Detection of land use and land cover from an optical remote sensing image is an essential research area from the inception of a remote sensing image. Land use land cover maps have numerous applications in agriculture, environment monitoring, urban planning, etc, along with managing various catastrophic events like floods, tsunamis, forest fires, etc. This paper reviewed major techniques for detection of land use and land cover from an optical remote sensing image. Many techniques based on only spectral information, spatio-contextual information and knowledge based methods have been discussed, finally arguing the importance of the techniques based on spatio-contextual information and Mathematical Morphology.
This paper shows the importance of fair scheduling in grid environment such that all the tasks get equal amount of time for their execution such that it will not lead to starvation. The load balancing of the available resources in the computational grid is another important factor. This paper considers uniform load to be given to the resources. In order to achieve this, load balancing is applied after scheduling the jobs. It also considers the Execution Cost and Bandwidth Cost for the algorithms used here because in a grid environment, the resources are geographically distributed. The implementation of this approach the proposed algorithm reaches optimal solution and minimizes the make span as well as the execution cost and bandwidth cost.
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