Master Thesis Remote Sensing Projects
Master Thesis Remote Sensing Projects service introduces by our 10+ years of experienced professionals with the target of create technological revolution among worldwide scholars in this scientific battlefield. Our world’s top scientists dedicate their scientific research life for plenty of students and research guys. Day by day, our dedicative experts create own ingenious and genius ideas for you to upgrade your proficiency and ability in your research career. We are available to give our guidance forever.
Topmost Research Topics for Master Thesis Remote Sensing Projects:
- High resolution remote sensing image change detection based on law of cosines with box-whisker plot
- A water extraction method based on airborne hyper spectral images in highly complex urban area
- Sea ice type classification based on random forest machine learning with Cryosat-2 altimeter data
- A weakly supervised road extraction approach via deep Convolutional nets based image segmentation
- An enhanced deep Convolutional neural network for densely packed objects detection in remote sensing images [Master Thesis Remote Sensing Projects]
- Feature enhancement for multi-polarimetric SAR images: A novel approach based on PDE and regularization
- Low-rank matrix decomposition with a spectral-spatial regularization for change detection in hyper spectral imagery
- Superpixel-based multiple change detection in very-high-resolution remote sensing images
- Multi-temporal PolSAR crops classification using polarimetric feature driven deep Convolutional neural network
- Change detection of SAR images based on supervised contractive auto encoders and fuzzy clustering
- Evaluation of clustering algorithms for unsupervised change detection in VHR remote sensing imagery
- Modeling soil sealing density in residential areas for Flanders and the Brussels capital region
- Issues and challenges of remote sensing-based local climate zone mapping for high-density cities [Master Thesis Remote Sensing Projects]
- Providing water for the poor – towards optimal water supply infrastructures for informal settlements by using remote sensing data
- Automated supervised classification of Ouagadougou built-up areas in Landsat scenes using OpenStreetMap
