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Library Land cover recognition using min-cut/max-flow segmentation and orthoimages

Land cover recognition using min-cut/max-flow segmentation and orthoimages

Land cover recognition using min-cut/max-flow segmentation and orthoimages

Resource information

Date of publication
декабря 2015
Resource Language
ISBN / Resource ID
AGRIS:LV2016000156
Pages
127-133

The geospatial information is significant for many socio-technical activities like urban planning, the prediction of natural hazards, the monitoring of land use, weather forecasting, cadastral surveys etc. It is possible to acquire geospatial information from a distance using remote sensing technologies, but remotely sensed images don’t have semantics without a previous recognition. The classification of geospatial information is expensive and time consuming process. The paper describes the automatic land cover recognition method, which is based on min-cut/max-flow segmentation. The raw data are orthoimages with a high resolution. The proposed method is tested and evaluated by Cohen’s kappa coefficient.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Kodors, S., Rezekne Higher Education Institution (Latvia)

Data Provider
Geographical focus