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2021 | OriginalPaper | Buchkapitel

Digital Terrain Models Generation based on GNSS-Acquired Data

verfasst von : Aurelia Maria Moanta, Oleg Rostanin, Tanja Riedel, Stephan Estel, Christoph Federle, Christian Bartolein

Erschienen in: Commercial Vehicle Technology 2020/2021

Verlag: Springer Fachmedien Wiesbaden

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The rapid population growth, cost pressure and environmental requests have changed the way agriculture is done by pushing both the industry and the farmers to develop and invest in efficient and sustainable technologies, aimed at improving crop yields and reduce input costs.A special attention is required by the application of pesticides, whose usage affects not only the crops, but also the environment. When applying pesticides highest precision is required, non-targeted area must not be contaminated and regulations e.g. in regard to buffer zones, where spraying is prohibited, must be met. Since pesticide contamination can occur not only through direct application, but also through run-off or erosion, the German law stipulates the presence of buffer zones between targeted areas and adjacent waterbodies.The PAM3D project aims to integrate elevation information in the computation of buffer zones by using Digital Elevation Models (DEMs). Based on DEMs, the slope parameter can be derived and further introduced into the computation of buffer zones. The progress made in the GNSS field, where the repeatable accuracy can go up to ± 2 cm (RTK techniques), makes the documentation data from various field operations a viable source of 3D coordinates, from which highquality DEMs can be generated through kriging interpolation method.Furthermore, a cloud-based service with capabilities to process and store 3D information from GNSS receivers has been implemented, together with APIs necessary for enabling the communication between users and service.

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Metadaten
Titel
Digital Terrain Models Generation based on GNSS-Acquired Data
verfasst von
Aurelia Maria Moanta
Oleg Rostanin
Tanja Riedel
Stephan Estel
Christoph Federle
Christian Bartolein
Copyright-Jahr
2021
DOI
https://doi.org/10.1007/978-3-658-29717-6_3

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