Abstract
Agricultural crops in plains or depressions (mainly cotton. maize and sugarbeets), suffer not only from diseases and frost, but also from floods, when heavy rains fall during sensitive phenological stages, e.g. during seeding or ripening. The usual cloudy weather, during and after the event, does not allow the use of optical sensors for qualitative and quantitative monitoring of the flooded area. On the other hand, flood monitoring, when images from radar sensors are used, suffer from classification problems, due mainly to the confusion created by the similar radiometric behaviour of flood pixels and the hill shade pixels, resulting in misclassification, qualitatively and quantitatively, of the flood extent and intensity. Digital Elevation Model (DEM) was used to overcome the above difficulties, thus "pushing" the classification algorithm to read only water return signal from plains and depressions and rejecting similar signals from slopping areas.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
