Text
Multitemporal image analysis for monitoring fuzzy shorelines
Rapid development and population growth in coastal areas always bring a risk of coastal damage. In this situation, monitoring of shoreline position plays an impotant role in achieving a balanced condition between economic development and coastal protection. For this purpose, local autorities and coastal planners reqiure information on shoreline changes for coastal land use planning and disaster risk management. Monitoring shoreline change for larger areas and longer time spans, however, is challanging due to limited data availability and hight cost. Remote sensing and specific image processing methods for the identification and monitoring of shoreline are needed, especially methods that can handle the uncertainty in shoroline positions.This disertation investigates and develops image analysis methid from remote sensing images to provide information for the sustainable coastal development. It focuses on using a fuzzy classification and a change detection technique to identify shorelines and monitor their change.Emphasis is given on data quality and the estimation of uncertainty. The methods proposed in this dissertation are applied on a series of images to identify shoreline positions in the nourthn part of central java province, Indonesia which experienced a serve change of shoreline position over three decades.
B20190419288 | DS 621.3678 RAT m | Perpustakaan BIG (500) | Tersedia |
B20190725318 | DS 621.3678 RAT m | Perpustakaan BIG (500) | Tersedia |
Tidak tersedia versi lain