A5005345622- Remote Sensing in Agriculture
- Soil Geostatistics and Mapping
- Leaf Properties and Growth Measurement
- Soil Carbon and Nitrogen Dynamics
- Spectroscopy and Chemometric Analyses
- Soil and Land Suitability Analysis
- Land Use and Ecosystem Services
- Remote Sensing and LiDAR Applications
- Geochemistry and Geologic Mapping
- Remote Sensing and Land Use
- Soil erosion and sediment transport
- Species Distribution and Climate Change
- Agricultural Economics and Policy
- Agricultural economics and policies
- Food Supply Chain Traceability
- Milk Quality and Mastitis in Dairy Cows
- Potato Plant Research
- Horticultural and Viticultural Research
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Geographic Information Systems Studies
- Landslides and related hazards
- Greenhouse Technology and Climate Control
- Pesticide and Herbicide Environmental Studies
- Land Use and Management
- 3D Modeling in Geospatial Applications
Julius Kühn-Institut
2016-2024
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
2007-2012
In the face of rapid global change it is imperative to preserve geodiversity for overall conservation biodiversity. Geodiversity important understanding complex biogeochemical and physical processes directly indirectly linked biodiversity on all scales ecosystem organization. Despite great importance geodiversity, there a lack suitable monitoring methods. Compared conventional in-situ techniques, remote sensing (RS) techniques provide pathway towards cost-effective, increasingly more...
Detailed and accurate statistics on crop productivity are key to inform decision-making related sustainable food production supply ensuring global security. However, annual high-resolution yield data provided by official agricultural generally lacking. Earth observation (EO) imagery, geodata meteorological soil conditions, as well advances in machine learning (ML) provide huge opportunities for model-based estimation terms of covering large spatial scales with unprecedented granularity. This...
Information on soil clay and organic carbon content a regional to local scale is vital for multitude of reasons such as conservation, precision agriculture, possibly also in the context global environmental change. The objective this study was evaluate potential multi-annual hyperspectral images acquired with HyMap sensor (450–2480 nm) during three flight campaigns 2004, 2005, 2008 prediction croplands by means partial least squares regression (PLSR). Supplementary, laboratory reflectance...
Spatiotemporally accurate estimates of crop traits are essential for both scientific modeling and practical decision making in sustainable agricultural management. Besides efficient concise methods to derive these traits, site- crop-specific reference data needed develop validate retrieval methods. To address this shortcoming, study first includes the establishment ’MISPEL’, a comprehensive spectral library (SpecLib) containing hyperspectral measurements six key ten widely grown crops....
Digital transformation is a key to turn public authorities into organisations that make decisions based on data-driven insights. The use of big geodata can enable tackle complex sustainability issues. However, the efficient management large amounts through implementing viable data infrastructures represents major challenge for authorities. In this article, we propose decentralized, cloud-integrated spatial infrastructure (SDI) meet needs mandated provide services earth observation (EO)...
Glyphosate is one of the most widely used non-selective systemic herbicides, but nowadays its application controversially discussed. Optical remote sensing techniques might provide a sufficient tool for monitoring glyphosate use. In order to investigate potential this technology, laboratory experiment was set-up using pots with rolled grass sods. Glyphosate-treated plants were compared drought-stressed and control plants. All frequently measured field spectrometer hyperspectral-imaging...
There is a growing need for an area-wide knowledge of SOC contents in agricultural soils at the field scale food security and monitoring long-term changes related to soil health climate change. In Germany, maps are mostly available with spatial resolution 250 m 1 km2. The nationwide availability both digital elevation models various resolutions multi-temporal satellite imagery enables derivation multi-scale terrain attributes (here: Landsat-based) reflectance composites (SRC) as explanatory...
Operational crop monitoring applications, including type mapping, condition monitoring, and yield estimation, would benefit from the ability to robustly detect map phenology measures related calendar management activities like emergence, stem elongation, harvest timing. However, this has proven be challenging due two main issues: first, lack of optimised approaches for accurate retrievals, second, cloud cover during growth period, which hampers use optical data. Hence, in current study, we...
Catch crops are intermediate sown between two main crop cycles. Their adoption into the cropping system has increased considerably in last years due to its numerous benefits, particular potential carbon fixation and preventing nitrogen leaching during winter. The growth period of catch Germany is often marked by dense cloud cover, which limits land surface monitoring through optical remote sensing. In such conditions, synthetic aperture radar (SAR) emerges as a viable option. Despite known...
Abstract Soils provide habitat, regulation and utilization functions. Therefore, Germany aims to reduce soil sealing 30 ha day $$^{-1}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow/> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> </mml:math> by 2030 eliminate it 2050. About 55 of are damaged (average 2018–2021), but detailed information on its quality is lacking. This study proposes a new approach using geo-information remote...
Leaf area index (LAI) and above ground biomass dry matter (DM) are key variables for crop growth monitoring yield estimation. High prediction accuracies of these parameters a vital prerequisite sophisticated projections. The aim the study was to examine predictive ability partial least squares regression (PLSR) LAI DM retrieval from hyperspectral (EnMAP), superspectral (Sentinel-2), multispectral (Landsat 8, RapidEye) remote sensing data based on field reflectance measurements. Data acquired...
There is a growing need for an area-wide knowledge of SOC contents in agricultural soils at field scale food security, monitoring long-term changes related to soil health and climate change. In Germany, large-scale maps are mostly available with spatial resolution 250 m 1 km2. The nationwide availability both digital elevation models various resolutions multi-temporal satellite imagery enables the derivation multi-scale terrain attributes Landsat-based reflectance composites (SRC) as...
Crop phenological phases have traditionally been observed from the ground, which is a labor-intensive and time-consuming activity that also lacks spatial variability due to sparse limited network of ground data, if any are available. In view this, remote sensing can provide low-cost avenue systematically monitor detect space. The most common approach for retrieving vegetation phenology remotely sensed time series dynamic threshold method. However, only few number studies attempted calibrate...