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Evolution of Remote Sensing and Graphical Information System Using CPU-GPU Platform

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Evolution of Remote Sensing and Graphical Information System Using CPU-GPU Platform

Suman Goyat | Dr A K Sahoo

Suman Goyat | Dr A K Sahoo "Evolution of Remote Sensing and Graphical Information System Using CPU-GPU Platform" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18731.pdf

The Earth's land use, land cover, land forms, spatial and geographical characteristics are crucial variables in global change. The impact of human activities on the earth has resulted greatly to climate change calls for a comparative study and mapping of the land in order to assess the condition of the land in the past comparing with the current state of the land in order to regulate the anthropogenic factors for sustainable development. Remote Sensing and Geographic Information Services allow the engineer to continuously monitor any change any intended plans to secure their success or rectification to meet the requirements. GIS technology has a major impact on the safety and quality of our daily lives. City planners and businesses use GIS applications to combine physical mapping information with demographic data such as population, street layout and local resources. As users push the boundaries of GIS applications, datasets are growing increasingly complex, often involving many gigabytes of interactive maps showing vectors, surface layers and images. As the amount of data and the complexity of the processing rise, the demand for processing power in GIS applications is increasing. The processing speed is a critical aspect to enable a productive interaction between the human operator and the machine in order to achieve ever more complex tasks satisfactorily. Graphic processing units (GPU) are good candidates to speed up some tasks. With the recent developments, programming these devices became very simple. In this paper, we introduce the method how complexity of RS and GIS can be reduced by implementing parallel architecture of GPU.

GPU (Graphics Processing Unit), HPC (High-Performance Computing), NDVI (Normalized Difference Vegetation Index), GPS (Global Positioning System), GIS (Geographical Information System), RS (Remote System), CUDA (Compute Unified Device Architecture),


Volume-2 | Issue-6 , October 2018

2456-6470

IJTSRD18731