Data processing in remote sensing

A brief overview of pattern recognition and image processing with special emphasis on the first topic and its application to remote sensing is presented. Some of the recent areas of work in pattern recognition are also highlighted

Recent trends in remote sensing data analysis

Seventh Vikram Sarabhai Memorial Lecture delivered at the time of National Symposium on Remote Sensing for Natural Resources with special emphasis on Infrastructure Development and Annual Convention of Indian Society of Remote Sensing on November 26, 1997

The x&#194;&#191;<SUP>n</SUP>-x plane for analysis of certain second-order nonlinear systems

Analysis of certain second-order nonlinear systems, not easily amenable to the phase-plane methods, and described by either of the following differential equations x&#194;&#191;n-2&#194;&#191;+ f(x)x&#194;&#191;2n+g(x)x&#194;&#191;n+h(x)=0 &#194;&#191;+f(x)x&#194;&#191;n+h(x)=0 n &#187; 0 can be effected easily by drawing the entire portrait of trajectories on a new plane; that is, on one of the x&#194;&#191;n&#194;&#191;x planes. Simple equations are given to evaluate time from a trajectory on any of these n planes. Poincar&#194; &#169; 's fundamental phase plane x &#194;&#191;&#194;&#191;x is conceived of as the simplest case of the general x&#197;&#191;n&#197;&#191;x plane

Techniques for analysis of certain nonlinear systems

This paper suggests the use of simple transformations like &#194; &#191;=kx, kx2 for second-order nonlinear differential equations to effect rapid plotting of the phase-plane trajectories. The method is particularly helpful in determining quickly the trajectory slopes along simple curves in any desired region of the phase plane. New planes such as the t &#194; &#191; -x, t &#194; &#191;2-x are considered for the study of some groups of nonlinear time-varying systems. Suggestions for solving certain higher-order nonlinear systems are also made

Remote sensing of environment - critical issues

An ecologically sustained environment is basically needed for achieving selfreliance in food, fodder and water requirements. In order to achieve the self-reliance in natural resources environment the holistic approach on every resource sector need to be concentrated in all levels of local, regional and global scales. The increase in population both human and livestock is further aggravating the demands on land, forcing decrease in per capita land either for agriculture or for fodder. The present 0.17 hectare per capita agricultural land in India indicates unsustainable nature to meet the food grain demand for the growing population. On the other hand we have in India around 2.38 lakh sq.km of waste lands which can be brought to agriculture in order to meet the gap in the food grain production. The reclamation and conservation of wastelands for bringing more area under agriculture needs a greater attention wherein sound ecological practices can only provide solutions. The use of satellite remote sensing and the availability of IRS1A and IB would further enhance the scope and provide information on all the vital resources sectors in a time and cost effective manner. The concept of "productivity per unit of water" need to be given adequate importance in all the environmental management programmed rather than concentrating on "productivity per unit area". The ecological degradation that is presently draining our country's vast natural resources can only be halted by the concerted effort by all the section of scientists who can provide solutions and create greater awareness on ecological conservation to preserve and nurture the India's environment on a sustained basis. The estimates, statistics and figures have always been the subject of conflict and debate. Whatever is the accuracy on reliability on these projections and estimates we are amply sure and convinced that our environment is threatened. The adoption of modern technological tools such as remote sensing would certainly provide greater insights synoptically on a time and cost effective manner

Landsat TM image of part of southern India

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