Proceedings

Find matching any: Reset
Werner, A
De Waele, T
Han, C
Holmes, G
Charvat, K
Add filter to result:
Authors
Stephens, P
Mackin, S
Holmes, G
Herold, L
Poelling, B
Wurbs, A
Werner, A
Charvat, K
Gnip, P
Charvat, K
Cepicky, J
Gnip, P
Charvat, K
Jezek, J
Musil, M
Krivanek, Z
Gnip, P
Holmes, G
Rojo, F
Roach, J
Coates, R
Upadhyaya, S
Delwiche, M
Han, C
Dhillon, R
Charvat, K
Reznik, T
Charvat jr., K
Lukas, V
Horakova, S
Kepka, M
Charvat, K
Reznik, T
Lukas, V
Charvat Jr., K
Horakova, S
Splichal, M
Kepka, M
Post, S
Jermy, M
Gaynor, P
Kabaliuk, N
Werner, A
Ekanayake, D.C
Owens, J
Werner, A
Holmes, A
Jafari, A
Karimi, F
Werner, A
Ghoreishi, S
Kargar, S
Charvat, K
Berzins, R
Bergheim, R
Zadrazil, F
Macura, J
Langovskis, D
Snevajs, H
Kubickova, H
Horakova, S
Charvat Jr., K
Charvat, K
Kepka, M
Berzins, R
Zadrazil, F
Langovskis, D
Musil, M
De Waele, T
Peralta, D
Shahid, A
De Poorter, E
Werner, A
Holmes, A
Topics
Remote Sensing Applications in Precision Agriculture
Profitability, Sustainability, and Adoption
Optimizing Farm-level use of Spatial Technologies
Sensor Application in Managing In-season Crop Variability
Remote Sensing Applications in Precision Agriculture
Proximal Sensing in Precision Agriculture
Standards & Data Stewardship
Precision Agriculture and Climate Change
Precision Crop Protection
On Farm Experimentation with Site-Specific Technologies
Precision Dairy and Livestock Management
Geospatial Data
Drainage Optimization and Variable Rate Irrigation
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2025
Home » Authors » Results

Authors

Filter results16 paper(s) found.

1. Exploiting the Dmc Satellite Constellation for Applications in Precision Agriculture

This paper presents the unique capabilities of the DMC constellation of optical sensors, and examples of how a number of organisations around the world are exploiting this powerful data source for applications in precision farming. The DMC consists of five satellites built in the UK by Surrey Satellite Technology Ltd, each carrying a wide swath (650km) optical sensor. It is an international programme of satellite ownership and groundstations, with joint campaigns being coordinated centrally... P. Stephens, S. Mackin, G. Holmes

2. Typology Of Farms And Regions In EU States Assessing The Impacts Of Precision Farming-technologies

A typology is developed describing the typical farms and the agricultural regions in Europe which presumably would apply Precision Farming technologies (PFT) and how. The typology focuses on the potential agronomic (cropping practices) benefits of PFT in crop production. Precision Farming covers a wide range of technologies for different sectors in agriculture. They differ in techniques, equipment and procedures and form core elements of information oriented production of various crops .... L. Herold, B. Poelling, A. Wurbs, A. Werner

3. Vision Of Farm Of Tomorrow

... K. Charvat, P. Gnip

4. New Geospatial Technologies For Precision Farming

... K. Charvat, J. Cepicky, P. Gnip

5. Vlite Node – New Sensor Technology For Precision Farming

... K. Charvat, J. Jezek, M. Musil, Z. Krivanek, P. Gnip

6. Multitemporal Satellite Imaging To Support Near Real-Time Precision Farming

This paper presents a 2014 update on the DMC constellation of optical satellite sensors and how they are exploited for various types of agricultural monitoring. Thousands of farmers around the world are exploiting this powerful data source for the management of crops, enabled by specialist service providers which convert the imagery into meaningful biophysical measurements and spatially variable nitrogen/irrigation recommendations. The paper also looks ahead to future DMC... G. Holmes

7. Development And Evaluation Of A Leaf Monitoring System For Continuous Measurement Of Plant Water Status In Almond And Walnut Crops

Abstract: Leaf temperature measurements using handheld infrared thermometers have been used to predict plant water stress by calculating crop water stress index (CWSI). However, for CWSI calculations it is recommended to measure canopy temperature of trees under saturated, stressed and current conditions simultaneously, which is not very practical while using handheld units. An inexpensive, easy to use sensing system was developed to predict plant water status for tree crops by measuring... F. Rojo, J. Roach, R. Coates, S. Upadhyaya, M. Delwiche, C. Han, R. Dhillon

8. FOODIE Data Model for Precision Agriculture

The agriculture sector is a unique sector due to its strategic importance for both citizens (consumers) and economy (regional and global), which ideally should make the whole sector a network of interacting organizations. The FOODIE project aims at building an open and interoperable agricultural specialized platform hub on the cloud for the management of spatial and non-spatial data relevant for farming production. The FOODIE service platform deals with including their thematic, spatial, and temporal... K. Charvat, T. Reznik, K. Charvat jr., V. Lukas, S. Horakova, M. Kepka

9. Quo Vadis Precision Farming

The agriculture sector is a unique sector due to its strategic importance for both citizens and economy which, ideally, should make the whole sector a network of interacting organizations. There is an increasing tension, the like of which is not experienced in any other sector, between the requirements to assure full safety and keep costs under control, but also assure the long-term strategic interests of Europe and worldwide. In that sense, agricultural production influences, and is influenced... K. Charvat, T. Reznik, V. Lukas, K. Charvat jr., S. Horakova, M. Splichal, M. Kepka

10. Real-Time Control of Spray Drop Application

Electrostatic application of spray drops provides unique opportunities to precisely control the application of pesticides due to the additional electrostatic force on the spray drops, in addition to the normally seen forces of aerodynamic drag, gravity, and inertia. In this work, we develop a computational model to predict the spray drop trajectories. The model is validated through experiments with high speed photography of spray drop trajectories, and quantification of which trajectories lead... S. Post, M. Jermy, P. Gaynor, N. Kabaliuk, A. Werner

11. Delineation of 'Management Classes' Within Non-Irrigated Maize Fields Using Readily Available Reflectance Data and Their Correspondence to Spatial Yield Variation

Maize is grown predominantly for silage or gain in North Island, New Zealand. Precision agriculture allows management of spatially variable paddocks by variably applying crop inputs tailored to distinctive potential-yield limiting areas of the paddock, known as management zones. However, uptake of precision agriculture among in New Zealand maize growers is slow and limited, largely due to lack of data, technical expertise and evidence of financial benefits. Reflectance data of satellite and areal... D.C. Ekanayake, J. Owens, A. Werner, A. Holmes

12. Feature Extraction from Radial Descriptor Lines for Body Condition Scoring of Cows

Body condition score (BCS) is considered as one of the most important indices for managing dairy cows, which is used to evaluate fat cover and changes in body condition. Dairy farmers should be aware of their cows BCS to be able to identify the patient cows on time and manage diets when needed. In this study, we have introduced a new index which uses Radial Descriptor Lines (RDL) for BC scoring. Based on the fact that the fatter the cow the smoother the back surface, we hypothesised that the changes... A. Jafari, F. Karimi, A. Werner, S. Ghoreishi, S. Kargar

13. Map Whiteboard As Collaboration Tool for Smart Farming Advisory Services

Precision agriculture, a branch of smart farming, holds great promise for modernization of European agriculture both in terms of environmental sustainability and economic outlook.  The vast data archives made available through Copernicus and related infrastructures, combined with a low entry threshold into the domain of AI-technologies has made it possible, if not outright easy, to make meaningful predictions that divides  individual agricultural fields into zones where variable rates... K. Charvat, R. Berzins, R. Bergheim, F. Zadrazil, J. Macura, D. Langovskis, H. Snevajs, H. Kubickova, S. Horakova, K. Charvat jr.

14. SmartAgriHubs FIE20 - Groundwater and Meteo Sensors and Earth Observation for Precision Agriculture

The solution developed under the SmartAgriHubs project in the scope of the Flagship Innovation Experiment FIE20 Groundwater and meteo sensors is an expert system to support farmers in decision-making process and planning process of field interventions. This FIE20 solution integrates various data sources and different analytical processes in a complete system and provides users an easy-to-use web map application as a common user interface. The FIE20 system integrates components developed during... K. Charvat, M. Kepka, R. Berzins, F. Zadrazil, D. Langovskis, M. Musil

15. Supervised Feature Selection and Clustering for Equine Activity Recognition

In this paper we introduce a novel supervised algorithm for equine activity recognition based on accelerometer data. By combining an approach of calculating a wide variety of time-series features with a supervised feature significance test we can obtain the best suited features using just 5 labeled samples per class and without requiring any expert domain knowledge. By using a simple cluster assignment algorithm with these obtained features, we get a classification algorithm that achieves a mean... T. De waele, D. Peralta, A. Shahid, E. De poorter

16. Measure, Model, Manage: the Unfinished Revolution in Agriculture

Over the last 40 years, the paradigm of Measure, Model, Manage has promised an agricultural revolution through data-informed precision management. This shift remains largely incomplete, lagging concurrent innovations in genetics and pesticides. Significant barriers persist in achieving breakthrough innovations for crop data collection and the development of data analysis/decision-making systems. These hurdles include a decades-old "Sensor Crisis" (a lack of appropriate tools),... A. Werner, A. Holmes