Sea breeze activity at an inland station Kharagpur (India) — A case study

Surfaces fluxes, turbulent kinetic energy and Flux Richardson number are calculated for three typical sea breeze days characterizing three types of sea breeze onset at an inland station Kharagpur (22°21 N, 87°19 E), 80 km inland, one of the sites for MONTBLEX (MONsoon Trough Boundary Layer EXperiment), in India. The sea breeze onset is associated with a decrease in momentum and heat fluxes and an increase in moisture flux. The turbulent kinetic energy shows quite a significant value even in the late afternoon. The surface layer becomes nearly stable even before sunset, due to the passage of the sea breeze.     

Interpolation of climate variables and temperature modeling

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.     

High-resolution satellite image segmentation using Hölder exponents

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.     

Studies on Schumann Resonance Phenomena and Some Recent Advancements

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...     

Segmentation and classification of high spatial resolution images based on Hölder exponents and variance

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%.     

Lunar ranging instrument for Chandrayaan-1

Lunar Laser Ranging Instrument (LLRI) proposed for the first Indian lunar mission Chandrayaan-1 is aimed to study the topography of the Moon’s surface and its gravitational field by precisely measuring the altitude from a polar orbit around the Moon. Altimetry data close to the poles of the Moon would also be available from the instrument, which was not covered by earlier missions. This instrument supplements the terrain mapping camera and hyperspectral imager payloads on Chandrayaan-1. The instrument consists of a diode pumped Nd:YAG pulsed laser transmitter having 10 nsec pulse width and a receiver system. The receiver system features 17 cm diameter Ritchey—Chrétien collecting optics, Si Avalanche Photo Detector (APD), preamplifiers, constant fraction discriminators, time-of-flight measurement unit and spacecraft interface. Altimeter resolution of better than 5 m is targeted. The received signal strength of LLRI depends on laser pulse backscatter from the Moon’s surface. Moon’s surface being a poor reflector, the choice of receiver size and its type and the selection of detector play an important role in getting a good signal-to-noise ratio and in turn achieving the target resolution. At the same time, the spacecraft puts a limitation on payload size and weight. This paper discusses the proposed LLRI system for Chandrayaan-1 and signal-to-noise ratio estimation.     

Geomorphological study of sundarban deltaic estuary

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.     

Land use alterations and its possible impact on premonsoon climatic variables

Changes in land surface characteristics have become a matter of great concern in the recent years. It is particularly important when the mesoscale phenomena control the climatic variables of a region. Gangetic West Bengal with its neighbourhood is such a region where during premonsoon season, mesoscale phenomena, i.e., sea breeze circulation and severe convective development, control the local climate of the season. It is also reported that a drastic changes in land use pattern has taken place in recent period over the region, which might affect the local climate, resulting in severe water crisis over the semi-arid part of the region. A detailed study has been undertaken to investigate the changes in land use pattern through satellite data over the area and its possible impact on the local climate through numerical modeling. Satellite (IRS-IC and Landsat 4 and 5) data shows a sharp change in dynamic vegetation during this period, which is due to, increased agricultural practices in the recent years. Mesoscale model indicates that agricultural practices hinder the development of sea breezes over the coastal and inland places, causing less incursion of moisture towards inland. This may be associated with less number of convective developments over the coastal and neighbouring places.     

Geochemistry of the Neoproterozoic Narji limestone,Cuddapah Basin,Andhra Pradesh,India: implication on palaeoenvironment

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.