35 resultados para Cover interpretation
Resumo:
We propose a new abstract domain for static analysis of executable code. Concrete states are abstracted using circular linear progressions (CLPs). CLPs model computations using a finite word length as is seen in any real life processor. The finite abstraction allows handling overflow scenarios in a natural and straight-forward manner. Abstract transfer functions have been defined for a wide range of operations which makes this domain easily applicable for analyzing code for a wide range of ISAs. CLPs combine the scalability of interval domains with the discreteness of linear congruence domains. We also present a novel, lightweight method to track linear equality relations between static objects that is used by the analysis to improve precision. The analysis is efficient, the total space and time overhead being quadratic in the number of static objects being tracked.
Resumo:
The changes in seasonal snow covered area in the Hindu Kush-Himalayan (HKH) region have been examined using Moderate – resolution Imaging Spectroradiometer (MODIS) 8-day standard snow products. The average snow covered area of the HKH region based on satellite data from 2000 to 2010 is 0.76 million km2 which is 18.23% of the total geographical area of the region. The linear trend in annual snow cover from 2000 to 2010 is −1.25±1.13%. This is in consistent with earlier reported decline of the decade from 1990 to 2001. A similar trend for western, central and eastern HKH region is 8.55±1.70%, +1.66% ± 2.26% and 0.82±2.50%, respectively. The snow covered area in spring for HKH region indicates a declining trend (−1.04±0.97%). The amount of annual snowfall is correlated with annual seasonal snow cover for the western Himalaya, indicating that changes in snow cover are primarily due to interannual variations in circulation patterns. Snow cover trends over a decade were also found to vary across seasonally and the region. Snow cover trends for western HKH are positive for all seasons. In central HKH the trend is positive (+15.53±5.69%) in autumn and negative (−03.68±3.01) in winter. In eastern HKH the trend is positive in summer (+3.35±1.62%) and autumn (+7.74±5.84%). The eastern and western region of HKH has an increasing trend of 10% to 12%, while the central region has a declining trend of 12% to 14% in the decade between 2000 and 2010. Snow cover depletion curve plotted for the hydrological year 2000–2001 reveal peaks in the month of February with subsidiary peaks observed in November and December in all three regions of the HKH.
Resumo:
Calculated phase relations in the system MnOSi02-C02-02 were used to propose a thermodynamic explanation for the thermal metamorphism of rhodochrosite beds lying between chert strata. The metamorphic MnOS i 0 2 minerals are arranged in order quartz(chert), rhodonite. tephroite and manganosite-hausmannite-pyrochroite rhodonite across the ore bed. The calculation covered temperatures up to 1000 K and pressures up to 5 kb. The zoning was interpreted as the result of a continuous rise in metamorphic temperature. The equilibrium partner of rhodochrosite changed from rhodonite through manganosite. Across the ore bed there are gradients in the chemical potential of MnO and SiO2 but fugacities of volatlle components such as C02. 02 and H20 were probably uniform at any given time and location during formation of the zones. Assuming that the total pressure and the fugacity of C02 were at 1.4 kb and 1.0 1 b. respectively. rhodonite. tephroite and manganosite would have formed at 472. 478 and 629 K.
Resumo:
All major rivers in Bhutan depend on snowmelt for discharge. Therefore, changes in snow cover due to climate change can influence distribution and availability of water. However, information about distribution of seasonal snow cover in Bhutan is not available. The MODIS snow product was used to study snow cover status and trends in Bhutan. Average snow cover area (SCA) of Bhutan estimated for the period 2002 to 2010 was 9030 sq. km, about 25.5% of the total land area. SCA trend of Bhutan for the period 2002-2010 was found to decrease (-3.27 +/- 1.28%). The average SCA for winter was 14,485 sq. km (37.7%), for spring 7411 sq. km (19.3%), for summer 4326 sq. km (11.2%), and for autumn 7788 sq. km (20.2%), mostly distributed in the elevation range 2500-6000 m amsl. Interannual and seasonal SCA trend both showed a decline, although it was not statistically significant for all sub-basins. Pho Chu sub-basin with 19.5% of the total average SCA had the highest average SCA. The rate of increase of SCA for every 100 m elevation was the highest (2.5%) in the Pa Chu sub-basin. The coefficient of variance of 1.27 indicates high variability of SCA in winter.
Resumo:
This paper presents hierarchical clustering algorithms for land cover mapping problem using multi-spectral satellite images. In unsupervised techniques, the automatic generation of number of clusters and its centers for a huge database is not exploited to their full potential. Hence, a hierarchical clustering algorithm that uses splitting and merging techniques is proposed. Initially, the splitting method is used to search for the best possible number of clusters and its centers using Mean Shift Clustering (MSC), Niche Particle Swarm Optimization (NPSO) and Glowworm Swarm Optimization (GSO). Using these clusters and its centers, the merging method is used to group the data points based on a parametric method (k-means algorithm). A performance comparison of the proposed hierarchical clustering algorithms (MSC, NPSO and GSO) is presented using two typical multi-spectral satellite images - Landsat 7 thematic mapper and QuickBird. From the results obtained, we conclude that the proposed GSO based hierarchical clustering algorithm is more accurate and robust.
Resumo:
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.
Resumo:
The amplitude-modulation (AM) and phase-modulation (PM) of an amplitude-modulated frequency-modulated (AM-FM) signal are defined as the modulus and phase angle, respectively, of the analytic signal (AS). The FM is defined as the derivative of the PM. However, this standard definition results in a PM with jump discontinuities in cases when the AM index exceeds unity, resulting in an FM that contains impulses. We propose a new approach to define smooth AM, PM, and FM for the AS, where the PM is computed as the solution to an optimization problem based on a vector interpretation of the AS. Our approach is directly linked to the fractional Hilbert transform (FrHT) and leads to an eigenvalue problem. The resulting PM and AM are shown to be smooth, and in particular, the AM turns out to be bipolar. We show an equivalence of the eigenvalue formulation to the square of the AS, and arrive at a simple method to compute the smooth PM. Some examples on synthesized and real signals are provided to validate the theoretical calculations.
Resumo:
The problem of finding a satisfying assignment that minimizes the number of variables that are set to 1 is NP-complete even for a satisfiable 2-SAT formula. We call this problem MIN ONES 2-SAT. It generalizes the well-studied problem of finding the smallest vertex cover of a graph, which can be modeled using a 2-SAT formula with no negative literals. The natural parameterized version of the problem asks for a satisfying assignment of weight at most k. In this paper, we present a polynomial-time reduction from MIN ONES 2-SAT to VERTEX COVER without increasing the parameter and ensuring that the number of vertices in the reduced instance is equal to the number of variables of the input formula. Consequently, we conclude that this problem also has a simple 2-approximation algorithm and a 2k - c logk-variable kernel subsuming (or, in the case of kernels, improving) the results known earlier. Further, the problem admits algorithms for the parameterized and optimization versions whose runtimes will always match the runtimes of the best-known algorithms for the corresponding versions of vertex cover. Finally we show that the optimum value of the LP relaxation of the MIN ONES 2-SAT and that of the corresponding VERTEX COVER are the same. This implies that the (recent) results of VERTEX COVER version parameterized above the optimum value of the LP relaxation of VERTEX COVER carry over to the MIN ONES 2-SAT version parameterized above the optimum of the LP relaxation of MIN ONES 2-SAT. (C) 2013 Elsevier B.V. All rights reserved.
Resumo:
Variable Endmember Constrained Least Square (VECLS) technique is proposed to account endmember variability in the linear mixture model by incorporating the variance for each class, the signals of which varies from pixel to pixel due to change in urban land cover (LC) structures. VECLS is first tested with a computer simulated three class endmember considering four bands having small, medium and large variability with three different spatial resolutions. The technique is next validated with real datasets of IKONOS, Landsat ETM+ and MODIS. The results show that correlation between actual and estimated proportion is higher by an average of 0.25 for the artificial datasets compared to a situation where variability is not considered. With IKONOS, Landsat ETM+ and MODIS data, the average correlation increased by 0.15 for 2 and 3 classes and by 0.19 for 4 classes, when compared to single endmember per class. (C) 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.
Resumo:
We investigated area changes in glaciers covering an area of similar to 200 km(2) in the Tista basin, Sikkim, Eastern Indian Himalaya, between similar to 1990 and 2010 using Landsat Thematic Mapper (TM) and Indian Remote-sensing Satellite (IRS) images and related the changes to debris cover, supraglacial lakes and moraine-dam lakes. The glaciers lost an area of 3.3 +/- 0.8% between 1989/90 and 2010. More detailed analysis revealed an area loss of 2.00 +/- 0.82, 2.56 +/- 0.61 and 2.28 +/- 2.01 km(2) for the periods 1989-97, 1997-2004/05 and 2004-2009/10, respectively. This indicates an accelerated retreat of glaciers after 1997. On further analysis, we observed (1) the formation and expansion of supraglacial lakes on many debris-covered glaciers and (2) the merging of these lakes over time, leading to the development of large moraine-dam lakes. We also observed that debris-covered glaciers with lakes lose a greater area than debris-covered glaciers without lakes and debris-free glaciers. The climatic data for 24 years (1987-2011), measured at the Gangtok meteorological station (1812 m a.s.l.), showed that the region experienced a 1.0 degrees C rise in the summer minimum temperature and a 2.0 degrees C rise in the winter minimum temperature, indicating hotter summers and warmer winters. There was no significant trend in the total annual precipitation. We find that glacier retreat is caused mainly by a temperature increase and that debris-covered glaciers can retreat at a faster rate than debris-free glaciers, if associated with lakes.
Missing (in-situ) snow cover data hampers climate change and runoff studies in the Greater Himalayas
Resumo:
The Himalayas are presently holding the largest ice masses outside the polar regions and thus (temporarily) store important freshwater resources. In contrast to the contemplation of glaciers, the role of runoff from snow cover has received comparably little attention in the past, although (i) its contribution is thought to be at least equally or even more important than that of ice melt in many Himalayan catchments and (ii) climate change is expected to have widespread and significant consequences on snowmelt runoff. Here, we show that change assessment of snowmelt runoff and its timing is not as straightforward as often postulated, mainly as larger partial pressure of H2O, CO2, CH4, and other greenhouse gases might increase net long-wave input for snowmelt quite significantly in a future atmosphere. In addition, changes in the short-wave energy balance such as the pollution of the snow cover through black carbon or the sensible or latent heat contribution to snowmelt are likely to alter future snowmelt and runoff characteristics as well. For the assessment of snow cover extent and depletion, but also for its monitoring over the extremely large areas of the Himalayas, remote sensing has been used in the past and is likely to become even more important in the future. However, for the calibration and validation of remotely-sensed data, and even-more so in light of possible changes in snow-cover energy balance, we strongly call for more in-situ measurements across the Himalayas, in particular for daily data on new snow and snow cover water equivalent, or the respective energy balance components. Moreover, data should be made accessible to the scientific community, so that the latter can more accurately estimate climate change impacts on Himalayan snow cover and possible consequences thereof on runoff. (C) 2013 Elsevier B.V. All rights reserved.
Resumo:
The study of recession flows offers fundamental insights into basin hydrological processes and, in particular, into the collective behavior of the governing dominant subsurface flows and properties. We use here an existing geomorphological interpretation of recession dynamics, which links the exponent in the classic recession curve -dQ/dt - kQ(alpha) to the geometric properties of the time-varying drainage network to study the general properties of recession curves across a wide variety of river basins. In particular, we show how the parameter k depends on the initial soil moisture state of the basin and can be made to explicitly depend on an index discharge, representative of initial sub-subsurface storage. Through this framework we obtain a non-dimensional, event-independent, recession curve. We subsequently quantify the variability of k across different basins on the basis of their geometry, and, by rescaling, collapse curves from different events and basins to obtain a generalized, or `universal', recession curve. Finally, we analyze the resulting normalized recession curves and explain their universal characteristics, lending further support to the notion that the statistical properties of observed recession curves bear the signature of the geomorphological structure of the networks producing them. (C) 2014 Elsevier Ltd. All rights reserved.