonies ' for urban goods. Although tremendous strides have been made in S&T in post-independence India, development is mainly focused on creating big S&T institutions and upgrading S&T infrastructure in major cities ( ' big science ' , macro-S&T). Rural India, which still accounts for 70% of the nation ' s population, has been grossly ignored. There is an urgent need to implement the notion of ' small science ' (micro-S&T) tailored for the rural sector to make villagers self-reliant. A beginning could be made by aggressively promoting outreach programmes in modern science education and research for young village students. Also, steps should be taken to establish a number of modest Rural Institute of Science Education and Research (sort of mini-IISER) spread all over the country with the ultimate goal of ' science for all ' . In the present setting, competition between rural and urban youth is uneven and unjust. It is time we provide villagers a level playing field and take them on board as equal partners. This is the only way to prevent emergence of two sub-nations ' Bharat ' and ' India ' .
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 52367
Title: Mycological foray: a culture missing in our country
Author: N.D.Sharma
Editor: P.Balaram
Year: 2009
Publisher: Current Sicence Association , Vol 97, No 12, 25 December 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Current Science
Keywords: None
Abstract: None
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 52366
Title: Role of food chain containing lactic acid bacteria in antibiotic resistance
Author: Vijendra Mishra, Akhilesh Upgade, K.P.Sharma
Editor: P.Balaram
Year: 2009
Publisher: Current Sicence Association , Vol 97, No 12, 25 December 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Current Science
Keywords: None
Abstract: None
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 52365
Title: Interactive and Automated Segmentation and Generalisation of Raster Data
Author: Kazemi S, Lim S and Rizos C
Editor: Dr. Nitin Kumar Tripathi
Year: 2009
Publisher: Association for Geoinformation Technology, Vol 5, No 3, September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Geoinformatics
Keywords: Raster data, Automated Segmentation and Raster Generalisation Framework (IASRGF), Kappa index
Abstract: This paper review past and current research activity in the area of generalisation of spatial data and presents a new methodological framework for segmentation and generalisation of raster data. In order to overcome drawbacks associated with supervised classification and generalisation of raster data, an Interactive Automated Segmentation and Raster Generalisation Framework (IASRGF) was developed and tested. Test results of the IASGRF shows that all objects derived from the generalisation of landuse data over Canberra, Australia, were well classified and mapped. The error assessment indicates that the percentile classification accuracy is 85.5%, whereas the commission error is relatively high (38.5%). More importantly, the maximum likelihood classifier using training sites and associated ground truth data suggests that the Kappa index is 0.798, which can be interpreted as a reliable and satisfactory classification result. In order to further enhance supervised classification, a post-classification was carried out. As a result, this extra process improved the overall classification accuracy slightly, however its commission error also increased by 6%.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 52364
Title: Artificial Neural Network Based Coral Cover Classifiers using Indian Remote Sensing (IRS LISS-III) Sensor Data: A Case Study in Gulf of Kachcch, India
Author: Bandyopadhyay S, Sharma S and Bahuguna A
Editor: Dr. Nitin Kumar Tripathi
Year: 2009
Publisher: Association for Geoinformation Technology, Vol 5, No 3, September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Geoinformatics
Keywords: Artificial network, coral reef, IRS P6 LISS III satellite data
Abstract: Artificial neural network have become popular in classification of remotely sensed satellite data where they demonstrate better accuracy than conventional methods. A back propagation neural network algorithm has been developed to classify eco-morphological zonation of coral reef as well as benthic communities. IRS P6 LISS III satellite data of March 2, 2006 has been used to map coral reefs using hybrid analysis of user based knowledge. The traditional method used for classification of coral reefs gives substantial amount of mis-classifications due to the similarity in reflectance values. The optimized neural network, made for the classification of coral reef image with high rate of noise, shows a better accuracy, as it is able to remove mis-classifications up to certain extent. The developed classifier uses the radiance values of 300 homogeneous pure pixels per class as training samples from a radiometrically and geometrically corrected image of the study area. The optimized network was applied on the complete coral reef image. Accuracy was checked by cross validating ground truth data which showed considerable improvement (84% at 90% confidence level to 91.14% at 90% confidence level) in mis-classification.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 52363
Title: Land Surface Temperature with Land Cover Dynamics: Multi-Resolution, Spatio-Temporal Data Analysis of Greater Bangalore, India
Author: Ramachandra T.V and Uttam Kumar
Editor: Dr. Nitin Kumar Tripathi
Year: 2009
Publisher: Association for Geoinformation Technology, Vol 5, No 3, September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Geoinformatics
Keywords: Urban flooding, climate change, Land surface temperature (LST), Bangalore
Abstract: Bangalore is experiencing unprecedented urbanisation in recent times due to concentrated developmental activities with impetus on IT (Information Technology) and BT (Biotechnology) sectors. The concentrated developmental activities has resulted in the increase in population and consequent pressure on infrastructure, natural resources, ultimately giving rise to a plethora of serious challenges such as urban flooding, climate change, etc. One of the perceived impact at local levels is the increase in sensible heat flux from the land surface to hte atmosphere, which is also referred as heat island effect. In this communication, we report the changes in land surface temperature (LST) with respect to land cover changes during 1973 to 2007. A novel technique combining the information from sub-pixel class proportions with information from classified image (using signatures of the respective classes collected from the ground) has been used to achieve more reliable classification. The analysis showed positive correlation with the increase in paved surfaces and LST. 466% increase in paved surfaces (buildings, roads etc) has lead to the increase in LST by about 20C during the last 2 decades, confirming urban heat island phenomenon. LSTs were relatively lower (~4 to 70C) at land uses such as vegetation (parks/forests) and water bodies which act as heat sinks.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 52362
Title: Impacts of Agricultural Expansion on Surface Runoff: A Case Study of a River Basin in the Brazilian Legal Amazon
Author: Maeda E.E, Formaggio A.R, Shimabukuro Y.E and Kaleita A.L
Editor: Dr. Nitin Kumar Tripathi
Year: 2009
Publisher: Association for Geoinformation Technology, Vol 5, No 3, September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Geoinformatics
Keywords: Land Use , Land Cover, LULC, Suia-Micu River basin, SCS curve number method,Automated Geospatial Watershed Assessment Tool (AGWA)
Abstract: This work presents an analysis of the Land Use and Land Cover (LULC) changes of a region in the Brazilian Legal Amazon, and an evaluation of their impacts on the surface runoff regime. This case study took place at the Suia-Micu River basin, located in the northeast region of Mato Grosso State. LULC maps were produced for the years 1973, 1984 and 2005 using remote sensing data. After analyzing the agricultural expansion in the study area, the Automated Geospatial Watershed Assessment Tool (AGWA) was applied in performing the surface runoff modeling for each of the analyzed years using the SCS curve number method. The results showed that by 1984, 13% of the natural vegetation had been replaced by pasture in this drainage basin. These changes were responsible for a 5.7% increase in the annual surface runoff volume when compared with the baseline values of 1973. In 2005, the agricultural areas increased to around 40% of the drainage basin, being 28% occupied by pasture and 12% by crop fields. In this last scenario, the annual average surface runoff was 37% higher than in 1973.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 52361
Title: Fractal Dimension Algorithm for Oil Spill and Look-Alike Detections using RADARSAT-1 SAR and AIRSAR/POLSAR Data
Author: Marghany M, Cracknell A P and Hashim M
Editor: Dr. Nitin Kumar Tripathi
Year: 2009
Publisher: Association for Geoinformation Technology, Vol 5, No 3, September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Geoinformatics
Keywords: Sythetic aperture radar (SAR), oil spill, RADARSAT-1 SAR S2 mode , AIRSARdata, POLSAR data
Abstract: Automatic detection of oil spill and look-alikes in sythetic aperture radar (SAR) is required standard procedures. In fact, oil spill and look-alike are appeared as dark patches in SAR data. This work utilizes a modification of the formula of the fractal box counting dimension in which divided a convoluted line of slick embedded in SAR data into small boxes. The method is based on the utilization of the probability distribution formula in the fractal box count. The purpose of this method is to use it for the discrimination of oil spill areas from the surrounding features e.g., sea surface and look-alikes in SAR data i.e. RADARSAT-1 SAR S2 mode and AIRSAR/POLSAR data. The results show that the modified formula of the fractal box counting dimension is able to discriminate between oil spills and look-alike areas. The low wind area has the highest fractal dimension peak of 2.9, as compared to the oil slick and the surrounding rough sea. Further, modified formula of fractal box counting dimension is also able to detect look-alikes and low wind zone areas in AIRSAR/POLSAR data. It is interesting to find out that oil spill is absent in AIRSAR/POLSAR data. Both SAR data have maximum error standard deviation of 0.45 which performs with fractal dimension value of 2.9. In conclusion, modification formula of fractal box counting dimension is promising method for oil spill automatic detection in different sensor of SAR data.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 52360
Title: The use of Back Propagating Artificial Neural Networks in Rare Vegetation Communities Classification from High-Resolution Satellite Imagery
Author: Hassanov H.G., Gambarov A.Y, and Gambarova Y.M
Editor: Dr. Nitin Kumar Tripathi
Year: 2009
Publisher: Association for Geoinformation Technology, Vol 5, No 3, September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Geoinformatics
Keywords: artificial neural networks (ANNs), Multi Layer Perceptron (MLP),
Abstract: This paper has presented artificial neural networks (ANNs) for rare vegetation communities ' classification using remotely sensed data. Three variants of training of the Multi Layer Perceptron (MLP) based on three different classification schemes are used. At first 12 types of rare vegetation communities were defined and the main classification scheme was designed on that basis. After preliminary statistical tests for training samples, two modification algorithms of the classification scheme were defined: the first one led to creating a scheme, which consisted of 7 classes and the second one led us to creating of 5 classes ' scheme. Testing results show that the use of ANNs of 5 classes ' scheme can produce higher classification accuracies than other alternative. The training procedures of these classifiers are described in details along with analysis and post processing products using Geoinformation Technologies. Ancillary geospatial data: DTM and its derivable (DEM, Slope, Aspect) as well as topographical, hydrological data and land use maps were created in order to support post classification operations. This result demonstrates that a level of classification accuracy achieved by artificial neural networks is higher than those generated by the statistical classifiers.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 52359
Title: Indexing PostGIS Databases and Spatial Query Performance Evaluations
Author: Nguyen T.T
Editor: Dr. Nitin Kumar Tripathi
Year: 2009
Publisher: Association for Geoinformation Technology, Vol 5, No 3, September 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Geoinformatics
Keywords: Geodatabases, GIS, Structured Query Language (SQL), Structured Query Language, ESRI website
Abstract: Geodatabases (also commonly known as geospatial databases) are central elements in spatial data infrastructures. The primary advantage over file-based data storage of spatial databases (access via GIS), is that they are structured to encompass existing capabilities of relational database management systems, including support for SQL (Structured Query Language) and the ability to generate complex geospatial queries. PostGIS is an extension to the PostgreSQL object-relational database system which allows GIS objects to be stored in the database. PostGIS comprises functions for basic analysis of GIS objects and more importantly, it also supports the spatial indexing schemes. Indexes are extremely important for large spatial tables, because they allow for quick retrieval of records during query. PostGIS is frequently used during analysis of large data sets if examination of spatial indexes is a particularly essential task. Reported here are results of indexing the PostGIS databases by adopting an R-Tree-over-GiST (Generalized Search Tree) scheme and evaluation of the performance of indexed and un-indexed spatial queries with respect to database size. Experiments were carried out with a huge amount of spatial data obtained from the ESRI website, and using the PgAdmin III tool, which is a comprehensive PostgreSQL database design and management system.Experimental results demonstrate approximately linear increase in spatial index building time as the size of tables increases, but, as the database size increases, processing time is very much greater if the spatial queries are not indexed. However, regardless of the size of the geodatabase, performance of spatial queries is highly sensitive to choice of geometric parameters that the queries refer to.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 52358
Title: Tree species identification in mixed coniferous forest using airborne laser scanning
Author: Agus Suratno, Carl Seielstad, Lloyd Queen
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: North America, Conifer, Laser scanning, Intensity, Tree species
Abstract: This study tests the capacity of relatively low density (<1 return/m2) airborne laser scanner data for discriminating between Douglas-fir, western larch, ponderosa pine, and lodgepole pine in a western North American montane forest and it evaluates the relative importance of intensity, height, and return type metrics for classifying tree species. Collectively, Exploratory Data Analysis, Pearson Correlation, ANOVA, and Linear Discriminant Analysis show that structural and intensity characteristics generated from LIDAR data are useful for classifying species at dominant and individual tree levels in multi-aged, mixed conifer forests. Proportions of return types and mean intensities are significantly different between species (p-value<0.001) for plot-level dominant species and individual trees. Classification accuracies based on single variables range from 49%-61% at the dominant species level and 37%-52% for individual trees. The accuracy can be improved to 95% and 68% respectively by using multiple variables. The inclusion of proportion of return type greatly improves the classification accuracy at the dominant species level, but not for individual trees, while canopy height improves the accuracy at both levels. Overall differences in intensity and return type between species largely reflect variations in the physical structure of trees and stands. These results are consistent with the findings of others and point to airborne laser scanning as a useful source of data for species classification. However, there are still many knowledge gaps that prevent accurate mapping of species using ALS data alone, particularly with relatively sparse datasets like the one used in this study. Further investigations using other datasets in different forest types will likely result in improvements to species identification and mapping for some time to come.
Location: 231
Literature cited 1: None
Literature cited 2: None