ID: 58563
Title: Convective thundercloud development over the Western Ghats mountain sloe in Kerala
Author: R Vishnu, V Anil Kumar, Hamza Varikoden, K Sarath Krishnan, T S Sreekanth, V N Subi Symon, S Murali Das and G Mohan Kumar
Editor: P. Balaram
Year: 2013
Publisher: Current Science Association, No 11, Vol 104, 10 June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: Current Science
Keywords: Convective Cbs, disaster, lightning, mountain weather, updraft
Abstract: Studies were carried out on the data from Braemore mountain observatory (lat. 8045 ' N, long. 7705 ' E) using a single-lens ceilometer (LIDAR), an electric field mill and a portable automatic weather station throughout the year 2010. The simultaneous data collected using the above instruments indicate the existence of strong updrafts followed by the formation of thunderclouds, a characteristic of the mountain slopes, during the thunderstorm months.Changes in atmosphere related to condensation and formation of water droplets during updraft events on the mountain slope could be detected from the ceilometer scattering data. Results of the study point to the cause of relatively more thunderstorm activity in that zone. This seems to be due to excessive updraft, which is strongly related to lightning activity in the region.
Location: TE15, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58562
Title: Losing threatened and rare wildlife to hunting in Ziro valley, Arunachal Pradesh, India
Author: K Muthamizh Selvan, Gopi Govindan Veeraswami, Bilal Habib and Salvador Lyngdoh
Editor: P. Balaram
Year: 2013
Publisher: Current Science Association, No 11, Vol 104, 10 June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: Current Science
Keywords: Apatani, Arunachal Pradesh, mammals, Wildlife hunting, Ziro valley
Abstract: Harvesting wild animals through hunting has become a major conservation issue, especially for large-bodied animals. We surveyed the Ziro valley in Arunachal Pradesh in order to assess the socio-ecnomic status and dependence of indigenous people on wildlife species. We used structured questionnaire for the survey and houses were selected randomly. Species hunted include common leopard, clouded leopard, marbled cat, leopard cat, spotted linsang, otter sp., yellow-throated marten, orange-bellied squirrel, Malayan giant squirrel, sambar, barking deer, wild pig and birds. Hunting was carried out mainly for subsistence (55%), commercial purposes (25%) and medicine (10%). There is an urgent need to assess the impact of wildlife hunting and the sustainability of such practices on the hunted species to aid in adopting strategies to improve the protection measures and making informed conservation decisions.
Location: TE15, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58561
Title: Shrimps - a nutritional perspective
Author: J Syama Dayal, A G Ponniah, H Imran Khan, E P Madhu Babu, K Ambasankar and K P Kumarguru Vasagam
Editor: P. Balaram
Year: 2013
Publisher: Current Science Association, No 11, Vol 104, 10 June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: Current Science
Keywords: Daily value, dietary cholesterol, nutritional composition, shrimp
Abstract: This article presents the nutritional value of shrimp on the strength of its nutrient composition and daily value (DV%). With its relatively lower lipid content (~1%), the DV(%) of 100g shrimp for an adult human is 75%, 70% and 35% for eicosapentonoic acid + docosahexanoic acid, essential amino acids (methionine, tryptophan and lysine) and protein respectively. The lower atherogenic (0.36) and thrombogenic (0.29) indices of shrimp show its cardio-protective nature. The controversy relating to shrimp cholesterol and the overall health benefits of eating shrimp are discussed to indicate that shrimp should be a regular item in the diet of normolipidemic peoples.
Location: TE15, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58560
Title: Modern salt (halite) deposits of the Sambhar lake, Rajasthan and their formative conditions
Author: B P Singh, Neha Singh, S P Singh
Editor: P. Balaram
Year: 2013
Publisher: Current Science Association, No 11, Vol 104, 10 June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: Current Science
Keywords: None
Abstract: None
Location: TE15, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58559
Title: Mountain tunnelling, aquifer and tectonics-a case study of Gran Sasso and its implications for the India-based Neutrino Observatory by V T Padmanabhan and Joseph Makkolil-a critique
Author: V Balachandran
Editor: P. Balaram
Year: 2013
Publisher: Current Science Association, No 11, Vol 104, 10 June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: Current Science
Keywords: None
Abstract: None
Location: TE15, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58558
Title: The case for banning endosulfan
Author: G K Mahapatro and Madhumita Panigrahi
Editor: P. Balaram
Year: 2013
Publisher: Current Science Association, No 11, Vol 104, 10 June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: Current Science
Keywords: None
Abstract: None
Location: TE15, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58557
Title: Conserving the endangered Mahseers (Tor spp) of India: the positive role of recreational fisheries
Author: Adrian C Pinder and Rajeev Raghavan
Editor: P. Balaram
Year: 2013
Publisher: Current Science Association, No 11, Vol 104, 10 June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: Current Science
Keywords: None
Abstract: None
Location: TE15, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58556
Title: Change detection from remotely sensed images: From pixel-based to object-based approaches
Author: Masroor Hussain, Dongmei Chen, Angela Cheng, Hui Wei, David Stanley
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier, Vol 80, June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Remote sensing, change detection, pixel-based, object-based, spatial-data-mining
Abstract: The appetite for up-to-date information about earth ' s surface is ever increasing, as such information provides a base for a large number of applications, including local, regional adn global resources monitoring, land-cover and land-use change monitoring, and environmental studies. The data from remote sensing satellites provide opportunities to acquire information about land at varying resolutions and has been widely used for change detection studies. A large number of change detection methodologies and techniques, utilizing remotely sensed data, have been developed, and newer techniques are still emerging. This paper begins with a discussion of the traditionally pixel-based and (mostly) statistics-oriented change detection techniques which focus mainly on the spectral values and mostly ignore the spatial context. This is succeeded by a review of object-based change detection techniques. Finally there is a brief discussion of spatial data mining techniques in image processing and change detection from remote sensing data. The merits and issues of different techniques are compared. The importance of the exponential increase in the image data volume and multiple sensors and associated challenges on the development of change detection techniques are highlighted. With the wide use of very-high-resolution (VHR) remotely sensed images, object-based methods and data mining techniques may have more potential in change detection.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58555
Title: Spectral discrimination of giant reed (Arundo donax L): A seasonal study in riparian areas
Author: Maria Rosario Fernandes, Francisca C Aguiar, Joao M N Silva, Maria Teresa Ferreira, Jose M C Pereira
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier, Vol 80, June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Giant reed, Common reed, phenological period, Riparian vegetation, Invasive plant species, Field spectroradiometry
Abstract: The giant reed (Arundo donax L) is a amongst the one hundred worst invasive alien species of the world and it is responsible for biodiversity loss and failure of ecosystem functions in riparian habitats. In this work, field spectroradiometry was used to assess teh spectral separability of the giant reed from the adjacent vegetation and from the common reed, a native similar species.
The study was conducted at different phenological periods and also for the giant reed stands regenerated after mechanical cutting (giant reed_RAC). A hierarchial procedure using Kruskal-Wallis test followed by Classification and Regression Trees (CART) was used to select the minimum number of optimal bands that discriminate the giant reed from the adjacent vegetation. A new approach was used to identify sets of wavelengths-wavezones-that maximize the spectral separability beyond the minimum number of optimal bands, Jeffries Matusita and Bhattacharya distance were used to evaluate the spectral separability using the minimum optimal bands and in three simulated satellite images, namely Landsat, IKONOS and SPOT.
Giant reed was spectrally separable from the adjacent vegetation, both at the vegetation and the senescent period, exception made ot the common reed at the vegetative period. The red edge region was repeatedly selected, although the visible region was also important to separate the giant reef from the herbaceous vegetation and the mid infrared region to the discrimination from the woody vegetation. The highest separability was obtained for the giant reed_RAC stands, due to its highly homogeneous, dense and dark-green stands. Results are discussed by relating the phenological, morphological and structural features of the giant reed stands and the adjacent vegetaion with thier optical traits. Weaknesses and strengths of the giant reed spectral discrimination are highlighted and implications of imagery selection for mapping purposes are argued based on preesnt results.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58554
Title: Improved topographic mapping through high-resolution SAR interferometry with atmospheric effect removal
Author: Mingsheng Liao, Houjun Jiang, Yong Wang, Teng Wang, Lu Zhang
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier, Vol 80, June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: High-resolution, SAR Interferometry, Topographic mapping, SRTM, atmospheric stratification, Atmospheric turbulence
Abstract: The application of SAR interferometry (InSAR ) in topographic mapping is usually limited by geometric/temporal decorrelations and atmospheric effect, particularly in repeat-pass mode. In this paper, to improve the accuracy of topographic mapping with high-resolution InSAR, a new approach to estimate and remove atmospheric effect has been developed. Under the assumptions that there was no ground deformation within a short temporal period and insignificant ionosphere interference on high-frequency radar signals, e.g. X-bands, the approach was focused on the removal of two types of atmospheric effects, namely tropospheric stratification and turbulence. Using an available digital elevation model (DEM) of moderate spatial resolution, e.g. Shuttle Radar Topography Mission (SRTM) DEM, a differential interferogram was firstly produced from the high-resolution InSAR data pair. A linear regression model between phase signal and auxillary elevation was established to estimate the stratified atmospheric effect from the differential interferogram. Afterwards, a combination of a low-pass and an adaptive filter was employed to separate the turbulent atmsopheric effect. After the removal of both types of atmospheric effects in the high-resolution interferogram, the interferometric phase information incorporating local topographic details was obtained and further processed to produce a high-resolution DEM. The feasibility and effectiveness of this approach was validated by an experiment with a tandem mode X-band COSMO-SKyMed InSAR data pair covering a mountainous area in Northwestern China. By using a standard Chinese national DEM of scale 1:50,000 as the reference, we evaluated the vertical accuracy of InSAR DEM with and without atmospheric effects correction, which shows that after atmospheric signal correction the root-mean-squarred error (RMSE) has decreased for 13.6 m to 5.7 m. Overall, from this study a significant improvement to derive topographic maps with high accuracy has been achieved by using the proposed approach.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58553
Title: Estimating crop net primary production using national inventory data and MODIS-derived parameters
Author: Varaprasad Bandaru, Tristram O West, Daniel M Ricciuto, R Cesar Izaurralde
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier, Vol 80, June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Agriculture, carbon flux, crop production, geospatial scaling, phenology, Satellite remote sensing
Abstract: National estimates of spatially resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux between land and atmosphere. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeo-chemical models at the local scale as well as national and continental scales. Existing satellite-based NPP products tend to underestimate NPP on croplands. An Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP over large multi-state regions. The method is documented here and evaluated for corn (Zea mays L) and soybean (Glycine max L Merr) in lowa and Illinois in 2006 and 2007. The method includes a crop-specific Enhanced Vegetation Index (EVI), shortwave radiation data estimated using the Mountain Climate Simulator (MTCLIM) algorithm, and crop-specific LUE per country. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that corresponds to the Cropland Data Layer (CDL) land cover product. Results from the modeling framework captured the spatial NPP gradient across croplands of Iowa and Illinois, and also represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 917 g Cm-2 yr-1 and 409 g Cm-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD1743 NPP product. Site comparisons with flux tower data show AgI-LUE NPP in close agreement with tower-derived NPP, lower than inventory-based NPP, and higher than MOD17A3 NPP. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large reigional extents.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58552
Title: Changes in plant defense chemistry (pyrrolizidine alkaloids) revealed through high-resolution spectroscopy
Author: Sabrina Carvalho, Mirka Macel, Martin Schlerf, Fatemeh Eghbali Moghaddam, Patrick P J Mulder, Andrew K Skidmore, Wim H van der Putten
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier, Vol 80, June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Plant defense chemistry, pyrrolizidine alkaloids, spectroscopy, Senecio erucifolius, Senecio inaequidens, Senecio jacobaea
Abstract: Plant toxic biochemicals play an important role in defense against enemies and often are toxic to humans and livestock. Hyperspectral reflectance is an established method for primary chemical detection and could be further used to determine plant toxicity in the field. In order to make a first step for pyrrolizidine alkaloids detection (toxic defense compound aginst mammals and many insects) we studied how such spectral data can estimate plant defense chemistry under controlled conditions.
In a greenhouse, we grew three related plant species that defend against generlist herbivores through pyrrolizidine alkaloids: Jacobaea vulgaris, Jacobaea erucifolia and Senecio inaequidens, and analyzed the relation between spectral measurements and chemical concentrations using multivariate statistics.
Nutrient addition enhanced tertiary-amine pyrrolizidine alkaloids contents of J. vulgaris and J. erucifolia and decrased N-oxide contents in S. inaequidens and J. vulgaris. Pyrrolizidine alkaloids could be predicted with a moderate accuracy. Pyrrolizidine alkaloid forms tertiary-amines and epoxides were predicted with 63% and 56% of the variation explained, respectively. The most relevant spectral regions selected for prediction were associated with electron transitions and C-H, O-H, and N-H bonds in the 1530 and 2100 nm regions.
Given the relatively low concentration in pyrrolizidine alkaloids concentration (in the order of mg g-1) and resultant predictions, it is promising that pyrrolizidine alkaloids interact with incident light. Further studies should be considered to determine if such a non-destructive method may predict changes in PA concentration in relation to plant natural enemies. Spectroscopy may be used to study plant defenses in intact plant tissues, and may provide managers of toxic plants, food industry and multitrophic -interaction researchers with faster and larger monitoring possibilities.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58551
Title: Derivation of tree skeletons and error assessment using LiDAR point cloud data of varying quality
Author: M Bremer, M Rutzinger, V Wichmann
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier, Vol 80, June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Laser scanning, Branch extraction, skeletonization, Eigenvectors, data reduction, object-based point cloud analysis
Abstract: The architecture of trees is of particular interest for 3D model creation in forestry and ecological applications. Terrestrial (TLS) and mobile laser sanning (MLS) systems are used to acquire detailed geometrical data of trees. Since 3D point clouds from laser scanning consist of large data amounts representing uninterpreted topographical information including noise and data gaps, an extraction of salient tree structures is important for further applications. We present a fully automated modular workflow for topological reliable reconstruction of tree architecture. Object-based point cloud processing such as branch extraction is combined with tree skeletonization. Branch extraction is performed using a segmentation procedure followed by segment-based analysis of form indices derived from eigenvector metrics. Extracted branch primitives are simplified and connected to line features during skeletonization. The modular workflow allows comprehensive parameter tests and error assessments that are used for calibration of the module parameters with respect to various characteristics of the input data (eg. noise, scanning resolution, and the number of scan positions). The estimated parameter settings are validated using an exemplary MLS data set. The quality of input point cloud data, strongly influencing the quality of the skeleton results, can be improved by the presented branch extraction procedure. The potential for data improvement increases with increasing point densities. For our object-based appoach, we can show that the presence of erroneous structures and filtering artifacts have the strongest influence onto the quality of the derived skeletons. In constrast to traditional skeletonization approaches, the existence of data gaps has less influence onto the results.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58550
Title: Shadow detection in very high spatial resolution aerial images: A comparative study
Author: K R M Adeline, M Chen, X Briottet, S K Pang, N Paproditis
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier, Vol 80, June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Shadow detection, urban areas, high spatial resolution, multispectral and hyperspectral
Abstract: Automatic shadow detection is a very important pre-processing step for many remtoe sensing applications, particularly for images acquired with high spatial resolution. In complex urban enviornments, shadows may occupy a significant portion of the image. Ignoring these regions would lead to errors in various applciations, such as atmospheric correction and classification. To better understand the radiative impact of shadows, a physical study was conducted through the simulation of a synthetic urban canyon scene. Its results helped to explain the most common assumptions made on shadows from a physical point of view in the literature. With this understanding, state-of-the-art methods on shadow detection were surveyed and categorized into six classes: histogram thresholding, invariant color models, object segmentation, geometrical methods, physics-based methods, unsupervised and supervised machine learning methods. Among them, some methods were selected and tested on a large dataset of multispectral and hyperspectral airborne images with high spatial resolution. The dataset chosen contains a large variety of typical occidental urban scenes. The results were compared based on accurate reference shadow masks. In these experiments, histogram thresholding on RGB and NIR channels performed the best with an average accuracy of 92.5%, followed by physics-based methods, such as Richter ' s method with 90.0%. Finally, this paper analyzes and discusses the limits algorithms, concluding with some recommendations for shadow detection.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58549
Title: Texture augmented detection of macrophyte species using decision trees
Author: Cameron Proctor, Yuhong He, Vincent Robinson
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier, Vol 80, June 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Floating macrophytes, image texture, feature selection, Jefferies-Matusita distance, decision trees
Abstract: Image classification using multispectral sensors has shown good performance in detecting macrophytes at the species level. However, species level classification often does not utilize the texture information provided by high resolution images. This study investigated whether image texture provides useful vector(s) for the discrimination of monospecific stands of three floating macrophyte species in Quickbird imagery of the South Nation River. Semivariograms indicated that window sizes of 5 x 5 and 13 x 13 pixels were the most appropriate spatial scales for calculation of the grey level co-occurrence matrix and subsequent texture attributes from the multispectral and panchromatic bands. Of the 214 investigated vectors (13 Haralick texture attributes * 15 bands +9 spectral bands +10 transformations/indices), feature selection determined which combination of spectral and textural vectors had the greatest class separability based on the Mann-Whitney U-test and Jefferies - Matusita distance. While multispectral red and near infrared (NIR) performed satisfactorily, the addition of panchromatic -dissimilarity slightly improved class separability and the accuracy of a decision tree classifier (Kappa: red/NIR/panchromatic-dissimilarity-93.2% versus red/NIR-90.4%). Class separability improved by incorporating a second texture attribute, but resulted in a decrease in classification accuracy. The results suggest that incorporating image texture may be beneficial for separating stands with high spatial heterogeneity. However, the benefits may be limited and must be weighed against the increased complexity of the classifier.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None