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The role of forests is being actively considered under the agenda of REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus) aimed at reducing emissions related to changes in forest cover and forest quality. Forests in general have undergone negative changes in the past in the form of deforestation and degradation, while in some countries positive changes are reported in the form of conservation, sustainable management of forests and enhancement of carbon stock. The present study in the Kashmir Himalayan forests is an effort to assess historical forest cover changes that took place from 1980 to 2009 and to predict the same for 2030 on the basis of past trend using geospatial modeling approach. Landsat data (Multispectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+)) was used for the years 1980, 1990 and (2001, 2009) respectively and change detection analysis between the dates was performed. The maps generated were validated through ground truthing. The study area (3375.62 km2) from 1980-2009 has uffered deforestation and forest degradation of about 126 km2 and 139.02 km2 respectively which can be claimed under negative options of REDD+, while as the area that experienced no change (1514 km2) can be claimed under conservation. A small area (23.31 km2) observed as positive change can be claimed under positive options. The projected estimates of forest cover for 2030 showed increased deforestation and forest degradation on the basis of trend analysis using Cellular Automata (CA) Markov modeling. Despite the fact that country as a whole has registered a net positive change in the past few decades, but there are regions like Kashmir region of western Himalaya which have constantly undergoing deforestation as well as degradation in the past few decades. 相似文献
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The occurrence of gas hydrate has been inferred from the presence of Bottom-Simulating Reflectors (BSRs) along the western
continental margin of India. In this paper, we assess the spatial and vertical distribution of gas hydrates by analyzing the
interval velocities and Amplitude Versus Offset (AVO) responses obtained from multi-channel seismics (MCSs). The hydrate cements
the grains of the host sediment, thereby increasing its velocity, whereas the free gas below the base of hydrate stability
zone decreases the interval velocity. Conventionally, velocities are obtained from the semblance analysis on the Common Mid-Point
(CMP) gathers. Here, we used wave-equation datuming to remove the effect of the water column before the velocity analysis.
We show that the interval velocities obtained in this fashion are more stable than those computed from the conventional semblance
analysis. The initial velocity model thus obtained is updated using the tomographic velocity analysis to account for lateral
heterogeneity. The resultant interval velocity model shows large lateral velocity variations in the hydrate layer and some
low velocity zones associated with free gas at the location of structural traps. The reflection from the base of the gas layer
is also visible in the stacked seismic data. Vertical variation in hydrate distribution is assessed by analyzing the AVO response
at selected locations. AVO analysis is carried out after applying true amplitude processing. The average amplitudes of BSRs
are almost constant with offset, suggesting a fluid expulsion model for hydrate formation. In such a model, the hydrate concentrations
are gradational with maxima occurring at the base of hydrate stability zone. 相似文献
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The effects of rainfall and the El Niño Southern Oscillation (ENSO) on groundwater in a semi-arid basin of India were analyzed using Archimedean copulas considering 17 years of data for monsoon rainfall, post-monsoon groundwater level (PMGL) and ENSO Index. The evaluated dependence among these hydro-climatic variables revealed that PMGL-Rainfall and PMGL-ENSO Index pairs have significant dependence. Hence, these pairs were used for modeling dependence by employing four types of Archimedean copulas: Ali-Mikhail-Haq, Clayton, Gumbel-Hougaard, and Frank. For the copula modeling, the results of probability distributions fitting to these hydro-climatic variables indicated that the PMGL and rainfall time series are best represented by Weibull and lognormal distributions, respectively, while the non-parametric kernel-based normal distribution is the most suitable for the ENSO Index. Further, the PMGL-Rainfall pair is best modeled by the Clayton copula, and the PMGL-ENSO Index pair is best modeled by the Frank copula. The Clayton copula-based conditional probability of PMGL being less than or equal to its average value at a given mean rainfall is above 70% for 33% of the study area. In contrast, the spatial variation of the Frank copula-based probability of PMGL being less than or equal to its average value is 35–40% in 23% of the study area during El Niño phase, while it is below 15% in 35% of the area during the La Niña phase. This copula-based methodology can be applied under data-scarce conditions for exploring the impacts of rainfall and ENSO on groundwater at basin scales. 相似文献
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This work provides an overview of various methods for estimating snow cover and properties in high mountains using remote sensing techniques involving microwaves. Satellite-based remote sensing with its characteristics such as synoptic view, repetitive coverage and uniformity over large areas has great potential for identifying the temporal snow cover. Many sensors have been used in the past with various algorithms and accuracies for this purpose. These methods have been improving with the use of Synthetic Aperture Radar sensors, working in different microwave frequencies, polarisation and acquisition modes. The limitations, advantages and drawbacks are illustrated while error sources and strategies on how to ease their impacts are also reviewed. An extensive list of references, with an emphasis on studies since 1990s, allows the reader to delve into specific topics. 相似文献
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V. Braito J. N. Reeves G. Dewangan I. George R. Griffiths A. Markowitz K. Nandra D. Porquet A. Ptak T. J. Turner T. Yaqoob K. Weaver 《Astronomische Nachrichten》2006,327(10):1067-1070
We present the results of the simultaneous XMM‐Newton and Chandra observations of the bright Seyfert 1.9 galaxy MCG–5‐23‐16, which is one of the best known examples of a relativistically broadened iron Kα line. We find that: a) the soft X‐ray emission is likely to be dominated by photoionized gas, b) the complex iron emission line is best modelled with a narrow and a broad component with a FWHM ∼44000 km/s. This latter component has an EW ∼50 eV and its profile is well described with an emission line mainly originating from the accretion disk a few tens of gravitational radii from the central black hole and viewed with an inclination angle ∼40°. We found evidence of a possible sporadic absorption line at ∼7.7 keV which, if associated with Fe XXVI Kα resonance absorption, is indicative of a possible high velocity (v ∼ 0.1c) outflow. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim) 相似文献
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Manish Yadav Nitin Kumar Singh Bhupendra Kumar Soni Kusum Soni Pawan Kumar Singh 《洁净——土壤、空气、水》2023,51(1):2200059
In this study, three approaches namely parallel, sequential, and multiple linear regression are applied to analyze the local air quality improvements during the COVID-19 lockdowns. In the present work, the authors have analyzed the monitoring data of the following primary air pollutants: particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO). During the lockdown period, the first phase has most noticeable impact on airquality evidenced by the parallel approach, and it has reflected a significant reduction in concentration levels of PM10 (27%), PM2.5 (19%), NO2 (74%), SO2 (36%), and CO (47%), respectively. In the sequential approach, a reduction in pollution levels is also observed for different pollutants, however, these results are biased due to rainfall in that period. In the multiple linear regression approach, the concentrations of primary air pollutants are selected, and set as target variables to predict their expected values during the city's lockdown period.The obtained results suggest that if a 21-days lockdown is implemented, then a reduction of 42 µg m−3 in PM10, 23 µg m−3 in PM2.5, 14 µg m−3 in NO2, 2 µg m−3 in SO2, and 0.7 mg m−3 in CO can be achieved. 相似文献
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We show that the excellent optical and gamma-ray data available for GRB 080319B rule out the internal shock model for the prompt emission. The data instead point to a model in which the observed radiation was produced close to the deceleration radius (∼1017 cm) by a turbulent source with random Lorentz factors of ∼10 in the comoving frame. The optical radiation was produced by synchrotron emission from relativistic electrons, and the gamma-rays by inverse-Compton scattering of the synchrotron photons. The gamma-ray emission originated both in eddies and in an inter-eddy medium, whereas the optical radiation was mostly from the latter. Therefore, the gamma-ray emission was highly variable whereas the optical was much less variable. The model explains all the observed features in the prompt optical and gamma-ray data of GRB 080319B. We are unable to determine with confidence whether the energy of the explosion was carried outwards primarily by particles (kinetic energy) or magnetic fields. Consequently, we cannot tell whether the turbulent medium was located in the reverse shock (we can rule out the forward shock) or in a Poynting-dominated jet. 相似文献
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