A5065166470- Remote Sensing in Agriculture
- Remote Sensing and LiDAR Applications
- Remote Sensing and Land Use
- Land Use and Ecosystem Services
- Smart Agriculture and AI
- Leaf Properties and Growth Measurement
- Soil Geostatistics and Mapping
- Spectroscopy and Chemometric Analyses
- Plant Water Relations and Carbon Dynamics
- Crop Yield and Soil Fertility
- Environmental and Agricultural Sciences
- Remote-Sensing Image Classification
- Rice Cultivation and Yield Improvement
- Species Distribution and Climate Change
- Regional Economic and Spatial Analysis
- Calibration and Measurement Techniques
- Plant nutrient uptake and metabolism
- Plant Surface Properties and Treatments
- Data Management and Algorithms
- Infrared Target Detection Methodologies
- Geographic Information Systems Studies
- 3D Modeling in Geospatial Applications
- Advanced Measurement and Detection Methods
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Soil Moisture and Remote Sensing
Yara (Germany)
2014-2022
Yara (Norway)
2019
University of Cologne
2006-2015
China Agricultural University
2010-2015
Rice farming in Northeast China is crucially important for China’s food security and sustainable development. A key challenge how to optimize nitrogen (N) management ensure high yield production while improving N use efficiency protecting the environment. Handheld chlorophyll meter (CM) active crop canopy sensors have been used improve rice this region. However, these technologies are still time consuming large-scale applications. Satellite remote sensing provides a promising technology...
Monitoring grassland biomass throughout the growing season is of key importance in sustainable, site-specific management decisions. Precision agriculture applications can support these However, precision relies on timely and accurate information plant parameters with a high spatial temporal resolution. The use structural spectral features derived from unmanned aerial vehicle (UAV)-based image data low-cost sensors promising nondestructive approach to assess traits such as above-ground or...
For in-season site-specific nitrogen (N) management of rice to be successful, it is crucially important diagnose N status efficiently across large areas within a short time frame. In recent studies, the FORMOSAT-2 satellite images with traditional blue (B), green (G), red (R), and near-infrared (NIR) wavebands have been used estimate due its high spatial resolution, daily revisit capability, relatively lower cost. This study aimed evaluate potential improvements RapidEye WorldView-2 data...
Abstract. Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications beneficial sustainable, site-specific treatment, grazing and forecasting mitigate potential negative impacts. To these decisions, timely accurate information needed plant parameters (e.g. yield) with a high spatial...
Timely nondestructive estimation of crop nitrogen (N) status is crucial for in-season site-specific N management. Active canopy sensors are the promising tools to obtain needed information without being affected by environmental light conditions. The objective this study was evaluate potential GreenSeeker active sensor estimate rice (Oryza sativa L.) status. Nine rate experiments were conducted from 2008 2012 in Jiansanjiang, Heilongjiang Province Northeast China. results indicated that...
Abstract. Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed geodata in last years (Hardin & Jensen 2011). Various applications numerous fields research like archaeology (Hendrickx et al., 2011), forestry or geomorphology evolved (Martinsanz, 2012). This contribution deals with generation multi-temporal crop surface models (CSMs) very high resolution by means low-cost equipment. The concept CSMs using Terrestrial Laserscanning (TLS) has...
Precise and timely information on biomass yield nitrogen uptake in intensively managed grasslands are essential for sustainable management decisions. Imaging sensors mounted unmanned aerial vehicles (UAVs) along with photogrammetric structure-from-motion processing can provide data crop traits rapidly non-destructively a high spatial resolution. The aim of this multi-temporal field study is to estimate aboveground dry matter (DMY), concentration (N%) (Nup) temperate from UAV-based image...
Abstract Remote sensing systems based on unmanned aerial vehicles (UAVs) are well suited for airborne monitoring of small to medium-sized farmland in agricultural applications. An imaging system is often used the form a multispectral multi-camera derive well-established vegetation indices (VIs) efficiently. This study investigates potential such with novel approach extend spectral sensitivity from visible-to-near-infrared (VNIR) short-wave infrared (SWIR) (400–1700 nm) estimating forage mass...
Abstract. The development of UAV-based sensing systems for agronomic applications serves the improvement crop management. latter is in focus precision agriculture which intends to optimize yield, fertilizer input, and protection. Besides, some cropping vehicle-based devices are less suitable because fields cannot be entered from certain growing stages onwards. This true rice, maize, sorghum, many more crops. Consequently, approaches fill a niche very high resolution data acquisition on field...
The development of UAV-based sensing systems for agronomic applications serves the improvement crop management. latter is in focus precision agriculture which intends to optimize yield, fertilizer input, and protection. Besides, some cropping vehicle-based devices are less suitable because fields cannot be entered from certain growing stages onwards. This true rice, maize, sorghum, many more crops. Consequently, approaches fill a niche very high resolution data acquisition on field scale...