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Interpolation of climate variables and temperature modeling 总被引：1，自引：0，他引：1
Sailesh Samanta Dilip Kumar Pal Debasish Lohar Babita Pal 《Theoretical and Applied Climatology》2012,107(1-2):35-45
Geographic Information Systems (GIS) and modeling are becoming powerful tools in agricultural research and natural resource management. This study proposes an empirical methodology for modeling and mapping of the monthly and annual air temperature using remote sensing and GIS techniques. The study area is Gangetic West Bengal and its neighborhood in the eastern India, where a number of weather systems occur throughout the year. Gangetic West Bengal is a region of strong heterogeneous surface with several weather disturbances. This paper also examines statistical approaches for interpolating climatic data over large regions, providing different interpolation techniques for climate variables' use in agricultural research. Three interpolation approaches, like inverse distance weighted averaging, thin-plate smoothing splines, and co-kriging are evaluated for 4°?×?4° area, covering the eastern part of India. The land use/land cover, soil texture, and digital elevation model are used as the independent variables for temperature modeling. Multiple regression analysis with standard method is used to add dependent variables into regression equation. Prediction of mean temperature for monsoon season is better than winter season. Finally standard deviation errors are evaluated after comparing the predicted temperature and observed temperature of the area. For better improvement, distance from the coastline and seasonal wind pattern are stressed to be included as independent variables. 相似文献
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Debasish Chakraborty Gautam Kumar Sen Sugata Hazra 《Journal of Earth System Science》2009,118(5):609-617
Texture in high-resolution satellite images requires substantial amendment in the conventional segmentation algorithms. A measure is proposed to compute the Hölder exponent (HE) to assess the roughness or smoothness around each pixel of the image. The localized singularity information is incorporated in computing the HE. An optimum window size is evaluated so that HE reacts to localized singularity. A two-step iterative procedure for clustering the transformed HE image is adapted to identify the range of HE, densely occupied in the kernel and to partition Hölder exponents into a cluster that matches with the range. Hölder exponent values (noise or not associated with the other cluster) are clubbed to a nearest possible cluster using the local maximum likelihood analysis. 相似文献
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Abhijit Ghosh Biswas Debasish Hazra Pranab Guha Gautam De S. S. 《Geomagnetism and Aeronomy》2019,59(8):980-994
Geomagnetism and Aeronomy - Discrete spectra of frequencies at 8, 14, 20, 26, … Hz are generated by electromagnetic emission from lightning sources and can be regarded as excitation of AC... 相似文献
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Debasish Sarkar Sudip Kumar Das Paramartha Mukherjee Amitava Bandyopadhyay 《洁净——土壤、空气、水》2010,38(8):764-770
Experiments have been carried out to characterize the adsorption of chromium(VI) in the aqueous phase onto dried roots of water hyacinth. Results revealed a very high degree of removal efficiency (∼100%). Theoretical analyzes are also made for describing the sorption and diffusion processes. The effective pore diffusivity of chromium(VI) in the water hyacinth roots is determined by a suitable global optimization technique. The depth of penetration, on the other hand, has been estimated for various initial concentrations of chromium(VI). Theoretically predicted concentration profiles are in excellent agreement with the experimental values. 相似文献
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The Neoproterozoic Narji Formation of Cuddapah Basin, Southern India is mainly composed of limestones with minor amount of clastic rocks. Limestones are massive as well as laminated and occasionally chert bearing. Geochemistry (major, trace, and REE) of limestones is studied to strengthen the knowledge on depositional environment of Narji Formation in the direction to better figure out the development of Cuddapah Basin during Neoproterozoic era. Average SiO2 (25.97), Al2O3/TiO2 (16.67), and K2O/Al2O3 (0.21) ratios suggest clastic contamination in the Narji limestones. PAAS (Post Archean Australian Shale) normalized REE?+?Y pattern of Narji limestones are showing seawater like REE?+?Y pattern. The Er/Nd and Y/Ho ratios (average 0.17 and 35.68, respectively) of Narji limestones indicate the retention of normal seawater character with the signatures of terrigenous input and diagenesis process. Positive Ce anomaly, high U/Th (>?1.25), and V/(V?+?Ni) (>?0.5) ratios of Narji limestones clearly indicate their deposition in dyoxic to anoxic condition. 相似文献
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Pixel-based or texture-based classification technique individually does not yield an appropriate result in classifying the high spatial resolution remote sensing imagery since it comprises textured and non-textured regions. In this study, Hölder exponents (HE) and variance (VAR) are used together to transform the image for measuring texture. A threshold is derived to segment the transformed image into textured and non-textured regions. Subsequently, the original image is extracted into textured and non-textured regions using this segmented image mask. Afterward, extracted textured region is classified using ISODATA classification algorithm considering HE, VAR, and intensity values of individual pixel of textured region. And extracted non-textured region of the image is classified using ISODATA classification algorithm. In case of non-textured region, HE and VAR value of individual pixel is not considered for classification for significant textural variation is not found among different classes. Consequently, the classified outputs of non-textured and textured regions that are generated independently are merged together to get the final classified image. IKONOS 1 m PAN images are classified using the proposed algorithm, and the classification accuracy is more than 88%. 相似文献
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Dipnarayan Ganguly Anirban Mukhopadhyay Rahul Krishna Pandey Debasish Mitra 《Journal of the Indian Society of Remote Sensing》2006,34(4):431-435
Study of landforms in Sundarbans deltaic estuary is necessary in regular basis due to its importance and impact on ecology,
climate and economy. Remote sensing has proved as an important tool to study this. Multi-temporal satellite data helps to
delineate the various geomorphic classes in different time domain and also provide inputs to study the coastal erosion and
accretion. Finer spatial and better temporal resolution will be an added adventure for this kind of study. 相似文献
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The carbonate-dominated Palaeo-Mesoproterozoic Vempalle Formation of the Cuddapah Basin, Southern India, represents deposition in a supratidal-subtidal setting. The facies associations, deciphered from this study, are consistent with continued gradual rise of sea level with little or no sedimentary influx during the deposition of sediments, wherein gradual deposition of carbonates are recorded with increased accommodation. The broad development of stromatolites in different layers of sediments across the coast indicates a moderately high-energy open coastline. The prolific volcanism as recorded at the top of the succession ultimately shuts down the Vempalle carbonate factory. 相似文献
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Debasish?Chakraborty Vinay?Kumar?SehgalEmail authorView author&#;s OrcID profile Rajkumar?Dhakar Eldho?Varghese Deb?Kumar?Das Mrinmoy?Ray 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(11):3067-3081
This study used gridded daily maximum temperature data (1°?×?1°) for 1951–2014 period to analyze the trend in monthly extreme warm days (ExWD) and changes in its probability distribution in each grid. It also analyzed the trend in spatial spread of annual ExWD over the study period at four exceedance levels and further related the number of ExWDs with cereal crop productivity of India. Extreme warm days have increased throughout India but were statistically significant in 42% grids. The increase was consistent over all the months in north-eastern region, southern plateau and both the coastal plains. It also increased significantly over north-western and central India during April to June summer period. The probability distribution of ExWD also changed significantly in many grids, especially in southern plateau and both the coastal plains. The changes indicated increased frequency in the existing levels of extremes and new occurrences of higher frequency of extremes. The analysis of land area affected by different levels of extremes indicated significant increase, with the rate being highest for higher extremes. In terms of extreme warm day temperatures, the study identified southern plateau, east and west coast plains, and north-eastern India as highly vulnerable. Using copula probability model, study showed that increase in ExWD from 20 to 60% may increase the probability of 5% or more yield loss from 17 to 53% for Kharif cereals, 11 to 43% for Rabi cereals and 19 to 63% for wheat crop. The results may be used for devising zone specific adaptation strategies. 相似文献