English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

study introduced an object-oriented approach to flood mapping and affected field estimation in central Cambodia. Traditional pixel-based image algorithms for flood mapping and land use and land cover classification endure from low accuracy, sub-pixel problems, and the cover noise effect in the resulting images On the other hand, the object-based image analysis (OBIA) approach has been thoroughly developed in the last two decades to overcome the limitations and disadvantages of the traditional pixel-based approaches by generating and analyzing meaningful image objects instead of individual pixels and reducing the speckle noise effect. The OBIA approach was applied for the image classification with a new improved estimation algorithm with multi scale parameter in the segmentation process to obtain more accurate results in the flood mapping. Flooding can be recognized using a variety of approaches such as statistics, ground-based measuring, prediction model, remote sensing techniques.

Object-Oriented Approach of Landsat Imagery for Flood Mapping