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Schnug, E
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Authors
Lilienthal, H
Wilde, P
Schnug, E
Gerighausen, H
Lilienthal, H
Schnug, E
Lilienthal, H
Gerighausen, H
Schnug, E
Lilienthal, H
Schnug, E
Haneklaus, S
Lilienthal, H
Haneklaus, S.H
Schnug, E
Lilienthal, H
Gerighausen, H
Schnug, E
Topics
Proximal Sensing in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
No Group Selected
Site-Specific Nutrient, Lime and Seed Management
Geospatial Data
Type
Oral
Year
2016
2018
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Authors

Filter results6 paper(s) found.

1. Proximal Hyperspectral Sensing in Plant Breeding

The use of remote sensing in plant breeding is challenging due to the large number of small parcels which at least actually cannot be measured with conventional techniques like air- or spaceborne sensors. On the one hand crop monitoring needs to be performed frequently, which demands reliable data availability. On the other hand hyperspectral remote sensing offers new methods for the detection of vegetation parameters in crop production, especially since methods for safe and efficient detection... H. Lilienthal, P. Wilde, E. Schnug

2. Non-destructive Plant Phenotyping Using a Mobile Hyperspectral System to Assist Breeding Research: First Results

Hybrid plants feature a stronger vigor, an increased yield and a better environmental adaptability than their parents, also known as heterosis effect. Heterosis of winter oilseed rape is not yet fully understood and conclusions on hybrid performance can only be drawn from laborious test crossings. Large scale field phenotyping may alleviate this process in plant breeding. The aim of this study was to test a low-cost mobile ground-based hyperspectral system for breeding research to easily... H. Gerighausen, H. Lilienthal, E. Schnug

3. First Experiences with the European Remote Sensing Satellites Sentinel-1A/ -2A for Agricultural Research

The Copernicus program headed by the European Commission (EC) in partnership with the European Space Agency (ESA) will launch up to twelve satellites, the so called “Sentinels” for earth and environmental observations until 2020. Within this satellite fleet, the Sentinel-1 (microwave) and Sentinal-2 (optical) satellites deliver valuable information on agricultural crops. Due to their high temporal (5 to 6 days repeating time) and spatial (10 to 20 m) resolutions a continuous monitoring... H. Lilienthal, H. Gerighausen, E. Schnug

4. 25 Years Precision Agriculture in Germany - a Retrospective

It all started with the availability of Global Positioning Systems for civil services in 1988. In the same year variable rate applications of fertilizers were demonstrated in northern Germany and Denmark, which were globally the first of their kind and introduced a new era of agricultural production. The idea of Computer Aided Farming (CAF) was born. Only one year later the first yield maps were established. In 1992 at the Soil Specific Crop Management Workshop in Bloomington, Minnesota which... H. Lilienthal, E. Schnug, S. Haneklaus

5. Frameworks for Variable Rate Application of Manure

Worldwide, nitrogen (N) and phosphorus (P) losses from agriculture are main contributors to eutrophication of water bodies so that forceful agro-technical measures are required to reduce their diffuse discharge to the environment. With view to worldwide finite mineral rock phosphates efficient standards are required to close the agricultural P cycle. In intensive agricultural livestock production manure is often treated as a waste problem rather than an organic fertilizer and source of nutrients.... H. Lilienthal, S.H. Haneklaus, E. Schnug

6. Agricultural Remote Sensing Information for Farmers in Germany

The European Copernicus program delivers optical and radar satellite imagery at a high temporal frequency and at a ground resolution of 10m worldwide with an open data policy. Since July 2017 the satellite constellation of the Sentinel-1 and -2 satellites is fully operational, allowing e.g. coverage of Germany every 1-2 days by radar and every 2-3 days with optical sensors. This huge data source contains a variety of valuable input information for farmers to monitor the in-field variability and... H. Lilienthal, H. Gerighausen, E. Schnug