Soil monitoring for precision farming using hyperspectral remote sensing and soil sensors
| Autor: | Michele Bandecchi, Wolfgang Gross, Dubravko Culibrk, Wolfgang Middelmann, Simon Schreiner |
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| Přispěvatelé: | Publica |
| Rok vydání: | 2021 |
| Předmět: |
KI
hyperspectral remote sensing Bodenüberwachung 0211 other engineering and technologies Hyperspectral imaging Hyperspektrale Fernerkundung 04 agricultural and veterinary sciences 02 engineering and technology Computer Science Applications AI 2D / 3D pedological maps Control and Systems Engineering Remote sensing (archaeology) soil monitoring 040103 agronomy & agriculture 2D / 3D pedologische Karten 0401 agriculture forestry and fisheries Environmental science Precision agriculture Electrical and Electronic Engineering 021101 geological & geomatics engineering Remote sensing |
| Zdroj: | at - Automatisierungstechnik. 69:325-335 |
| ISSN: | 2196-677X 0178-2312 |
| DOI: | 10.1515/auto-2020-0042 |
| Popis: | This work describes an approach to calculate pedological parameter maps using hyperspectral remote sensing and soil sensors. These maps serve as information basis for automated and precise agricultural treatments by tractors and field robots. Soil samples are recorded by a handheld hyperspectral sensor and analyzed in the laboratory for pedological parameters. The transfer of the correlation between these two data sets to aerial hyperspectral images leads to 2D-parameter maps of the soil surface. Additionally, rod-like soil sensors provide local 3D-information of pedological parameters under the soil surface. The goal is to combine the area-covering 2D-parameter maps with the local 3D-information to extrapolate large-scale 3D-parameter maps using AI approaches. |
| Databáze: | OpenAIRE |
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