24 resultados para Temporal sequences
Resumo:
Urban developments have exerted immense pressure on wetlands. Urban areas are normally centers of commercial activity and continue to attract migrants in large numbers in search of employment from different areas. As a result, habitations keep coming up in the natural areas / flood plains. This is happening in various Indian cities and towns and large habitations are coming up in low-lying areas, often encroaching even over drainage channels. In some cases, houses are constructed even on top of nallahs and drains. In the case of Kochi the situation is even worse as the base of the urban development itself stands on a completely reclaimed island. Also the topography and geology demanded more reclamation of land when the city developed as an agglomerative cluster. Cochin is a coastal settlement interspersed with a large backwater system and fringed on the eastern side by laterite-capped low hills from which a number of streams drain into the backwater system. The ridge line of the eastern low hills provides a welldefined watershed delimiting Cochin basin which help to confine the environmental parameters within a physical limit. This leads to an obvious conclusion that if physiography alone is considered, the western flatland is ideal for urban development. However it will result in serious environmental deterioration, as it comprises mainly of wetland and for availability of land there has to be large scale filling up of these wetlands which includes shallow mangrove-fringed water sheets, paddy fields, Pokkali fields, estuary etc.Chapter 1 School 4 of Environmental Studies The urban boundaries of Cochin are expanding fast with a consequent over-stretching of the existing fabric of basic amenities and services. Urbanisation leads to the transformation of agricultural land into built-up areas with the concomitant problems regarding water supply, drainage, garbage and sewage disposal etc. Many of the environmental problems of Cochin are hydrologic in origin; like water-logging / floods, sedimentation and pollution in the water bodies as well as shoreline erosion
Resumo:
The influence of salinity on phytoplankton varies widely, because different species have different salinity preferences. Like marine and aquatic species, many phytoplankton species exhibit tolerance to certain salinity, beyond which, it can inhibit their growth. Light is the most important factor that influences phytoplankton growth. In aquatic environments (lakes, sea or estuary) the light incident on the surface is rapidly reduced exponentially with depth (Krik, 1994). In estuaries, the major factor influencing the light availability is the suspended particulate matter, which attenuates and scatters the light. The light changes with time of the day and the season, affecting the amount of light penetrating the water column. Similarly, biological factor like copepod grazing is a major factor influencing the standing crop of phytoplankton. The copepod can actively graze up to 75% of the phytoplankton biomass in a tropical estuary (Tan et. al., 2004). It is in the context that the present study investigates the salinity, light (physical factors) and copepod grazing (biological factor) phytoplankton as the factors controlling phytoplankton growth and distribution
Resumo:
The present study is focused on the intensity distribution of rainfall in different classes and their contribution to the total seasonal rainfall. In addition, we studied the spatial and diurnal variation of the rainfall in the study areas. For the present study, we retrieved data from TRMM (Tropical Rain Measuring Mission) rain rate available in every 3 h temporal and 25 km spatial resolutions. Moreover, station rainfall data is used to validate the TRMM rain rate and found significant correlation between them (linear correlation coefficients are 0.96, 0.85, 0.75 and 0.63 for the stations Kota Bharu, Senai, Cameron highlands and KLIA, respectively). We selected four areas in the Peninsular Malaysia and they are south coastal, east coastal, west coastal and highland regions. Diurnal variation of frequency of rain occurrence is different for different locations. We noticed bimodal variation in the coastal areas in most of the seasons and unimodal variation in the highland/inland area. During the southwest monsoon period in the west coastal stations, there is no distinct diurnal variation. The distribution of different intensity classes during different seasons are explained in detail in the results
Resumo:
Present study is focused on the spatiotemporal variation of the microbial population (bacteria, fungus and actinomycetes) in the grassland soils of tropical montane forest and its relation with important soil physico-chemical characteristics and nutrients. Different physico-chemical properties of the soil such as temperature, moisture content, organic carbon, available nitrogen, available phosphorous and available potassium have been studied. Results of the present study revealed that both microbial load and soil characteristics showed spatiotemporal variation. Microbial population of the grassland soils were characterized by high load of bacteria followed by fungus and actinomycetes. Microbial load was high during pre monsoon season, followed by post monsoon and monsoon. The microbial load varied with important soil physico-chemical properties and nutrients. Organic carbon content, available nitrogen and available phosphorous were positively correlated with bacterial load and the correlation is significant at 0.05 and 0.01 levels respectively. Available nitrogen and available phosphorous were positively correlated with fungus at 0.05 level significance. Moisture content was negatively correlated with actinomycetes at 0.01 level of significance. Organic carbon negatively correlated with actinomycetes load at 0.05 level of significance
Resumo:
In this paper, moving flock patterns are mined from spatio- temporal datasets by incorporating a clustering algorithm. A flock is defined as the set of data that move together for a certain continuous amount of time. Finding out moving flock patterns using clustering algorithms is a potential method to find out frequent patterns of movement in large trajectory datasets. In this approach, SPatial clusteRing algoRithm thrOugh sWarm intelligence (SPARROW) is the clustering algorithm used. The advantage of using SPARROW algorithm is that it can effectively discover clusters of widely varying sizes and shapes from large databases. Variations of the proposed method are addressed and also the experimental results show that the problem of scalability and duplicate pattern formation is addressed. This method also reduces the number of patterns produced
Resumo:
The status of fisheries and seasonal variation in fish diversity in the Kodungallur-Azhikode Estuary (KAE) were investigated. Total annual average fish production in the estuary declined significantly to 908.6 t with average yield of 5.4 kg ha-1 day-1, when compared to earlier study; where 2747 t was reported. During the present study, 60 species of finfishes (belonging to 34 finfish families), 6 species of penaeid shrimps, 2 species of palaemonid prawns, 2 species of crabs (4 crustacean families), 6 species of bivalves and 2 species of edible oysters (3 molluscan families) were noticed. Finfishes were the major group that contributed 69.62% of total fishery in the estuary and crustaceans (23.47%), bivalves (6.84%) and oysters (0.07%) also formed good fishery. Many of the fish species in the estuary were observed as threatened (Horabagrus brachysoma, Channa striatus, Channa marulius, Clarias batrachus, Heteropneustes fossilis and Wallago attu). The major fishing gears employed in the estuary were gillnets, cast nets, stake nets, scoop nets, ring nets, traps and Chinese dip nets. Gillnets contributed 45% of the total fish catch. Gillnets also showed highest catch per unit effort (CPUE) of 6.91 kg h -1 followed by cast nets (1.85 kg h -1), Chinese dip nets (3.20 kg h -1), stake nets (3.05 kg h -1), ring nets (1.27 kg h -1), hooks and lines (1.35 kg h -1) and scoop nets (0.92 kg h -1). The study implies that temporal changes in fish landing pattern of the KAE was mainly due to environmental variability, habitat modification and fish migration; under the influence of south-west monsoon and anthropogenic activities in the KAE. Results of the study suggest that spatio-temporal variations in the fish community structure could be an indicator for anthropogenic stress and it should be considered for restoration programmes.
Resumo:
The phytoplankton standing crop was assessed in detail along the South Eastern Arabian Sea (SEAS) during the different phases of coastal upwelling in 2009.During phase 1 intense upwelling was observed along the southern transects (8◦N and 8.5◦N). The maximum chlorophyll a concentration (22.7 mg m −3) was observed in the coastal waters off Thiruvananthapuram (8.5◦N). Further north there was no signature of upwelling, with extensive Trichodesmium erythraeum blooms. Diatoms dominated in these upwelling regions with the centric diatom Chaetoceros curvisetus being the dominant species along the 8◦N transect. Along the 8.5◦N transect pennate diatoms like Nitzschia seriata and Pseudo-nitzschia sp. dominated. During phase 2, upwelling of varying intensity was observed throughout the study area with maximum chlorophyll a concentrations along the 9◦N transect (25 mg m−3) with Chaetoceros curvisetus as the dominant phytoplankton. Along the 8.5◦N transect pennate diatoms during phase 1 were replaced by centric diatoms like Chaetoceros sp. The presence of solitary pennate diatoms Amphora sp. and Navicula sp. were significant in the waters off Kochi. Upwelling was waning during phase 3 and was confined to the coastal waters of the southern transects with the highest chlorophyll a concentration of 11.2 mg m−3. Along with diatoms, dinoflagellate cell densities increased in phases 2 and 3. In the northern transects (9◦N and 10◦N) the proportion of dinoflagellates was comparatively higher and was represented mainly by Protoperidinium spp., Ceratium spp. and Dinophysis spp.
Resumo:
Knowledge discovery in databases is the non-trivial process of identifying valid, novel potentially useful and ultimately understandable patterns from data. The term Data mining refers to the process which does the exploratory analysis on the data and builds some model on the data. To infer patterns from data, data mining involves different approaches like association rule mining, classification techniques or clustering techniques. Among the many data mining techniques, clustering plays a major role, since it helps to group the related data for assessing properties and drawing conclusions. Most of the clustering algorithms act on a dataset with uniform format, since the similarity or dissimilarity between the data points is a significant factor in finding out the clusters. If a dataset consists of mixed attributes, i.e. a combination of numerical and categorical variables, a preferred approach is to convert different formats into a uniform format. The research study explores the various techniques to convert the mixed data sets to a numerical equivalent, so as to make it equipped for applying the statistical and similar algorithms. The results of clustering mixed category data after conversion to numeric data type have been demonstrated using a crime data set. The thesis also proposes an extension to the well known algorithm for handling mixed data types, to deal with data sets having only categorical data. The proposed conversion has been validated on a data set corresponding to breast cancer. Moreover, another issue with the clustering process is the visualization of output. Different geometric techniques like scatter plot, or projection plots are available, but none of the techniques display the result projecting the whole database but rather demonstrate attribute-pair wise analysis
Resumo:
The classical methods of analysing time series by Box-Jenkins approach assume that the observed series uctuates around changing levels with constant variance. That is, the time series is assumed to be of homoscedastic nature. However, the nancial time series exhibits the presence of heteroscedasticity in the sense that, it possesses non-constant conditional variance given the past observations. So, the analysis of nancial time series, requires the modelling of such variances, which may depend on some time dependent factors or its own past values. This lead to introduction of several classes of models to study the behaviour of nancial time series. See Taylor (1986), Tsay (2005), Rachev et al. (2007). The class of models, used to describe the evolution of conditional variances is referred to as stochastic volatility modelsThe stochastic models available to analyse the conditional variances, are based on either normal or log-normal distributions. One of the objectives of the present study is to explore the possibility of employing some non-Gaussian distributions to model the volatility sequences and then study the behaviour of the resulting return series. This lead us to work on the related problem of statistical inference, which is the main contribution of the thesis