Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots. This type of work will be quite helpful in the near future to develop a hotspots monitoring system using these operational satellites data.     

Innovations for competitiveness: European views on “better-faster-cheaper”

The paper elaborates on “ lessons learned” from two recent ESA workshops, one focussing on the role of Innovation in the competitiveness of the space sector and the second on technology and engineering aspects conducive to better, faster and cheaper space programmes. The paper focuses primarily on four major aspects, namely:

1. a) the adaptations of industrial and public organisations to the global market needs;

2. b) the understanding of the bottleneck factors limiting competitiveness;

3. c) the trends toward new system architectures and new engineering and production methods;

4. d) the understanding of the role of new technology in the future applications.

Under the pressure of market forces and the influence of many global and regional players, applications of space systems and technology are becoming more and more competitive. It is well recognised that without major effort for innovation in industrial practices, organisations, R&D, marketing and financial approaches the European space sector will stagnate and loose its competence as well as its competitiveness. It is also recognised that a programme run according to the “better, faster, cheaper” philosophy relies on much closer integration of system design, development and verification, and draws heavily on a robust and comprehensive programme of technology development, which must run in parallel and off-line with respect to flight programmes.

A company's innovation capabilities will determine its future competitive advantage (in time, cost, performance or value) and overall growth potential. Innovation must be a process that can be counted on to provide repetitive, sustainable, long-term performance improvements. As such, it needs not depend on great breakthroughs in technology and concepts (which are accidental and rare). Rather, it could be based on bold evolution through the establishment of know-how, application of best practices, process effectiveness and high standards, performance measurement, and attention to customers and professional marketing. Having a technological lead allows industry to gain a competitive advantage in performance, cost and opportunities. Instrumental to better competitiveness is an R&D effort based on the adaptation of high technology products, capable of capturing new users, increasing production, decreasing the cost and delivery time and integrating high level of intelligence, information and autonomy. New systems will have to take in to account from the start what types of technologies are being developed or are already available in other areas outside space, and design their system accordingly. The future challenge for “faster, better, cheaper” appears to concern primarily “cost-effective”, performant autonomous spacecraft, “cost-effective”, reliable launching means and intelligent data fusion technologies and robust software serving mass- market real time services, distributed via EHF bands and Internet.

In conclusion, it can be noticed that in the past few years new approaches have considerably enlarged the ways in which space missions can be implemented. They are supported by true innovations in mission concepts, system architecture, development and technologies, in particular for the development of initiatives based on multi-mission mini-satellites platforms for communication and Earth observation missions. There are also definite limits to cost cutting (such as lowering heads counts and increasing efficiency), and therefore the strategic perspective must be shifted from the present emphasis on cost-driven enhancement to revenue-driven improvements for growth. And since the product life-cycle is continuously shortening, competitiveness is linked very strongly with the capability to generate new technology products which enhance cost/benefit performance.     

Modelling and observations of photospheric magnetic helicity

Mounting observational evidence of the emergence of twisted magnetic flux tubes through the photosphere have now been published. Such flux tubes, formed by the solar dynamo and transported through the convection zone, eventually reach the solar atmosphere. Their accumulation in the solar corona leads to flares and coronal mass ejections. Since reconnections occur during the evolution of the flux tubes, the concepts of twist and magnetic stress become inappropriate. Magnetic helicity, as a well preserved quantity, in particular in plasma with high magnetic Reynolds number, is a more suitable physical quantity to use, even if reconnection is involved.     

Spectral-domain covariance estimation with a priori knowledge

A knowledge-aided spectral-domain approach to estimating the interference covariance matrix used in space-time adaptive processing (STAP) is proposed. Prior knowledge of the range-Doppler clutter scene is used to identify geographic regions with homogeneous scattering statistics. Then, minimum-variance spectral estimation is used to arrive at a spectral-domain clutter estimate. Finally, space-time steering vectors are used to transform the spectral-domain estimate into a data-domain estimate of the clutter covariance matrix. The proposed technique is compared with ideal performance and to the fast maximum likelihood technique using simulated results. An investigation of the performance degradation that can occur due to various inaccurate knowledge assumptions is also presented