Proceedings :: International Society of Precision Agriculture

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Dreyer, J

Scheithauer, H

Wang, Y

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Authors

Gebbers, R

Dworak, V

Mahns, B

Weltzien, C

Büchele, D

Gornushkin, I

Mailwald, M

Ostermann, M

Rühlmann, M

Schmid, T

Maiwald, M

Sumpf, B

Rühlmann, J

Bourouah, M

Scheithauer, H

Heil, K

Heggemann, T

Leenen, M

Pätzold, S

Welp, G

Chudy, T

Mizgirev, A

Wagner, P

Beitz, T

Kumke, M

Riebe, D

Kersebaum, C

Wallor, E

Ameglio, L

Darrozes, J

Dreyer, J

Wang, Y

Balmos, A

Krogmeier, J

Buckmaster, D

Krogmeier, J

Buckmaster, D

Ault, A

Wang, Y

Zhang, Y

Layton, A

Noel, S

Balmos, A

Topics

Precision Nutrient Management

Proximal and Remote Sensing of Soil and Crop (including Phenotyping)

Big Data, Data Mining and Deep Learning

Profitability and Success Stories in Precision Agriculture

Type

Poster

Oral

Year

2016

2018

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Filter results4 paper(s) found.
1. Integrated Approach to Site-specific Soil Fertility Management In precision agriculture the lack of affordable methods for mapping relevant soil attributes is a fundamental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil fertility... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor Download paper
2. Farm Soil Moisture Mapping Using Reflected GNSS SNR Data Onboard Low Level Flying Aircraft Soil moisture/water content monitoring (spatial and temporal) is a critical component of farm management decision primarily for crop/plant growth and yield improvement, but also for optimization of practice such as tillage and field treatments. Satellite humidity probes do not deliver the relevant resolution for farming purposes. Ground moisture probes only provide punctual measurements and do not reflect the true spatial variability of soil moisture. Previous studies have demonstrated... L. Ameglio, J. Darrozes, J. Dreyer Download paper
3. Data-Driven Agricultural Machinery Activity Anomaly Detection and Classification In modern agriculture, machinery has become the one of the necessities in providing safe, effective and economical farming operations and logistics. In a typical farming operation, different machines perform different tasks, and sometimes are used together for collaborative work. In such cases, different machines are associated with representative activity patterns, for example, in a harvest scenario, combines move through a field following regular swaths while grain carts follow irregular paths... Y. Wang, A. Balmos, J. Krogmeier, D. Buckmaster Download paper
4. Use Cases for Real Time Data in Agriculture Agricultural data of many types (yield, weather, soil moisture, field operations, topography, etc.) comes in varied geospatial aggregation levels and time increments. For much of this data, consumption and utilization is not time sensitive. For other data elements, time is of the essence. We hypothesize that better quality data (for those later analyses) will also follow from real-time presentation and application of data for it is during the time that data is being collected that errors can be... J. Krogmeier, D. Buckmaster, A. Ault, Y. Wang, Y. Zhang, A. Layton, S. Noel, A. Balmos Download paper

Filter results4 paper(s) found.

1. Integrated Approach to Site-specific Soil Fertility Management

In precision agriculture the lack of affordable methods for mapping relevant soil attributes is a fundamental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil fertility... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor

Download paper

2. Farm Soil Moisture Mapping Using Reflected GNSS SNR Data Onboard Low Level Flying Aircraft

Soil moisture/water content monitoring (spatial and temporal) is a critical component of farm management decision primarily for crop/plant growth and yield improvement, but also for optimization of practice such as tillage and field treatments. Satellite humidity probes do not deliver the relevant resolution for farming purposes. Ground moisture probes only provide punctual measurements and do not reflect the true spatial variability of soil moisture. Previous studies have demonstrated... L. Ameglio, J. Darrozes, J. Dreyer

Download paper

3. Data-Driven Agricultural Machinery Activity Anomaly Detection and Classification

In modern agriculture, machinery has become the one of the necessities in providing safe, effective and economical farming operations and logistics. In a typical farming operation, different machines perform different tasks, and sometimes are used together for collaborative work. In such cases, different machines are associated with representative activity patterns, for example, in a harvest scenario, combines move through a field following regular swaths while grain carts follow irregular paths... Y. Wang, A. Balmos, J. Krogmeier, D. Buckmaster

Download paper

4. Use Cases for Real Time Data in Agriculture

Agricultural data of many types (yield, weather, soil moisture, field operations, topography, etc.) comes in varied geospatial aggregation levels and time increments. For much of this data, consumption and utilization is not time sensitive. For other data elements, time is of the essence. We hypothesize that better quality data (for those later analyses) will also follow from real-time presentation and application of data for it is during the time that data is being collected that errors can be... J. Krogmeier, D. Buckmaster, A. Ault, Y. Wang, Y. Zhang, A. Layton, S. Noel, A. Balmos

Download paper