Syed Sohel Ali

PhD Research Student

Current Academic Program

• Thesis Title
  Integration of Multi-spectral Imagery and Laser Scanner Data for Land cover Classifications: Pixel and Feature Level Approaches
  
• Thesis Abstract
  Remote sensing from airborne and spaceborne platforms provides valuable data in various forms and scales for mapping and monitoring earth resources. The trend has increased dramatically in recent times due to availability of high-resolution multi-spectral images and high-density Airborne Laser Scanner (ALS) data. However, to explore the full value of these data, the appropriate information has to be extracted and presented in an integrated (fusion) format, which is more suitable for human and machine perception or further image-processing tasks such as segmentation, feature extraction and object recognition. This research intends to develop a data fusion model, which will not only integrate different sensor derived multi-spectral image data but also integrate ALS data. This model will provide a basis to integrate various sensor data for landcover monitoring and environmental change analysis. An object-based fusion will be implemented followed by a pixel-based approach to compare their fusion efficiency.

Publications