995 resultados para Forest mapping


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This paper presents an improved hierarchical clustering algorithm for land cover mapping problem using quasi-random distribution. Initially, Niche Particle Swarm Optimization (NPSO) with pseudo/quasi-random distribution is used for splitting the data into number of cluster centers by satisfying Bayesian Information Criteria (BIC). Themain objective is to search and locate the best possible number of cluster and its centers. NPSO which highly depends on the initial distribution of particles in search space is not been exploited to its full potential. In this study, we have compared more uniformly distributed quasi-random with pseudo-random distribution with NPSO for splitting data set. Here to generate quasi-random distribution, Faure method has been used. Performance of previously proposed methods namely K-means, Mean Shift Clustering (MSC) and NPSO with pseudo-random is compared with the proposed approach - NPSO with quasi distribution(Faure). These algorithms are used on synthetic data set and multi-spectral satellite image (Landsat 7 thematic mapper). From the result obtained we conclude that use of quasi-random sequence with NPSO for hierarchical clustering algorithm results in a more accurate data classification.

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Native species' response to the presence of invasive species is context specific. This response cannot be studied in isolation from the prevailing environmental stresses in invaded habitats such as seasonal drought. We investigated the combined effects of an invasive shrub Lantana camara L. (lantana), seasonal rainfall and species' microsite preferences on the growth and survival of 1,105 naturally established seedlings of native trees and shrubs in a seasonally dry tropical forest. Individuals were followed from April 2008 to February 2010, and growth and survival measured in relation to lantana density, seasonality of rainfall and species characteristics in a 50-ha permanent forest plot located in Mudumalai, southern India. We used a mixed effects modelling approach to examine seedling growth and generalized linear models to examine seedling survival. The overall relative height growth rate of established seedlings was found to be very low irrespective of the presence or absence of dense lantana. 22-month growth rate of dry forest species was lower under dense lantana while moist forest species were not affected by the presence of lantana thickets. 4-month growth rates of all species increased with increasing inter-census rainfall. Community results may be influenced by responses of the most abundant species, Catunaregam spinosa, whose growth rates were always lower under dense lantana. Overall seedling survival was high, increased with increasing rainfall and was higher for species with dry forest preference than for species with moist forest preference. The high survival rates of naturally established seedlings combined with their basal sprouting ability in this forest could enable the persistence of woody species in the face of invasive species.

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This paper presents a unified framework using the unit cube for measurement, representation and usage of the range of motion (ROM) of body joints with multiple degrees of freedom (d.o.f) to be used for digital human models (DHM). Traditional goniometry needs skill and kn owledge; it is intrusive and has limited applicability for multi-d.o.f. joints. Measurements using motion capture systems often involve complicated mathematics which itself need validation. In this paper we use change of orientation as the measure of rotation; this definition does not require the identification of any fixed axis of rotation. A two-d.o.f. joint ROM can be represented as a Gaussian map. Spherical polygon representation of ROM, though popular, remains inaccurate, vulnerable due to singularities on parametric sphere and difficult to use for point classification. The unit cube representation overcomes these difficulties. In the work presented here, electromagnetic trackers have been effectively used for measuring the relative orientation of a body segment of interest with respect to another body segment. The orientation is then mapped on a surface gridded cube. As the body segment is moved, the grid cells visited are identified and visualized. Using the visual display as a feedback, the subject is instructed to cover as many grid cells as he can. In this way we get a connected patch of contiguous grid cells. The boundary of this patch represents the active ROM of the concerned joint. The tracker data is converted into the motion of a direction aligned with the axis of the segment and a rotation about this axis later on. The direction identifies the grid cells on the cube and rotation about the axis is represented as a range and visualized using color codes. Thus the present methodology provides a simple, intuitive and accura te determination and representation of up to 3 d.o.f. joints. Basic results are presented for the shoulder. The measurement scheme to be used for wrist and neck, and approach for estimation of the statistical distribution of ROM for a given population are also discussed.

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Effective conservation and management of natural resources requires up-to-date information of the land cover (LC) types and their dynamics. The LC dynamics are being captured using multi-resolution remote sensing (RS) data with appropriate classification strategies. RS data with important environmental layers (either remotely acquired or derived from ground measurements) would however be more effective in addressing LC dynamics and associated changes. These ancillary layers provide additional information for delineating LC classes' decision boundaries compared to the conventional classification techniques. This communication ascertains the possibility of improved classification accuracy of RS data with ancillary and derived geographical layers such as vegetation index, temperature, digital elevation model (DEM), aspect, slope and texture. This has been implemented in three terrains of varying topography. The study would help in the selection of appropriate ancillary data depending on the terrain for better classified information.

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Glycodelin A (GdA) is a dimeric glycoprotein synthesized by the human endometrium under progesterone regulation. Based on the high sequence similarity with beta-lactoglobulin, it is placed under the lipocalin superfamily. The protein is one of the local immunomodulators present at the feto-maternal interface which affects both the innate as well as the acquired arms of the immune system, thereby bringing about successful establishment and progression of pregnancy. Our previous studies revealed that the domain responsible for the immunosuppressive activity of glycodelin lies on its protein backbone and the glycans modulate the same. This study attempts to further delineate the apoptosis inducing region of GdA. Our results demonstrate that the stretch of amino acid sequence between Met24 to Leu105 is necessary and sufficient to inhibit proliferation of T cells and induce apoptosis in them. Further, within this region the key residues involved in harboring the activity were shown to be present between Asp52 and Ser65.

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Here, we report for the first time a simple thermal oxidation strategy for the large area synthesis of Ge/GeO2 nanoholes from Ge and studied the luminescence of Ge/GeO2 and hole formation mechanism through phase and luminescence mapping. Photoluminescence mapping reveals that the emission in the visible range is only from the hole region, which provokes the necessity of the nanoholes. Such materials can also be used to convert ultraviolet to visible radiation for detection by conventional phototubes and to coat blue or ultraviolet diodes to obtain white light.

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The paper presents a new controller inspired by the human experience based, voluntary body action control (dubbed motor control) learning mechanism. The controller is called Experience Mapping based Prediction Controller (EMPC). EMPC is designed with auto-learning features without the need for the plant model. The core of the controller is formed around the motor action prediction-control mechanism of humans based on past experiential learning with the ability to adapt to environmental changes intelligently. EMPC is utilized for high precision position control of DC motors. The simulation results are presented to show that accurate position control is achieved using EMPC for step and dynamic demands. The performance of EMPC is compared with conventional PD controller and MRAC based position controller under different system conditions. Position Control using EMPC is practically implemented and the results are presented.

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Tropical dry forests and savannas constitute more than half of all tropical forests and grasslands, but little is known about forest fire regimes within these two extensive types of ecosystems. Forest fire regimes in a predominantly dry forest in India, the Nilgiri landscape, and a predominantly savanna ecosystem in the Sathyamangalam landscape, were examined. Remote sensing data were applied to delineate burned areas, determine fire size characteristics, and to estimate fire-rotation intervals. Belt transects (0.5 ha) were used to estimate forest structure, diversity, and fuel loads. Mean area burned, mean number of fires, and mean fire size per year were substantially higher in the Nilgiri landscape compared to the Sathyamangalam landscape. Mean fire-rotational interval was 7.1 yr in the Nilgiri landscape and 44.1 yr in the Sathyamangalam landscape. Tree (>= 10 cm diameter at breast height) species diversity, tree density, and basal area were significantly higher in the Nilgiri landscape compared to the Sathyamangalam landscape. Total fuel loads were significantly higher in tropical dry and moist deciduous forests in the Nilgiri landscape, but total fuel loads were higher in the tropical dry thorn forests of the Sathyamangalam landscape. Thus, the two landscapes revealed contrasting fire regimes and forest characteristics, with more and four-fold larger fires in the Nilgiri landscape. The dry forests and savannas could be maintained by a combination of factors, such as fire, grazing pressures, and herbivore populations. Understanding the factors maintaining these two ecosystems will be critical for their conservation.

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Invasive species, local plant communities and invaded ecosystems change over space and time. Quantifying this change may lead to a better understanding of the ecology and the effective management of invasive species. We used data on density of the highly invasive shrub Lantana camara (lantana) for the period 1990-2008 from a 50 ha permanent plot in a seasonally dry tropical forest of Mudumalai in southern India. We used a cumulative link mixed-effects regression approach to model the transition of lantana from one qualitative density state to another as a function of biotic factors such as indicators of competition from local species (lantana itself, perennial grasses, invasive Chromolaena odorata, the native shrub Helicteres isora and basal area of native trees) and abiotic factors such as fire frequency, inter-annual variability of rainfall and relative soil moisture. The density of lantana increased substantially during the study period. Lantana density was negatively associated with the density of H. isora, positively associated with basal area of native trees, but not affected by the presence of grasses or other invasive species. In the absence of fire, lantana density increased with increasing rainfall. When fires occurred, transitions to higher densities occurred at low rainfall values. In drier regions, lantana changed from low to high density as rainfall increased while in wetter regions of the plot, lantana persisted in the dense category irrespective of rainfall. Lantana seems to effectively utilize resources distributed in space and time to its advantage, thus outcompeting local species and maintaining a population that is not yet self-limiting. High-risk areas and years could potentially be identified based on inferences from this study for facilitating management of lantana in tropical dry forests.

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A rain forest dusk chorus consists of a large number of individuals of acoustically communicating species signaling at the same time. How different species achieve effective intra-specific communication in this complex and noisy acoustic environment is not well understood. In this study we examined acoustic masking interference in an assemblage of rain forest crickets and katydids. We used signal structures and spacing of signalers to estimate temporal, spectral and active space overlap between species. We then examined these overlaps for evidence of strategies of masking avoidance in the assemblage: we asked whether species whose signals have high temporal or spectral overlap avoid calling together. Whereas we found evidence that species with high temporal overlap may avoid calling together, there was no relation between spectral overlap and calling activity. There was also no correlation between the spectral and temporal overlaps of the signals of different species. In addition, we found little evidence that species calling in the understorey actively use spacing to minimize acoustic overlap. Increasing call intensity and tuning receivers however emerged as powerful strategies to minimize acoustic overlap. Effective acoustic overlaps were on average close to zero for most individuals in natural, multispecies choruses, even in the absence of behavioral avoidance mechanisms such as inhibition of calling or active spacing. Thus, call temporal structure, intensity and frequency together provide sufficient parameter space for several species to call together yet communicate effectively with little interference in the apparent cacophony of a rain forest dusk chorus.

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This paper addresses the problem of localizing the sources of contaminants spread in the environment, and mapping the boundary of the affected region using an innovative swarm intelligence based technique. Unlike most work in this area the algorithm is capable of localizing multiple sources simultaneously while also mapping the boundary of the contaminant spread. At the same time the algorithm is suitable for implementation using a mobile robotic sensor network. Two types of agents, called the source localization agents (or S-agents) and boundary mapping agents (or B-agents) are used for this purpose. The paper uses the basic glowworm swarm optimization (GSO) algorithm, which has been used only for multiple signal source localization, and modifies it considerably to make it suitable for both these tasks. This requires the definition of new behaviour patterns for the agents based on their terminal performance as well as interactions between them that helps the swarm to split into subgroups easily and identify contaminant sources as well as spread along the boundary to map its full length. Simulations results are given to demonstrate the efficacy of the algorithm.

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Long term forest research sites in India, going by different names including Linear Tree Increment Plots, Linear Increment Plots, Linear Sample Plots and Permanent Preservation Plots, cover diverse plant communities and environmental conditions. Presently, some of these long-term observational studies are functional, some are disturbed and others have almost been lost. The accumulated data will become increasingly important in the context of environmental modelling and climate change, especially if the plots and data can be maintained and/or revived. This contribution presents the history and current state of forest research plots in India, including details of locations and re-measurements. We provide a brief introduction of the National Forest Inventory (NFI), Preservation Plots in natural forests, the 50-ha Mudumalai Forest Dynamics Plot as part of the Centre for Tropical Forest Science and Smithsonian Institution Global Earth Observatories network (CTFS-SIGEO), and research plots established in plantations for tree growth studies and modelling. We also present some methodological details including assessment and analysis for two types of observational studies, the Tree Count Plots (TCP) and Tree Re-measurement Plots (TRP). Arguments are presented in favour of enumeration and analysis methods which are consistent with current approaches in forest ecological research. (c) 2013 Elsevier B.V. All rights reserved.

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The current understanding of wildfire effects on water chemistry is limited by the quantification of the elemental dissolution rates from ash and element release rate from the plant litter, as well as quantification of the specific ash contribution to stream water chemistry. The main objective of the study was to provide such knowledge through combination of experimental modelling, field data and end-member mixing analysis (EMMA) of wildfire impact on a watershed scale. The study concerns watershed effects of fire in the Indian subcontinent, a region that is typically not well represented in the fire science literature. In plant litter ash, major elements are either hosted in readily-soluble phases (K, Mg) such as salts, carbonates and oxides or in less-soluble carrier-phases (Si, Ca) such as amorphous silica, quartz and calcite. Accordingly, elemental release rates, inferred from ash leaching experiments in batch reactor, indicated that the element release into solution followed the order K > Mg > Na > Si > Ca. Experiments on plant litter leaching in mixed-flow reactor indicated two dissolution regimes: rapid, over the week and slower over the month. The mean dissolution rates at steady-state (R-ss) indicated that the release of major elements from plant litter followed the order Ca > Si > Cl > Mg > K > Na. R-ss for Si and Ca for tree leaves and herbaceous species are similar to those reported for boreal and European tree species and are higher than that from the dissolution of soil clay minerals. This identifies tropical plant litters as important source of Si and Ca for tropical surface waters. In the wildfire-impacted year 2004, the EMMA indicated that the streamflow composition (Ca, K, Mg, Na, Si, Cl) was controlled by four main sources: rainwater, throughfall, ash leaching and soil solution. The influence of the ash end-member was maximal early in the rainy season (the two first storm events) and decreased later in the rainy season, when the stream was dominated by the throughfall end-member. The contribution of plant litter decay to the streamwater composition for a year not impacted by wildfire is significant with estimated solute fluxes originating from this decay greatly exceed, for most major elements, the annual elemental dissolved fluxes at the Mule Hole watershed outlet. This highlighted the importance of solute retention and vegetation back uptake processes within the soil profile. Overall, the fire increased the mobility and export of major elements from the soils to the stream. It also shifted the vegetation-related contribution to the elemental fluxes at the watershed outlet from long-term (seasonal) to short-term (daily to monthly). (C) 2014 Elsevier B.V. All rights reserved.

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Periodic estimation, monitoring and reporting on area under forest and plantation types and afforestation rates are critical to forest and biodiversity conservation, sustainable forest management and for meeting international commitments. This article is aimed at assessing the adequacy of the current monitoring and reporting approach adopted in India in the context of new challenges of conservation and reporting to international conventions and agencies. The analysis shows that the current mode of monitoring and reporting of forest area is inadequate to meet the national and international requirements. India could be potentially over-reporting the area under forests by including many non-forest tree categories such as commercial plantations of coconut, cashew, coffee and rubber, and fruit orchards. India may also be under-reporting deforestation by reporting only gross forest area at the state and national levels. There is a need for monitoring and reporting of forest cover, deforestation and afforestation rates according to categories such as (i) natural/primary forest, (ii) secondary/degraded forests, (iii) forest plantations, (iv) commercial plantations, (v) fruit orchards and (vi) scattered trees.

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Anthropogenic fires in seasonally dry tropical forests are a regular occurrence during the dry season. Forest managers in India, who presently follow a fire suppression policy in such forests, would benefit from a system of assessing the potential risk to fire on a particular day. We examined the relationship between weather variables (seasonal rainfall, relative humidity, temperature) and days of fire during the dry seasons of 2004-2010, based on MODIS fire incident data in the seasonally dry tropical forests of Mudumalai in the Western Ghats, southern India. Logistic regression analysis showed that high probabilities of a fire day, indicating successful ignition of litter and grass fuel on the forest floor, were associated with low levels of early dry season rainfall, low daily average relative humidity and high daily average temperatures. These weather conditions are representative of low moisture levels of fine fuels, suggesting that the occurrence of fire is moderated by environmental conditions that reduce the flammability of fine fuels in the dry tropics. We propose a quantitative framework for assessing risk of a fire day to assist forest managers in anticipating fire occurrences in this seasonally dry tropical forest, and possibly for those across South Asia.