Use of remote sensing techniques to analyse lodging level in cereal crops

openNowadays, there is high attention to sustainability in all areas of human activities. But what does sustainability mean? As the World Commission on Environment and Development says, sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs”. Definitively, it is possible to affirm that sustainability is based on three main pillars: the social one, the economic one and the environment. If all those pillars will be met, sustainability can be reached. What about agriculture? There are several definitions for Sustainable Agriculture, one says that Sustainable Agriculture is the efficient production of safe, high quality agricultural products, in a way that protects and improves the natural environment, the social and economic conditions of farmers, their employees and local communities, and safeguards the health and welfare of all farmed species (Sustainable Agriculture Initiative Platform). The aim of this dissertation is to illustrate how Precision Agriculture can help not only farmers, but also agriculture business operators to process the right decision in order to satisfy sustainable principles. New technologies are useful to manage resources employed in agricultural processes such as soil, water, fertilizers or pesticide, but also to reduce wastage maximizing yields and, consequently farm profit. In particular, the dissertation is going to illustrate how monitoring technologies implementation is useful to manage soil, crop and weather with proximal and remote sensing. Those collected data can be processed, corrected and interpreted by operators in order to generate Decision Support System which is useful to improve company’s decision-making capability. The study focuses on one of the main extensive crops, barley, in particular on its lodging. Different barley varieties were tested on 195 plots located in Idice, province of Bologna, North-East Italy to asses which one can better resist to lodge and to demonstrate how Unmanned Aerial Vehicle can be useful to monitor crop evolution. In fact, UAV was employed to collect data and, to validate them, crop smart scouting was necessary. After data collection and correction, a Digital Elevation Model has been created in order to evaluate three classes: laid crop, partial laid crop, no laid crop. The study evidences how remote sensing, in particular UAV’s, can help to process data otherwise hard to collect, giving useful information to farmers and business operators to make the right decision with high accuracy in short time.Nowadays, there is high attention to sustainability in all areas of human activities. But what does sustainability mean? As the World Commission on Environment and Development says, sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs”. Definitively, it is possible to affirm that sustainability is based on three main pillars: the social one, the economic one and the environment. If all those pillars will be met, sustainability can be reached. What about agriculture? There are several definitions for Sustainable Agriculture, one says that Sustainable Agriculture is the efficient production of safe, high quality agricultural products, in a way that protects and improves the natural environment, the social and economic conditions of farmers, their employees and local communities, and safeguards the health and welfare of all farmed species (Sustainable Agriculture Initiative Platform). The aim of this dissertation is to illustrate how Precision Agriculture can help not only farmers, but also agriculture business operators to process the right decision in order to satisfy sustainable principles. New technologies are useful to manage resources employed in agricultural processes such as soil, water, fertilizers or pesticide, but also to reduce wastage maximizing yields and, consequently farm profit. In particular, the dissertation is going to illustrate how monitoring technologies implementation is useful to manage soil, crop and weather with proximal and remote sensing. Those collected data can be processed, corrected and interpreted by operators in order to generate Decision Support System which is useful to improve company’s decision-making capability. The study focuses on one of the main extensive crops, barley, in particular on its lodging. Different barley varieties were tested on 195 plots located in Idice, province of Bologna, North-East Italy to asses which one can better resist to lodge and to demonstrate how Unmanned Aerial Vehicle can be useful to monitor crop evolution. In fact, UAV was employed to collect data and, to validate them, crop smart scouting was necessary. After data collection and correction, a Digital Elevation Model has been created in order to evaluate three classes: laid crop, partial laid crop, no laid crop. The study evidences how remote sensing, in particular UAV’s, can help to process data otherwise hard to collect, giving useful information to farmers and business operators to make the right decision with high accuracy in short time

Robotic equipment carrying RN detectors: requirements and capabilities for testing

77 pags., 32 figs., 5 tabs.-- ERNCIP Radiological and Nuclear Threats to Critical Infrastructure Thematic Group . -- This publication is a Technical report by the Joint Research Centre (JRC) . -- JRC128728 . -- EUR 31044 ENThe research leading to these results has received funding from the European Union as part of the European Reference Network for Critical Infrastructure Protection (ERNCIP) projec

New strategies for row-crop management based on cost-effective remote sensors

Agricultural technology can be an excellent antidote to resource scarcity. Its growth has led to the extensive study of spatial and temporal in-field variability. The challenge of accurate management has been addressed in recent years through the use of accurate high-cost measurement instruments by researchers. However, low rates of technological adoption by farmers motivate the development of alternative technologies based on affordable sensors, in order to improve the sustainability of agricultural biosystems. This doctoral thesis has as main objective the development and evaluation of systems based on affordable sensors, in order to address two of the main aspects affecting the producers: the need of an accurate plant water status characterization to perform a proper irrigation management and the precise weed control. To address the first objective, two data acquisition methodologies based on aerial platforms have been developed, seeking to compare the use of infrared thermometry and thermal imaging to determine the water status of two most relevant row-crops in the region, sugar beet and super high-density olive orchards. From the data obtained, the use of an airborne low-cost infrared sensor to determine the canopy temperature has been validated. Also the reliability of sugar beet canopy temperature as an indicator its of water status has been confirmed. The empirical development of the Crop Water Stress Index (CWSI) has also been carried out from aerial thermal imaging combined with infrared temperature sensors and ground measurements of factors such as water potential or stomatal conductance, validating its usefulness as an indicator of water status in super high-density olive orchards. To contribute to the development of precise weed control systems, a system for detecting tomato plants and measuring the space between them has been developed, aiming to perform intra-row treatments in a localized and precise way. To this end, low cost optical sensors have been used and compared with a commercial LiDAR laser scanner. Correct detection results close to 95% show that the implementation of these sensors can lead to promising advances in the automation of weed control. The micro-level field data collected from the evaluated affordable sensors can help farmers to target operations precisely before plant stress sets in or weeds infestation occurs, paving the path to increase the adoption of Precision Agriculture techniques

Multi-Robot Coordination and Scheduling for Deactivation & Decommissioning

Large quantities of high-level radioactive waste were generated during WWII. This waste is being stored in facilities such as double-shell tanks in Washington, and the Waste Isolation Pilot Plant in New Mexico. Due to the dangerous nature of radioactive waste, these facilities must undergo periodic inspections to ensure that leaks are detected quickly. In this work, we provide a set of methodologies to aid in the monitoring and inspection of these hazardous facilities. This allows inspection of dangerous regions without a human operator, and for the inspection of locations where a person would not be physically able to enter. First, we describe a robot equipped with sensors which uses a modified A* path-planning algorithm to navigate in a complex environment with a tether constraint. This is then augmented with an adaptive informative path planning approach that uses the assimilated sensor data within a Gaussian Process distribution model. The model\u27s predictive outputs are used to adaptively plan the robot\u27s path, to quickly map and localize areas from an unknown field of interest. The work was validated in extensive simulation testing and early hardware tests. Next, we focused on how to assign tasks to a heterogeneous set of robots. Task assignment is done in a manner which allows for task-robot dependencies, prioritization of tasks, collision checking, and more realistic travel estimates among other improvements from the state-of-the-art. Simulation testing of this work shows an increase in the number of tasks which are completed ahead of a deadline. Finally, we consider the case where robots are not able to complete planned tasks fully autonomously and require operator assistance during parts of their planned trajectory. We present a sampling-based methodology for allocating operator attention across multiple robots, or across different parts of a more sophisticated robot. This allows few operators to oversee large numbers of robots, allowing for a more scalable robotic infrastructure. This work was tested in simulation for both multi-robot deployment, and high degree-of-freedom robots, and was also tested in multi-robot hardware deployments. The work here can allow robots to carry out complex tasks, autonomously or with operator assistance. Altogether, these three components provide a comprehensive approach towards robotic deployment within the deactivation and decommissioning tasks faced by the Department of Energy

Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments

Nuclear facilities have a regulatory requirement to measure radiation levels within Post Operational Cleanout (POCO) around nuclear facilities each year, resulting in a trend towards robotic deployments to gain an improved understanding during nuclear decommissioning phases. The UK Nuclear Decommissioning Authority supports the view that human-in-the-loop robotic deployments are a solution to improve procedures and reduce risks within radiation haracterisation of nuclear sites. We present a novel implementation of a Cyber-Physical System (CPS) deployed in an analogue nuclear environment, comprised of a multi-robot team coordinated by a human-in-the-loop operator through a digital twin interface. The development of the CPS created efficient partnerships across systems including robots, digital systems and human. This was presented as a multi-staged mission within an inspection scenario for the heterogeneous Symbiotic Multi-Robot Fleet (SMuRF). Symbiotic interactions were achieved across the SMuRF where robots utilised automated collaborative governance to work together where a single robot would face challenges in full characterisation of radiation. Key contributions include the demonstration of symbiotic autonomy and query-based learning of an autonomous mission supporting scalable autonomy and autonomy as a service. The coordination of the CPS was a success and displayed further challenges and improvements related to future multi-robot fleets

Research Naval Postgraduate School, v.13, no.1, February 2003

NPS Research is published by the Research and Sponsored Programs, Office of the Vice President and Dean of Research, in accordance with NAVSOP-35. Views and opinions expressed are not necessarily those of the Department of the Navy.Approved for public release; distribution is unlimited