Abstract
The Lower Saxonian Elbe Valley Biosphere Reserve is part of the UNESCO Biosphere Reserve “Elbe River Landscape”, and used mainly for agriculture. One of tasks of the Biosphere Reserve Administration is to develop sustainable forms of land use which requires comprehensive updated land cover maps. Land use maps are hard to produce because of surveying costs and time. Nevertheless, these large areas need to be monitored. TerraSAR-X images are used to establish agricultural land use maps. In this study, two areas are selected within the Elbe Biosphere Reserve situated around the oxbows Wehninger Werder and Walmsburger Werder. Multi temporal classification methods were used to identify the different crops using maximum likelihood classifier for the years 2010 and 2011. The crop classifications were used to evaluate the effect of the number of images, the necessity of polarizations, and the consequences of some missing images within the crop calendar. These classifications were analyzed to estimate producer accuracy and Kappa index for each crop besides the overall accuracy for each agricultural land use map. The study shows that using dual polarization imagery enhances producer accuracies for many crops over the single polarization imagery, and demonstrates the importance of using frequent images during the cultivation period.
Highlights
The Elbe River flows through four countries namely Germany, the Czech Republic, Austria and Poland. 65% of the river basin lies in Germany [1]
This study identifies the agricultural land uses within two study areas
Two study areas are selected around the Wehninger Werder between Elbe-Kilometer (505 - 520), and Walmsburger Werder between Elbe-Kilometer (533 - 543) within the Lower Saxonian Elbe River Biosphere Reserve (Figure 3)
Summary
Some studies recommend using higher frequency signals such as X-band where the signals are more reflected by the vegetation cover [16] This enables better crop classification results where the classification process identifies patterns of similar characteristics according to the corresponding observed backscattering response and their temporal progress. This study identifies the agricultural land uses within two study areas The images are used to produce several proper classifications which identify the crops cultivated in the investigated areas based on the field visits. The test fields are assumed to be remote inaccessible areas
Sign-in/Register to view highlights & summary 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.
