Fraunhoffer Diffraction Analysis of Satellite Cloud Imagery

The Fraunhoffer diffraction analysis of cloud-covered satellite imagery has shown that the diffraction pattern follows approximately cosine squared distribution. The overshooting tops of clouds and the shadows cast by them contribute much to the diffraction of light, particularly in the high-frequency range. Indeed, cloud-covered imagery can be distinguished from cloud-free imagery on the basis of rate of decay of the diffracted light power in the high-frequency band.

Electron Cyclotron Resonance in Strained Si and Si0.94Ge0.06 Channels on Relaxed Si0.62Ge0.38 Buffers Grown by Rapid Thermal Chemical Vapor Deposition

We report the far-infrared measurements of the electron cyclotron resonance absorption in n-type Si/Si0. 62Ge0.38 and Si0.94Ge0.06 /Si0. 62Ge0.38 modulation- doped heterostructures grown by rapid thermal chemical vapor deposition. The strained Si and Si0.94Ge0.06 channels were grown on relaxed Si0.62Ge0.38 buffer layers, which consist of 0.6 μm uniform Si0.62Ge0.38 layers and 0.5 μm compositionally graded relaxed SiGe layers from 0% Ge to 38 % Ge. The buffer layers were annealed at 800 °C for 1 hr to obtain complete relaxation. The samples had 100 Å spacers and 300 Å 2×1019 cm-3 n-type supply layers on the tops of the 75 Å channels. The far-infrared measurements of electron cyclotron resonance were performed at 4K with the magnetic field of 4 – 8 Tesla. The effective masses determined from the slope of center frequency of absorption peak vs applied magnetic field plot are 0.20 mo and 0.19 mo for the two dimensional electron gases in the Si and Si0.94Ge0.06 channels, respectively. The Si effective mass is very close to that of two dimensional electron gas in Si MOSFET (0.198mo). The electron effective mass of Si0.94Ge0.06 is reported for the first time and about 5 % lower than that of pure Si.

Vegetation Status in Uttara Kannada District

Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years, and natural forests have declined.

Vegetation Analysis in Uttara Kannada District Using GIS and Remote Sensing Techniques

Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years,and natural forests have declined.

A 10 tesla table-top controlled waveform magnet

Controlled waveform magnets (CWMs) are a class of pulsed magnets whose pulse shape with time can be programmed by the user. With a CWM, the user gains control not only over the magnitude of the field but also over its rate of change. In this work we present a table-top CWM, driven by a capacitor bank, capable of producing virtually any user-shaped magnetic field waveform up to 10 tesla. Insulated gate bipolar transistor chips have been paralleled to form the high current switch and paralleled chips of SiC Schottky diodes form the crowbar diode module. Sample controlled waveforms including flat-tops up to 10 tesla and some triangular magnetic field pulses have been successfully generated for 10-20 ms with a ripple < 1%. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.3699316]

Estimation of Aboveground Phytomass of Plantations Using Digital Photogrammetry and High Resolution Remote Sensing Data

The study follows an approach to estimate phytomass using recent techniques of remote sensing and digital photogrammetry. It involved tree inventory of forest plantations in Bhakra forest range of Nainital district. Panchromatic stereo dataset of Cartosat-1 was evaluated for mean stand height retrieval. Texture analysis and tree-tops detection analyses were done on Quick-Bird PAN data. The composite texture image of mean, variance and contrast with a 5x5 pixel window was found best to separate tree crowns for assessment of crown areas. Tree tops count obtained by local maxima filtering was found to be 83.4 % efficient with an RMSE+/-13 for 35 sample plots. The predicted phytomass ranged from 27.01 to 35.08 t/ha in the case of Eucalyptus sp. while in the case of Tectona grandis from 26.52 to 156 t/ha. The correlation between observed and predicted phytomass in Eucalyptus sp. was 0.468 with an RMSE of 5.12. However, the phytomass predicted in Tectona grandis was fairly strong with R-2=0.65 and RMSE of 9.89 as there was no undergrowth and the crowns were clearly visible. Results of the study show the potential of Cartosat-1 derived DSM and Quick-Bird texture image for the estimation of stand height, stem diameter, tree count and phytomass of important timber species.