SPATIO-TEMPORAL DYNAMICS ALONG THE TERRAIN GRADIENT OF DIVERSE LANDSCAPE

Land use (LU) land cover (LC) information at a temporal scale illustrates the physical coverage of the Earth's terrestrial surface according to its use and provides the intricate information for effective planning and management activities. LULC changes are stated as local and location specific, collectively they act as drivers of global environmental changes. Understanding and predicting the impact of LULC change processes requires long term historical restorations and projecting into the future of land cover changes at regional to global scales. The present study aims at quantifying spatio temporal landscape dynamics along the gradient of varying terrains presented in the landscape by multi-data approach (MDA). MDA incorporates multi temporal satellite imagery with demographic data and other additional relevant data sets. The gradient covers three different types of topographic features, planes; hilly terrain and coastal region to account the significant role of elevation in land cover change. The seasonality is another aspect to be considered in the vegetation dominated landscapes; variations are accounted using multi seasonal data. Spatial patterns of the various patches are identified and analysed using landscape metrics to understand the forest fragmentation. The prediction of likely changes in 2020 through scenario analysis has been done to account for the changes, considering the present growth rates and due to the proposed developmental projects. This work summarizes recent estimates on changes in cropland, agricultural intensification, deforestation, pasture expansion, and urbanization as the causal factors for LULC change.

Temporal variability of forest communities: empirical estimates of population change in 4000 tree species

Long-term surveys of entire communities of species are needed to measure fluctuations in natural populations and elucidate the mechanisms driving population dynamics and community assembly. We analysed changes in abundance of over 4000 tree species in 12 forests across the world over periods of 6-28years. Abundance fluctuations in all forests are large and consistent with population dynamics models in which temporal environmental variance plays a central role. At some sites we identify clear environmental drivers, such as fire and drought, that could underlie these patterns, but at other sites there is a need for further research to identify drivers. In addition, cross-site comparisons showed that abundance fluctuations were smaller at species-rich sites, consistent with the idea that stable environmental conditions promote higher diversity. Much community ecology theory emphasises demographic variance and niche stabilisation; we encourage the development of theory in which temporal environmental variance plays a central role.

Multi-Temporal Satellite Image Analysis Using Gene Expression Programming

This paper discusses an approach for river mapping and flood evaluation to aid multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation to extract water covered region. Analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images is applied in two stages: before flood and during flood. For these images the extraction of water region utilizes spectral information for image classification and spatial information for image segmentation. Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as artificial neural networks and gene expression programming to separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water region. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification and region-based segmentation is an accurate and reliable for the extraction of water-covered region.

Approximation of Spatio-Temporal Random Processes Using Tensor Decomposition

A new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Loeve (KL) decomposition. However, for multiparameter processes such as a spatio-temporal process, the covariance function itself can be defined in multiple ways. Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants. Then the spatial covariance matrix at different time instants are considered to define the covariance of the process. This set of square, symmetric, positive semi-definite matrices is then represented as a third-order tensor. A suitable decomposition of this tensor can identify the dominant components of the process, and these components are then used to define a closed-form representation of the process. The procedure is analogous to the KL decomposition for a single-parameter process, however, the decompositions and interpretations vary significantly. The tensor decompositions are successfully applied on (i) a heat conduction problem, (ii) a vibration problem, and (iii) a covariance function taken from the literature that was fitted to model a measured wind velocity data. It is observed that the proposed representation provides an efficient approximation to some processes. Furthermore, a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL, both in terms of computer memory and execution time.

Estimation of voice-onset time in continuous speech using temporal measures

This paper proposes an automatic acoustic-phonetic method for estimating voice-onset time of stops. This method requires neither transcription of the utterance nor training of a classifier. It makes use of the plosion index for the automatic detection of burst onsets of stops. Having detected the burst onset, the onset of the voicing following the burst is detected using the epochal information and a temporal measure named the maximum weighted inner product. For validation, several experiments are carried out on the entire TIMIT database and two of the CMU Arctic corpora. The performance of the proposed method compares well with three state-of-the-art techniques. (C) 2014 Acoustical Society of America

VIRTUAL VIEW SYNTHESIS BY NON-LOCAL MEANS FILTERING USING TEMPORAL DATA

A novel algorithm for Virtual View Synthesis based on Non-Local Means Filtering is presented in this paper. Apart from using the video frames from the nearby cameras and the corresponding per-pixel depth map, this algorithm also makes use of the previously synthesized frame. Simple and efficient, the algorithm can synthesize video at any given virtual viewpoint at a faster rate. In the process, the quality of the synthesized frame is not compromised. Experimental results prove the above mentioned claim. The subjective and objective quality of the synthesized frames are comparable to the existing algorithms.

Wind speed prediction using spatio-temporal covariance

High wind poses a number of hazards in different areas such as structural safety, aviation, and wind energy-where low wind speed is also a concern, pollutant transport, to name a few. Therefore, usage of a good prediction tool for wind speed is necessary in these areas. Like many other natural processes, behavior of wind is also associated with considerable uncertainties stemming from different sources. Therefore, to develop a reliable prediction tool for wind speed, these uncertainties should be taken into account. In this work, we propose a probabilistic framework for prediction of wind speed from measured spatio-temporal data. The framework is based on decompositions of spatio-temporal covariance and simulation using these decompositions. A novel simulation method based on a tensor decomposition is used here in this context. The proposed framework is composed of a set of four modules, and the modules have flexibility to accommodate further modifications. This framework is applied on measured data on wind speed in Ireland. Both short-and long-term predictions are addressed.

Spatio-temporal correlations in aqueous systems: computational studies of static and dynamic heterogeneity by 2D-IR spectroscopy

Local heterogeneity is ubiquitous in natural aqueous systems. It can be caused locally by external biomolecular subsystems like proteins, DNA, micelles and reverse micelles, nanoscopic materials etc., but can also be intrinsic to the thermodynamic nature of the aqueous solution itself (like binary mixtures or at the gas-liquid interface). The altered dynamics of water in the presence of such diverse surfaces has attracted considerable attention in recent years. As these interfaces are quite narrow, only a few molecular layers thick, they are hard to study by conventional methods. The recent development of two dimensional infra-red (2D-IR) spectroscopy allows us to estimate length and time scales of such dynamics fairly accurately. In this work, we present a series of interesting studies employing two dimensional infra-red spectroscopy (2D-IR) to investigate (i) the heterogeneous dynamics of water inside reverse micelles of varying sizes, (ii) supercritical water near the Widom line that is known to exhibit pronounced density fluctuations and also study (iii) the collective and local polarization fluctuation of water molecules in the presence of several different proteins. The spatio-temporal correlation of confined water molecules inside reverse micelles of varying sizes is well captured through the spectral diffusion of corresponding 2D-IR spectra. In the case of supercritical water also, we observe a strong signature of dynamic heterogeneity from the elongated nature of the 2D-IR spectra. In this case the relaxation is ultrafast. We find remarkable agreement between the different tools employed to study the relaxation of density heterogeneity. For aqueous protein solutions, we find that the calculated dielectric constant of the respective systems unanimously shows a noticeable increment compared to that of neat water. However, the `effective' dielectric constant for successive layers shows significant variation, with the layer adjacent to the protein having a much lower value. Relaxation is also slowest at the surface. We find that the dielectric constant achieves the bulk value at distances more than 3 nm from the surface of the protein.

Retrieval and Multi-scale Validation of Soil Moisture from Multi-temporal SAR Data in a Semi-Arid Tropical Region

The current study presents an algorithm to retrieve surface Soil Moisture (SM) from multi-temporal Synthetic Aperture Radar (SAR) data. The developed algorithm is based on the Cumulative Density Function (CDF) transformation of multi-temporal RADARSAT-2 backscatter coefficient (BC) to obtain relative SM values, and then converts relative SM values into absolute SM values using soil information. The algorithm is tested in a semi-arid tropical region in South India using 30 satellite images of RADARSAT-2, SMOS L2 SM products, and 1262 SM field measurements in 50 plots spanning over 4 years. The validation with the field data showed the ability of the developed algorithm to retrieve SM with RMSE ranging from 0.02 to 0.06 m(3)/m(3) for the majority of plots. Comparison with the SMOS SM showed a good temporal behaviour with RMSE of approximately 0.05 m(3)/m(3) and a correlation coefficient of approximately 0.9. The developed model is compared and found to be better than the change detection and delta index model. The approach does not require calibration of any parameter to obtain relative SM and hence can easily be extended to any region having time series of SAR data available.

DETERMINATION OF THE MASS OF IGR J17091-3624 FROM ``SPECTRO-TEMPORAL'' VARIATIONS DURING THE ONSET PHASE OF THE 2011 OUTBURST

The 2011 outburst of the black hole candidate IGR J17091-3624 followed the canonical track of state transitions along with the evolution of quasi-periodic oscillation (QPO) frequencies before it began exhibiting various variability classes similar to GRS 1915+105. We use this canonical evolution of spectral and temporal properties to determine the mass of IGR J17091-3624, using three different methods: photon index (Gamma)-QPO frequency (nu) correlation, QPO frequency (nu)-time (day) evolution, and broadband spectral modeling based on two-component advective flow (TCAF). We provide a combined mass estimate for the source using a naive Bayes based joint likelihood approach. This gives a probable mass range of 11.8 M-circle dot-13.7 M-circle dot. Considering each individual estimate and taking the lowermost and uppermost bounds among all three methods, we get a mass range of 8.7 M-circle dot-15.6 M-circle dot with 90% confidence. We discuss the possible implications of our findings in the context of two-component accretion flow.

Dynamics of history-dependent epidemics in temporal networks

The structural properties of temporal networks often influence the dynamical processes that occur on these networks, e.g., bursty interaction patterns have been shown to slow down epidemics. In this paper, we investigate the effect of link lifetimes on the spread of history-dependent epidemics. We formulate an analytically tractable activity-driven temporal network model that explicitly incorporates link lifetimes. For Markovian link lifetimes, we use mean-field analysis for computing the epidemic threshold, while the effect of non-Markovian link lifetimes is studied using simulations. Furthermore, we also study the effect of negative correlation between the number of links spawned by an individual and the lifetimes of those links. Such negative correlations may arise due to the finite cognitive capacity of the individuals. Our investigations reveal that heavy-tailed link lifetimes slow down the epidemic, while negative correlations can reduce epidemic prevalence. We believe that our results help shed light on the role of link lifetimes in modulating diffusion processes on temporal networks.

Spatio-temporal Map Formation Based on a Potential Function

We revisit the problem of temporal self organization using activity diffusion based on the neural gas (NGAS) algorithm. Using a potential function formulation motivated by a spatio-temporal metric, we derive an adaptation rule for dynamic vector quantization of data. Simulations results show that our algorithm learns the input distribution and time correlation much faster compared to the static neural gas method over the same data sequence under similar training conditions.

Evaluación temporal y espacial en el bosque de Pinus oocarpa Schiede y su impacto sobre la fijación de carbono en el municipio de Dipilto

El objetivo de este estudio fue a nalizar el cambio de uso de suelo durante un periodo de 18 años en las áreas de bosque de pino y su influencia en la fijación de bióxido de carbono en el Municipio de Dipilto, Nueva Segovia . Se seleccionaron 3 Fincas : San Martín, El Sarrete y Campofresco que presentaron estados de desarrollo: bosque maduro, bosque joven y bosque en regeneración. Se establecieron 9 parcelas temporales (con predominancia P. oocarpa ), utilizándose una parcela temporal para cada es tado d esarrollo. En cada estado de desarrollo se derribó un árbol tipo, se separó en tallo, ramas y follaje. La mayor par te de biomasa seca se encuentra en la finca San Martin con 99.12 Mg/ha estado en desarrollo maduro , estado en desarrollo joven con 77.70 Mg/ ha y estado en desarrollo regeneración 38.63 Mg/ha . El Factor de expansión de biomasa en San Martin 1.59 esta do en desarrollo regeneración, El Sarrete para el estado en desarrollo maduro 1 .40 y finca Campofresco 1.27 estado desarrollo joven . El total de ca rbono almacenado lo presentó San Martín para el estado en desarrollo maduro con 27.13 Mg/ha , joven 22.06 Mg/ha y estado en desarrollo regeneraci ón con 9.82 Mg/ha . El contenido de carbono en el suelo 826.89 Mg/ha regeneración, 503.96 Mg/ha Joven , 294.55 Mg/ ha maduro en San Martín de 0 a 20 cm de profundidad. En un 38.49 % de esa área se emitieron entre 0 - 15 Mg/ha . Emisiones de 26 - 30 Mg/ha se presentaron en un 17.8 1 % del área. Existe un 48.19 % del área total que fijo rangos de 26 - 30 Mg/ha y un 38. 49 % de las áreas fij aron entre 0 - 15 Mg /ha . Se encontró un balance neto positivo de 2925. 2 1 hectáreas, de las cuales 1981.25 hectáreas fijaron rangos de 26 - 30 Mg/ha, 606.06 hectáre as fijaron en un rango entre 0 - 15 Mg /ha y el rango 16 - 25 Mg/ha 337.89 hect áreas .

Numerical Investigation on Laser Transformation Hardening with Different Temporal Pulse Shapes

A 3-D numerical model for pulsed laser transformation hardening (LTH) is developed using the finite element method. In this model, laser spatial and temporal intensity distribution, temperature-dependent thermophysical properties of material, and multi-phase transformations are considered. The influence of laser temporal pulse shape on connectivity of hardened zone, maximum surface temperature of material and hardening depth is numerically investigated at different pulse energy levels. Results indicate that these hardening parameters are strongly dependent on the temporal pulse shape. For the rectangular temporal pulse shape, the temperature field obtained from this model is in excellent agreement with analytical solution, and the predicted hardening depth is favorably compared with experimental one. It should be pointed out that appropriate temporal pulse shape should be selected according to pulse energy level in order to achieve desirable hardening quality under certain laser spatial intensity distribution.

Biomasa y nutrientes de arboles de sombra temporal y permanente en sistemas agroforestales con Coffea arabiga L de cinco años en el Pacifico de Nicaragua

Chavarria, E; Hernández, J. 2,006. Biomasa y nutrientes de árboles de sombra temporal y permanente en sistemas agroforestales con Coffea arabiga L de 5 años en el pacífico de Nicaragua. La presente investigación se realizó en sistemas agroforestales con café (Coffea arábiga L.) en el Municipio de Masatepe, Nicaragua, determinando el aporte de biomasa y los contenidos de N, P, K, Ca y Mg. de la sombra temporal y permanente. Se evaluaron dos factores de estudio en un diseño de bloques completamente al azar con arreglo de parcelas subdivididas: A) Tipo de sombra: temporal estableciéndose de forma homogénea y mixtas, especies de leguminosas más no leguminosas para sombra de café como Cajanus cajan y Ricinus communis y en sombra permanente, especies de árboles leguminosas y/o maderables (Inga laurina, Simarouba glauca, Samanea saman, Tabebuia rosea) y una parcela de café a pleno sol, distribuidas en parcelas grandes; B) Los niveles de insumos: Convencional Intensivo (CI) y Convencional Extensivo (CE), Orgánico Intensivo (OI) y Orgánico Extensivo (OE); relativos a aportes de nutrientes, manejo de enfermedades, malezas e insectos dañinos. La biomasa de sombra temporal se cuantificó en 2,002 por podas y 2,003 por eliminación de la misma. También se cuantificó la biomasa en la sombra permanente por podas en 2,004 y de raleo 2,005. La biomasa total por especie y tratamientos en sombra temporal y permanente, se obtuvieron a partir de los componentes hojas, tallos menores a 2 cm, tallos mayores de 2 cm de diámetro y tronco. Se tomó una muestra de biomasa fresca por tratamiento, se secó al horno a temperaturas de 65 ºC, para obtener el contenido de materia seca. A este mismo material, se procedió a la determinación de las concentraciones de los elementos minerales anteriormente mencionados. Los resultados obtenidos mostraron que la especie de sombra temporal no leguminosa Higuera (Ricinus communis) presentó el mayor aporte de materia seca con 4,356 kg ha-1 en dos años (2,002 + 2,003), representando también los mayores contenidos de N, P, K, Ca y Mg con 82, 28, 165, 68 y 57 kg ha-1 respectivamente. Respecto a las especies de sombra permanente, sometidas al manejo de poda el nivel de sombra Il+Sg produce los mayores aportes de MS con 5,695.66 kg ha-1 a-1 de los cuales el 39 % se recicla en el sistema, este mismo tipo de sombra aporta al sistema los mayores contenidos de N, P, K, Ca y Mg con 64, 55, 55, 66 y 36 % respectivamente. En el manejo de raleo el tipo de sombra que produjo mayor cantidad de MS es Sg+Tr con 9,096.89 kg ha-1 a-1 aportando al sistema el 45 %, este mismo tipo de sombra aporta al sistema las mayores cantidades de N, P, K, Ca y Mg con 67, 54, 70, 80 y 44 % respectivamente. Los porcentaje restante de materia seca y nutrientes tanto en poda y raleo correspondiente a tallos mayores de 2 cm de diámetro, es extraído del sistema como leña y postes respectivamente.