ID: 50827
Title: A global map of rainfed cropland areas (GMRCA) at the end of last millennium using remote sensing
Author: Chandrashekhar M. Biradar, Prasad S. Thenkabail, Praveen Noojipady, Yuanjie Li, Venkateswarlu Dheeravath, Hugh Turral, Manohar Velpuri, Murali K. Gumma, Obi Reddy P. Gangalakunta, Xueliang L. Cai, Xiangming Xiao, Mitchell A. Schull, Ranjith D. Alanka
Editor: Alfred Stein
Year: 2009
Publisher: Elsevier, Volume 11, issue 2, April 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Global mapping, GMRCA, Rainfed and irrigated croplands, Remote sensing, sub-pixel areas
Abstract: The overarching goal of this study was to produce a global map of rainfed cropland areas (GMRCA) and calculate country-by-country rainfed area statistics using remote sensing data. A suite of spatial datasets, methods and protocols for mapping GMRCA were described. These consist of :(a) data fusion and composition of multi-resolution time -series mega-file data-cube (MFDC), (b) image segmentation based on precipitaion, temperature and elevation zones, (c) spectral correlation similarity (SCS), (d) protocols for class indentification and labeling through uses of SCS R2 -values , bi-spectral plots, space-time spiral curves (ST-SCs), rich source of field-plot data and zoom -in-views of Google Earth (GE) and (e) techbiques for resolving mixed classes by decision tree algorithms and spatial modeling. The outcome was a 9-class GMRCA from which country - by- country rainfed area statistics were computed for the end of the last millennium. The global rainfed cropland area estimate from the GMRCA 9-class map was 1.13 billion hectares (Bha). The total global cropland areas (rainfed plus irrigated) was 1.53 Bha which was close to national statistics complied by FAOSTAT (1.51 Bha). The accuracies and errors of GMRCA were assessed using field- plot and Google Earth data points. The accuracy varied between 92 and 98% with kappa value of about 0.76, errors of omission of 2-8% and the errors of commission of 19-36%.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 50826
Title: Study of the intensity of super cyclonic storm GONU using satellite observations
Author: K.Muni Krishna, S. Ramalingeswara Rao
Editor: Alfred Stein
Year: 2009
Publisher: Elsevier, Volume 11, issue 2, April 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Tropical microwave imager (TMI), SST, Surface latent heat flux, Wind speed, Precipitation rate, GONU
Abstract: Satellite microwave measurements show sea surface temperature (SST) increase in advance of significant cyclone intensification. Moreover, cyclone intensification may also be related to the location of high SST. In the present study results indicate pre-existing high sea surface temperature anomaly (SSTA) located at the right side of the storm track for Cyclone GONU. I emphasize that high SST which occured at the right time and right place was conducive to the cyclone intensification. In particular, high SST in the northeastern quadrant of the storm track induced significant increases in surface latent heat fluxed contributing to the rapid intensification of GONU. The present study alos focuses on the air-sea interactions associated with cyclone GONU. Surface latent heat flux (SLHF) and precipitation rate (PR) increase anomalously prior to landfall as compared to when the GONU was at its maximum intensity (category 5). Wind speed rain-rate data from satellite observations show breakup of the eye-wall and asymmetric structure leading to increased precipitation prior to landfall.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 50825
Title: Estimating sagebrush cover in semi-arid environments using Landsat Thematic Mapper data
Author: Ramesh Sivanpillae, Steven D.Prager, Thomas O. Storey
Editor: Alfred Stein
Year: 2009
Publisher: Elsevier, Volume 11, issue 2, April 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Pinedale, Logistic regression, Mule deer , Remote sensing, Sage grouse
Abstract: Sagebrush ecosystems of the western US provide important habitat for several ungulate and vertebrate species. As a consequence of energy development, these ecosystem in Wyoming have been subjected to a variety of anthropogenic disturbances. Land managers require methodology that will allow them to consistently catalog sagebrush ecosystems and evaluate potential impact of proposed anthropogenic activities. This study addresses the utility of remotely sensed and ancillary geospatial data to estimate sagebrush cover using ordinal logistic regression. We demonstrate statistically significant prediction of ordinal sagebrush cover categories using spectral ( X2 = 113; p<0.0001) and transformed indices ( X2 = 117; p<0.0001). Both Landsat spectral bands (c-value =0.88) and transformed indices (c- value = 0.89) can distinguish sites with closed, moderate and open cover sagebrush cover categories from no cover. The techniques described in this study can be used for estimating categories of sagebrush cover in arid ecosystems.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 50824
Title: Modification of fractal algorithm for oil spill detection from RADARSAT-1 SAR data
Author: Maged Marghany, Arthur P.Cracknell, Mazlan Hashim
Editor: Alfred Stein
Year: 2009
Publisher: Elsevier, Volume 11, issue 2, April 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: RADARSAT-1 SAR, S2 mode data, W1 mode data, oil spill, Lood-alike, Low wind zone, Fractal dimension
Abstract: This paper introduces a modified formula for the fractal box counting dimension. The method is based on 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. surface and look-alikes in RADARSAT-1 SAR Wide beam mode (W1) and Standard beam mode (S2) data have been collected under different wind speeds. The results show that the new formula of the fractal box counting dimension is able to discriminate between oil spills, lood - alike areas and pixels of the size of a single ship. The W1 mode data illustrate an error standard deviation of 0.05, thus performing a better discrimination of oil spills as compared to S2 mode data. We conclude that automatic detection and discrimination of oil spill and other sea surface features can be opertionalized by using the new formula for fractal bow counting.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 50823
Title: Margin - based feature selection for hyperspectral data
Author: Mahesh Pal
Editor: Alfred Stein
Year: 2009
Publisher: Elsevier, Volume 11, issue 3, June 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Feature selection, Margin, Support vector machines, Classification accuracy
Abstract: A margin - based feature selection approach is explored for hyperspectral data. This approach is based on measuring the confidence of a classifier when making predictions on a test data. Greedy feature flip and iterative search algorithms, which attempts to maximise the margin-based evaluation functions , were used in the present study. Evaluation functions use linear, zero- one and sigmoid utility functions where a utility function controls the contribution of each margin term to the overall score. The results obtained by margin - based feature selection technique were compared to a support vector machine - based recurring feature elimination approach. Two different hyperspectral data sets, one consisting of 65 bands (DAIS data) and other with 185 bands (AVIRIS data ) were used. With digital airborne imaging spectrometer (DAIS) data, the classification accuracy by greedy feature flip algorithm and sigmoid utility function was 93.02% using a total of 24 selected features in comparison to an accuracy of 91.76% with full set of 65 features. The results suggest a significant increase in classification accuracy with 24 selected features. The classification accuracy (93.4%) achieved by the iterative search margin-based algorithm with 20 selected features using sigmoid utility function is also significantly more accurate than that achieved with 65 features. To judge the usefulness of margin-based feature selection approaches, another hyperspectral data set consisting of 185 features was used. A total of 65 selected features were used to evaluate the performance of margin-based feature selection approach. The results suggest a significantly improved performance by greedy feature flip-based feature selection technique with this data set also. This study also suggest that margin-based feature selection algorithms provide a comparable performance to support vector machine-based recurring feature elimination approach.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 50822
Title: Mapping beech (Fagus sylvatica L.) forest structure with airborne hyperspectral imagery
Author: Moses Azong Cho, Andrew K. Skidmore, Istiak Sobhan
Editor: Alfred Stein
Year: 2009
Publisher: Elsevier, Volume 11, issue 3, June 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Forest structure, Diameter-at-breast height, Tree height, Tree density, Vegetation indices, Hyperspectral imagery, Partial least square regression, Spatial structure
Abstract: Estimating forest structural attributes using multispectral remote sensing is challenging because of the saturation of multispectral indices at high canopy cover. The objective of this study was to assess the utility of hyperspectral data in estimating and mapping forest structural parameters including mean diameter-at-breast height (DBH), mean tree height and tree density of a closed canopy beech forest (Fagus sylvatica L.). Airborne HyMap images and data on forest structural attributes were collected from the Majella National Park, Italy in July 2004. The predictive performances of vegetation indices (VI) derived from all possible two -band combinations VI(ij) = (Ri - Rj )/( Ri + Rj ),where Ri and Rj = reflectance in any two bands) were evaluated using calibration (n=33) and test (n=20) data sets. The potential of partial least squares (PLS) regression, a multivariate technique involving several bands was also assessed. New VIs based on the contrast between reflectance in the red-edge shoulder (756-820 nm) and the water absorption feature centred at 1200 nm ( 1172 - 1320 nm) were found to show higher correlations with the forest structural parameters than standard VIs derived from NIR and visible reflectance (i.e. the normalised difference vegetation index, NDVI). PLS regression showed a slight improvement in estimating the beech forest structural attributes (prediction errors of 27.6% , 32.6% and 46.4% for mean DBH, height and tree density, respectively) compared to VIs using linear regression models (prediction errors of 27.8%, 35.8% and 48.3% for mean DBH,height and tree density, respectively). Mean DBH was the best predicted variable among the stand parameters (calibration R2 = 0.62 for an exponential model fit and standard error of prediction = 5.12cm, i.e.25% of the mean).The predicted map of mean DBH revealed high heterogeneity in the beech forest structure in the study area. The spatial variability of mean DBH occurs at less than 450 m. The DBH map could be useful to forest management in many ways, e.g. thinning of coppice to promote diameter growth, to assess the effects of management on forest structure or to detect changes in the forest structure caused by anthropogenic and natural factors.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 50821
Title: The use of selected pseudo - invariant targets for the application of atmospheric correction in multi -temporal studies using satillite remotely sensed imagery
Author: D.G.Hadjimitsis,C.R.I.Clayton, A.Retalis
Editor: Alfred Stein
Year: 2009
Publisher: Elsevier, Volume 11, issue 3, June 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Atmosperic correction, Pseudo-invariant targets, Empirical line method, Dark target, Light target, Reflectance, Remote sensing
Abstract: Because atmospheric effects can have a significant impact on the data obtained from multi-spectral satellite remote sensing. It is frequently necessary to make corrections before any other image processing can be started. This paper describes a robust and relatively simple atmospheric correction method that uses pseudo-invariant targets (PITs) in conjunction with the empirical line method. The method is based on the selection of a number of suitable generic PITs, on the basis that they are large, distinctive in shape and occur in many geographical areas. Whereas the multi-temporal normalization method corrects all images to a selected reference image, in this method images are simultaneously corrected using targets with a range of estimated surface reflectance values. The paper describes some applications of the method for a range of environmental studies involving water quality and air pollution monitoring and mapping land-cover changes.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 50820
Title: Landslide inventory using image fusion techniques in Brazil
Author: Emerson Vieira Marcelino, Antonio Roberto Formaggio, Eduardo Eiji Maeda
Editor: Alfred Stein
Year: 2009
Publisher: Elsevier ,Volume 11, issue 3, June 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Landslide, Inventory map, Image fusion, Brazil
Abstract: The present work aims to assess the accuracy of six fusion techniques (Brovey,IHS, HSV, PCA,WTYO and WTVE) in order to compile landslide inventories using orbital images (ETM +and PAN HRV). The study area is characterized by steep terrain and dense forest in Caraguatatuba, Sao Paulo State, Brazil. In terms of spatial quality, the Wavelet Transform technique provided the best results, presenting correlations above 90%. As for spectral quality, the best results were obtained with the IHS fusion. Based on the results, it may be concluded that the IHS is the best technique for preserving spatial and spectral information from the original images, so as to more clearly identify landslide scars. However, it was still not possible to typify the landslides from remote sensing data. Nonetheless , it is believed that image fusion techniques adequately met expectations in terms of their capacity to identify landslide for the creation of an inventory for the studied area.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 50819
Title: Fusion of PolSAR and PollnSAR data for land cover classification
Author: M.Shimoni, D.Borghys, R.Heremans, C.Perneel, M.Acheroy
Editor: Alfred Stein
Year: 2009
Publisher: Elsevier ,Volume 11, issue 3, June 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: polSAR, pollnSAR, Fusion, Neural network architecture, Land cover classification, Feature extraction
Abstract: The main research goal of this study is to investigate the complementarity and fusion of different frequencies (L- and P- band), polarimetric SAR (polSAR) and polarimetric interferometric (pollnSAR) data for land cover classification. A large feature set was derived from each of these four modalities and a two-level fusion method was developed: Logistic regression (LR) as ' feature-level fusion ' and the neural network (NN) method for higher level fusion. For comparison, a support vector machine (SVM) was also applied. NN and SVM were applied on various combinations of the feature sets. The results show that for both NN and SVM, the overall accuracy for each of the fused sets is better than the accuracy for the separate feature sets.Moreover, that fused features from different SAR frequencies are complementary and adequate for land cover classification and that pollnSAR is complementary to polSAR information and that both are essential for producing accurate land cover classification.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 50818
Title: Impact of Heavy Metal Pollution on Revelry Ecology from River Tajan
Author: Hasanzadeh Hosseinabadi Hasan
Editor: P.K.Wong, R.K.Trivedy, Sadhana Sharma
Year: 2008
Publisher: Asian Journal of Microbiology, Biotechnology & Environmental Sciences (AJMBES) Vol.10, No.3, 2008
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Asian Journal of Microbiology, Biotechnology, Environmental Sciences
Keywords: Heavy metal, River pollution, River sediment
Abstract: The present study on the determination and distribution of heavy metal concentration, i.e., Pb, Cu, Cr, Cd, Fe, Ni, Mn and Zn in water and in bed sediments of river Tajan have been studied from Alborze origin of river to join Caspian sea ( a stretch of about 145 km. sq). Water and sediment samples were collected from 18 sampling stations at upstream, middle and downstream. These heavy metals were determined at monthly intervals for a period of October 2005 to September 2006 using Atomic Absorption Spectrophotometer (A.A.S). In the water and sediments of river Tajan varies in it ' s downstream at various points as most of the industries discharging heavy metals are situated in this area. Dilution during autumn season decreased the metal level even below the prescribed limit. The study reveals that monthly and seasonal average values of sampling stations of the river values may cross the tolerance limit if their inflow though domestic and industrial wastes is checked. Present observations revealed high concentrations of heavy metals at downstream sites, because huge quantity of partially domestic sewage and industrial effluents were discharged into the river at all these sites. While in sediments contents of these metals showed considerable variation at different sampling sites. This may be due to precipitation and sedimentation of these metals. It may be concluded that downstream sampling stations got more polluted than upstream sampling stations. The results of the analysis level that all the heavy metals at eighteen stations to compared of standards heavy metals in the order of their relative dominal were in the sequence Cr>Mn>Fe>Ni>Zn>Pb>Cd>Cu in water river and Mn>Cr>Zn>Ni>Cu>Pb>Cd>Fe in the sediment of river Tajan.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 50817
Title: Detection of Antibodies against Canine distemper Virus using Competitive ELISA
Author: S. Ramya, T.Pugalendhi, G.Dhinakar Raj and M.S. Shaila
Editor: P.K.Wong, R.K.Trivedy, Sadhana Sharma
Year: 2008
Publisher: Asian Journal of Microbiology, Biotechnology & Environmental Sciences (AJMBES) Vol.10, No.3, 2008
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Asian Journal of Microbiology, Biotechnology, Environmental Sciences
Keywords: Canine distemper virus, competitive ELISA , rinder pest virus, Morbillivirus
Abstract: Canini Distemper Virus (CDV) infection causes a frequently fatal systemic disease in a broad range of carnivore species, including domestic dogs. Various virologic and serologic methods are used for the diagnosis of the disease. In this study, competitive ELISA with monoclonal antibodies and mono - specific rabbit serum was used to detect the antibodies of CDV in dogs aged from 3 to more than 12 months. A total of 70 serum were tested, of which the cELISA showed a maximum of 79.4% antibodies to CDV with rabbit serum. Maximum prevalence of antibody was observed in the dogs of age group between 10 -12 months. However there was no correlation between the prevalence of CDV antibodies and the ages of dogs sampled. The result also indicates that vaccinated dogs produced a maximum number of positive (82%) with rabbit serum than the unvaccinated dogs. The cELISA was 68.5% sensitive and 75% specific. Futher, it has been confirmed that the competitive ELISA and was highly specific and sensitive and practically applicable method to detect CDV antibodies.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 50816
Title: Decolorization of Purple 2R by Aspergillus ochraceus (NCIM -1146)
Author: R.P.Humnabadkar, G.D. Saratale and S.P. Govindwar
Editor: P.K.Wong, R.K.Trivedy, Sadhana Sharma
Year: 2008
Publisher: Asian Journal of Microbiology, Biotechnology & Environmental Sciences (AJMBES) Vol.10, No.3, 2008
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Asian Journal of Microbiology, Biotechnology, Environmental Sciences
Keywords: Dye decolorization, Aspergillus ochraceus, purple 2R, agitation,phytotoxicity
Abstract: Aspergillus ochraceus (NCIM -1146) have ability to decolorize various textile dyes viz. purple 2R, orange TG22, yellow HE64, red HE7B and golden yellow HER was determined with Aspergillus ochraceus (NCIM -1146) by monitoring the decrease in absorbance of each dye in the culture supernatant. Decolorization performance of purple 2R with various conditions such as; different media, concentration of dye, agitation and static conditions were studied. The decrease in dye decolorization capability of mycelium was observed with increasing dye concentration in repeated batch mode. Spectrophotometric data revealed that the process involved in decolorization is through microbial metabolism but not biosorption. Phytotoxicity study demonstrated no toxicity of the biodegraded products for plants with respect to Phaseolus mungo and Sorghum vulgarae. This study suggests that Aspergillus ochraceus could be a useful tool for textile effluent treatment and the alternative to the traditional physicochemical process.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 50815
Title: Ecological Category of Earthworms of the Western Ghats
Author: P.Kathireswari and R. Jeyaraaj
Editor: P.K.Wong, R.K.Trivedy, Sadhana Sharma
Year: 2008
Publisher: Asian Journal of Microbiology, Biotechnology & Environmental Sciences (AJMBES) Vol.10, No.3, 2008
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Asian Journal of Microbiology, Biotechnology, Environmental Sciences
Keywords: Ecological Category, Epigeic, Anecic, Endogeic, Western ghats
Abstract: The Western Ghats is home for rich diversity of flora and fauna and is recognized as one of the 25 biodiversity ' hot spots ' of the world. Our study area, the Coimbatore forest division of the Western Ghats has complex topography, high rainfall and warm humid tropical climate for habitat of 3 main ecological categories of 13 epigeic, 5 anecic and 20 endogeics earthworms. Based on the functional approach its again sub categorized into Epigeic, Epi-anecic, Aneic,Endo polyhumic, Endo mesohumic, Endo- anecic and Endo oligohumic which have different effects on soil function.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 50814
Title: A Study on Assessment on Pollution Load from Dairy Effluent
Author: Dhamotharan .R, Murugesan. S, kamaleswari.J and Dhamodhar Kumar
Editor: P.K.Wong, R.K.Trivedy, Sadhana Sharma
Year: 2008
Publisher: Asian Journal of Microbiology, Biotechnology & Environmental Sciences (AJMBES) Vol.10, No.3, 2008
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Asian Journal of Microbiology, Biotechnology, Environmental Sciences
Keywords: pollution assessment- Dairy effluent - Green alga
Abstract: Biodegradation is increasingly being considered as a less expensive alternative to physical and chemical means of decomposing organic pollutants. Pathways of biodegradation have been characterized for a number of microorganisms, some of whidh have been used for remediation of wastewater. Since algae are photo autotrophic their use for bioremediation of surface waters would circumvent the need to supply biodegradative heterotrophs with organic nutrients. This paper demonstrates that green alga Scenedesmus bijugatus have a natural ability to degrade dairy wastewater.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 50813
Title: Serum Enzyme infuence due to aflatoxicosis and role of herbal toxin binders in counteracting the toxicity on breeding Japanese Quails (Coturnix coturnix japonica)
Author: R. Kungumapriya and K.Revathi
Editor: P.K.Wong, R.K.Trivedy, Sadhana Sharma
Year: 2008
Publisher: Asian Journal of Microbiology, Biotechnology & Environmental Sciences (AJMBES) Vol.10, No.3, 2008
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Asian Journal of Microbiology, Biotechnology, Environmental Sciences
Keywords: Mycotoxins, Aflatoxicosis, Azadirachta indica, Cynodon dactylon, Curcuma longa, Japanese quail, Poultry feed
Abstract: Mycotoxins play a global role in human and animal health. Aflatoxins cause malperformance, metabolic disorders and pathologic alterations in different species of poultry. Various species of poultry differ in susceptibility to acute and sub- acute aflatoxicosis. This work was carried out to study the role of locally available herbal plant extracts such as Azadirachta indica, Cynodon dactylon and Curcuma longa in counteracting the effects of experimental aflatoxicosis in laying Japanese quail by feeding them with diets containing aflatoxin at 1.5 and 3 ppm levels for a period of six weeks.
Location: 241
Literature cited 1: None
Literature cited 2: None