This thesis describes the definition, implementation, and in-orbit testing of an autonomous navigation unit based upon a GPS receiver for use on board a small satellite in low Earth orbit. It explains the motivation for the use of GPS to provide this function, and describes the practical application and integration of this technology into an existing microsatellite system. Until now, the technology for any satellite to track itself has not existed. Space agencies spend significant funds supporting a network of tracking stations around the world for orbit determination. With the recent realisation of the Global Positioning System and the availability of inexpensive receiver hardware, it has become a practical proposition to include a GPS receiver within the demanding constraints of a small satellite. A GPS receiver on-board a satellite can eliminate the necessity for ground-based tracking by providing an autonomous orbit determination capability. During the course of these studies, the requirements and constraints of a small satellite were identified by the author and matched with the capabilities of a GPS receiver. A GPS Navigation Unit was defined to provide autonomous services available oil demand for the satellite platform and payloads; position and velocity; time synchronisation; orbital elements; payload triggering and GPS data logging (for experimental and research purposes). The GPS Navigation Unit includes a processing facility capable of command and initialisation of the GPS receiver, and data processing to give orbit determination capability. When used on a microsatellite, the additional constraints of low power consumption necessitate the intermittent operation of the GPS receiver. To test the concept of the GPS Navigation Unit, a commercial Trimble TANS II GPS receiver system that had been modified for orbital velocities was integrated into the PoSAT-1 microsatellite which was launched into low Earth orbit in September 1993. A method for orbit determination was developed for use with the output from the GPS receiver, and the GPS Navigation Unit was implemented in software according to the constraints of the PoSAT-1 mission. The significant results from these studies include: The first use of a GPS receiver on a microsatellite, PoSAT-1. The implementation, test and validation of a GPS Navigation Unit in low Earth orbit. The first satellite mission to demonstrate the capability for autonomous orbit determination through the GPS Navigation Unit. The definition of the general-purpose interfaces between a small satellite and a satellite- borne GPS Navigation Unit.

No description available.

This thesis investigates new convex optimisation techniques for motion and pose estimation. Numerous computer vision problems can be formulated as optimisation problems. These optimisation problems are generally solved via linear techniques using the singular value decomposition or iterative methods under an L2 norm minimisation. Linear techniques have the advantage of offering a closed-form solution that is simple to implement. The quantity being minimised is, however, not geometrically or statistically meaningful. Conversely, L2 algorithms rely on iterative estimation, where a cost function is minimised using algorithms such as Levenberg-Marquardt, Gauss-Newton, gradient descent or conjugate gradient. The cost functions involved are geometrically interpretable and can statistically be optimal under an assumption of Gaussian noise. However, in addition to their sensitivity to initial conditions, these algorithms are often slow and bear a high probability of getting trapped in a local minimum or producing infeasible solutions, even for small noise levels. In light of the above, in this thesis we focus on developing new techniques for finding solutions via a convex optimisation framework that are globally optimal. Presently convex optimisation techniques in motion estimation have revealed enormous advantages. Indeed, convex optimisation ensures getting a global minimum, and the cost function is geometrically meaningful. Moreover, robust optimisation is a recent approach for optimisation under uncertain data. In recent years the need to cope with uncertain data has become especially acute, particularly where real-world applications are concerned. In such circumstances, robust optimisation aims to recover an optimal solution whose feasibility must be guaranteed for any realisation of the uncertain data. Although many researchers avoid uncertainty due to the added complexity in constructing a robust optimisation model and to lack of knowledge as to the nature of these uncertainties, and especially their propagation, in this thesis robust convex optimisation, while estimating the uncertainties at every step is investigated for the motion estimation problem. First, a solution using convex optimisation coupled to the recursive least squares (RLS) algorithm and the robust H filter is developed for motion estimation. In another solution, uncertainties and their propagation are incorporated in a robust L convex optimisation framework for monocular visual motion estimation. In this solution, robust least squares is combined with a second order cone program (SOCP). A technique to improve the accuracy and the robustness of the fundamental matrix is also investigated in this thesis. This technique uses the covariance intersection approach to fuse feature location uncertainties, which leads to more consistent motion estimates. Loop-closure detection is crucial in improving the robustness of navigation algorithms. In practice, after long navigation in an unknown environment, detecting that a vehicle is in a location it has previously visited gives the opportunity to increase the accuracy and consistency of the estimate. In this context, we have developed an efficient appearance-based method for visual loop-closure detection based on the combination of a Gaussian mixture model with the KD-tree data structure. Deploying this technique for loop-closure detection, a robust L convex posegraph optimisation solution for unmanned aerial vehicle (UAVs) monocular motion estimation is introduced as well. In the literature, most proposed solutions formulate the pose-graph optimisation as a least-squares problem by minimising a cost function using iterative methods. In this work, robust convex optimisation under the L norm is adopted, which efficiently corrects the UAV’s pose after loop-closure detection. To round out the work in this thesis, a system for cooperative monocular visual motion estimation with multiple aerial vehicles is proposed. The cooperative motion estimation employs state-of-the-art approaches for optimisation, individual motion estimation and registration. Three-view geometry algorithms in a convex optimisation framework are deployed on board the monocular vision system for each vehicle. In addition, vehicle-to-vehicle relative pose estimation is performed with a novel robust registration solution in a global optimisation framework. In parallel, and as a complementary solution for the relative pose, a robust non-linear H solution is designed as well to fuse measurements from the UAVs’ on-board inertial sensors with the visual estimates. The suggested contributions have been exhaustively evaluated over a number of real-image data experiments in the laboratory using monocular vision systems and range imaging devices. In this thesis, we propose several solutions towards the goal of robust visual motion estimation using convex optimisation. We show that the convex optimisation framework may be extended to include uncertainty information, to achieve robust and optimal solutions. We observed that convex optimisation is a practical and very appealing alternative to linear techniques and iterative methods.

This thesis presents the concept of dynamics-aware parabolic blends for an unmanned surface vehicle. Typically, trajectory generation techniques consider only kinematic constraints on a vehicle. By transforming the equations of motion for a surface vehicle to the body fixed frame, the dynamical constraints on the system are more intuitively integrated into the trajectory generator, when compared to working in the Earth fixed frame. Additionally, the accelerations, velocities, and positions generated by the parabolic blend algorithm are incorporated into the dynamic equations of motion for the vehicle to provide the feedforward control input of a two degree of freedom control law. The feedback control input of the two degree of freedom scheme is an integral sliding mode control law, which tracks the error between the vehicle state and the desired states generated by the novel parabolic blend technique. The approach is numerically validated through simulation, where the described control law demonstrates a 71.93% reduction in error when compared to a standard proportional-derivative control law subjected to the same desired trajectory. Furthermore, on water experiments were performed using both a proportional-derivative control law and an integral sliding mode control law. Both showed the ability to track the proposed parabolic blend approach. / Includes bibliography. / Dissertation (PhD)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

As the use of Unmanned Aerial Systems (UAS) becomes more common in both civilian/commercial and military applications, so too has the risk of injury to individuals and third parties on the ground. The purpose of this research is to further enhance methods currently in use for performing flight path risk assessment for UAS, as well as improve upon an existing software tool: Quantitative Approach and Departure Risk Assessment (QUADRA). The primary focus is upon the incorporation of building information to determine the protection offered to sheltered populations, reevaluate the probability of fatality models used in aircraft failures to more accurately determine the risk for smaller UAS systems, and to provide a metric for determining the number of individuals that are adversely affected by the noise of the autonomous system as it performs its mission. / Master of Science / Unmanned Aerial Vehicles are aircraft that are operated without a pilot onboard. More conventionally known as drones, these aircraft can be at increased risk to individuals on the ground as there is no pilot in the aircraft to course correct should the aircraft fail. Due to the potential for drones to fail and thus injure people on the ground, a method for determining the number of people injured or killed by an aircraft for its mission has been developed. These methods identify areas on the ground where the aircraft may land, as well as the potential number of fatalities for a given mission. To minimize the risk to people on the ground, the flight path of the drone is changed until a lower risk flight path is found. Similarly, the sound produced by these drones is used to determine the number of people who may hear the aircraft as it is flying overhead, as well as the number of people who may be annoyed or disturbed by this noise.

Operation of Unmanned Air Vehicles (UAVs) has increased significantly over the past few years. However, routine operation in non-segregated airspace remains a challenge, primarily due to nature of the environment and restrictions and challenges that accompany this. Currently, tight human control is envisaged as a means to achieve the oft quoted requirements of transparency , equivalence and safety. However, the problems of high cost of human operation, potential communication losses and operator remoteness remain as obstacles. One means of overcoming these obstacles is to devolve authority, from the ground controller to an on-board system able to understand its situation and make appropriate decisions when authorised. Such an on-board system is known as an Autonomous System. The nature of the autonomous system, how it should be designed, when and how authority should be transferred and in what context can they be allowed to control the vehicle are the general motivation for this study. To do this, the system must overcome the negative aspects of differentiators that exist between UASs and manned aircraft and introduce methods to achieve required increases in the levels of versatility, cost, safety and performance. The general thesis of this work is that the role and responsibility of an airborne autonomous system are sufficiently different from those of other conventionally controlled manned and unmanned systems to require a different architectural approach. Such a different architecture will also have additional requirements placed upon it in order to demonstrate acceptable levels of Transparency, Equivalence and Safety. The architecture for the system is developed from an analysis of the basic requirements and adapted from a consideration of other, suitable candidates for effective control of the vehicle under devolved authority. The best practices for airborne systems in general are identified and amalgamated with established principles and approaches of robotics and intelligent agents. From this, a decision architecture, capable of interacting with external human agencies such as the UAS Commander and Air Traffic Controllers, is proposed in detail. This architecture has been implemented and a number of further lessons can be drawn from this. In order to understand in detail the system safety requirements, an analysis of manned and unmanned aircraft accidents is made. Particular interest is given to the type of control moding of current unmanned aircraft in order to make a comparison, and prediction, with accidents likely to be caused by autonomously controlled vehicles. The effect of pilot remoteness on the accident rate is studied and a new classification of this remoteness is identified as a major contributor to accidents A preliminary Bayesian model for unmanned aircraft accidents is developed and results and predictions are made as an output of this model. From the accident analysis and modelling, strategies to improve UAS safety are identified. Detailed implementations within these strategies are analysed and a proposal for more advanced Human-Machine Interaction made. In particular, detailed analysis is given on exemplar scenarios that a UAS may encounter. These are: Sense and Avoid , Mission Management Failure, Take Off/Landing, and Lost Link procedures and Communications Failure. These analyses identify the nature of autonomous, as opposed to automatic, operation and clearly show the benefits to safety of autonomous air vehicle operation, with an identifiable decision architecture, and its relationship with the human controller. From the strategies and detailed analysis of the exemplar scenarios, proposals are made for the improvement of unmanned vehicle safety The incorporation of these proposals into the suggested decision architecture are accompanied by analysis of the levels of benefit that may be expected. These suggest that a level approaching that of conventional manned aircraft is achievable using currently available technologies but with substantial architectural design methodologies than currently fielded.

Operation of Unmanned Air Vehicles (UAVs) has increased significantly over the past few years. However, routine operation in non-segregated airspace remains a challenge, primarily due to nature of the environment and restrictions and challenges that accompany this. Currently, tight human control is envisaged as a means to achieve the oft quoted requirements of transparency , equivalence and safety. However, the problems of high cost of human operation, potential communication losses and operator remoteness remain as obstacles. One means of overcoming these obstacles is to devolve authority, from the ground controller to an on-board system able to understand its situation and make appropriate decisions when authorised. Such an on-board system is known as an Autonomous System. The nature of the autonomous system, how it should be designed, when and how authority should be transferred and in what context can they be allowed to control the vehicle are the general motivation for this study. To do this, the system must overcome the negative aspects of differentiators that exist between UASs and manned aircraft and introduce methods to achieve required increases in the levels of versatility, cost, safety and performance. The general thesis of this work is that the role and responsibility of an airborne autonomous system are sufficiently different from those of other conventionally controlled manned and unmanned systems to require a different architectural approach. Such a different architecture will also have additional requirements placed upon it in order to demonstrate acceptable levels of Transparency, Equivalence and Safety. The architecture for the system is developed from an analysis of the basic requirements and adapted from a consideration of other, suitable candidates for effective control of the vehicle under devolved authority. The best practices for airborne systems in general are identified and amalgamated with established principles and approaches of robotics and intelligent agents. From this, a decision architecture, capable of interacting with external human agencies such as the UAS Commander and Air Traffic Controllers, is proposed in detail. This architecture has been implemented and a number of further lessons can be drawn from this. In order to understand in detail the system safety requirements, an analysis of manned and unmanned aircraft accidents is made. Particular interest is given to the type of control moding of current unmanned aircraft in order to make a comparison, and prediction, with accidents likely to be caused by autonomously controlled vehicles. The effect of pilot remoteness on the accident rate is studied and a new classification of this remoteness is identified as a major contributor to accidents A preliminary Bayesian model for unmanned aircraft accidents is developed and results and predictions are made as an output of this model. From the accident analysis and modelling, strategies to improve UAS safety are identified. Detailed implementations within these strategies are analysed and a proposal for more advanced Human-Machine Interaction made. In particular, detailed analysis is given on exemplar scenarios that a UAS may encounter. These are: Sense and Avoid , Mission Management Failure, Take Off/Landing, and Lost Link procedures and Communications Failure. These analyses identify the nature of autonomous, as opposed to automatic, operation and clearly show the benefits to safety of autonomous air vehicle operation, with an identifiable decision architecture, and its relationship with the human controller. From the strategies and detailed analysis of the exemplar scenarios, proposals are made for the improvement of unmanned vehicle safety The incorporation of these proposals into the suggested decision architecture are accompanied by analysis of the levels of benefit that may be expected. These suggest that a level approaching that of conventional manned aircraft is achievable using currently available technologies but with substantial architectural design methodologies than currently fielded. / ©Cranfield University © BAE Systems

Thesis (PhD (Electrical and Electronic Engineering))--University of Stellenbosch, 2010. / Dissertation presented in fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering at Stellenbosch University. / ENGLISH ABSTRACT: Airworthiness certification of unmanned aircraft systems (UAS) is normally considered to be a regulatory function. In the absence of comprehensive UAS airworthiness regulations, the development of new and unique UAS, and their introduction into non-segregated airspace, remain major challenges for the UAS industry and regulators. Thus, in response, the objective of this research was to establish a framework and guidelines, within the scope of the typical regulatory regime, that can be used by the UAS engineering domain to ensure the safe and reliable functioning of a UAS, whether regulated or not. UAS airworthiness is currently mainly based on manned aircraft regulations, and the focus is on the unmanned aircraft and the 'airworthiness' of the remote control station. The typical UAS as a system, however, consists of more than just these elements and a broader approach to the 'airworthiness' of a UAS is required. This study investigated and introduces the concept of UAS operability, where the term 'operability' addresses the safe and reliable functioning of the UAS as a system, the airworthiness of its airborne sub-systems, and the safe and reliable functioning of its non-airborne subsystems and functional payloads. To ensure that the results of this study are aligned with typical aviation regulatory systems, a regulatory basis was defined within which UAS operability guidelines could be developed. Based on the operability concept, and in the scope of the regulatory basis, a UAS operability framework was developed for the UAS engineering domain. This framework is an index and reference source from which appropriate operability elements can be selected for a particular UAS. The scope of the framework is generic, rather than UAS-type or -class specific, and includes operability elements for the UAS as a system, for its airborne and non-airborne sub-systems, and for its payloads. The framework was validated by developing lower hierarchical levels for the framework and by populating each operability element of the framework with appropriate engineering guidance criteria. The guidance criteria were derived and/or developed from industry 'best practices' found in the literature, or were newly developed where no existing practices were found. The significance of this study is found in its establishing of a generic UAS operability framework that not only focuses on the airworthiness of the unmanned aircraft, but addresses the operability of the UAS as a system, as well as the operability of its airborne sub-systems, its non-airborne sub-systems and its payloads. In practice, the UAS operability framework can be used in the UAS engineering domain as an index and reference source to select relevant operability elements for a particular UAS. The guidance criteria for the selected elements can subsequently be used to develop the appropriate processes, procedures, requirements and specifications to achieve initial operability of the UAS, and to maintain its continued operability. Although the objective of the research was achieved, the UAS operability framework must still be applied and tested in real-life UAS projects and, where necessary, revised to eliminate shortcomings and to provide for new and novel developments in UAS engineering technologies. / AFRIKAANSE OPSOMMING: Die lugwaardigheidsertifisering van onbemande vliegtuigstelsels (OVS) word normaalweg beskou as 'n reguleringsfunksie. In die afwesigheid van omvattende OVS lugwaardigheidsregulasies bly die ontwikkeling van nuwe en unieke OVS, en die inbedryfstelling daarvan in onafgesonderde lugruim, besonderse uitdagings vir beide die OVS nywerheid en reguleerders. Die doelwit van hierdie navorsing was dus om riglyne binne die bestek van die tipiese reguleringsregime te vestig wat deur die OVS ingenieursdomein benut kan word om die veilige en betroubare funksionering van 'n OVS te verseker, of dit gereguleer word aldan nie. OVS lugwaardigheid word tans hoofsaaklik gebaseer op lugwaardigheidsvereistes vir bemande vliegtuie. Die fokus is dan ook meerendeels op die onbemande vliegtuig en die 'lugwaardigheid' van die afstandbeheerstasie. Die tipiese OVS bestaan egter uit meer sub-stelsels en 'n weier beskouing van die 'lugwaardigheid' van 'n OVS is nodig. Die konsep van OVS bedryfbaarheid is in hierdie studie ondersoek en voorgestel. 'Bedryfbaarheid' beteken in hierdie konteks die veilige en betroubare funksionering van die OVS as 'n stelsel, die lugwaardigheid van die lug sub-stelsels, die veilige en betroubare funksionering van die nie-lug sub-stelsels, asook die veilige en betroubare funksionering van funksionele loonvragte. Om te verseker dat die resultate van hierdie studie versoenbaar is met tipiese lugvaart reguleringstelsels, is 'n reguleringsbasis omskryf vir die ontwikkeling van OVS bedryfbaarheidsriglyne. Gebaseer op die bedryfbaarheidskonsep, en binne die riglyne van die reguleringsbasis, is 'n OVS bedryfbaarheidsraamwerk ontwikkel vir die OVS ingenieursdomein. Die raamwerk is 'n indeks en verwysingsbron waaruit gepaste bedryfbaarheids-elemente gekies kan word vir 'n bepaalde OVS. Die bestek van die raamwerk is generies en nie beperk tot spesifieke OVS tipes of klasse nie. Die raamwerk sluit bedryfbaarheidselemente in vir die OVS as stelsel, asook vir die lug en nie-lug sub-stelsels van die OVS, en vir die loonvragte van die OVS. Die raamwerk se geldigheid was bevestig deur die struktuur van die raamwerk tot laer vlakke uit te brei en gepaste ingenieursriglyne vir elke bedryfbaarheids-element in die raamwerk te ontwikkel. Die riglyne was gebaseer op 'beste praktyke' soos beskryf in die literatuur, of was van nuuts af ontwikkel waar geen bestaande praktyke gevind kon word nie. Die bydrae van hierdie studie is gesetel in die vestiging van 'n generiese OVS bedryfbaarheidsraamwerk wat nie net gemik is op die lugwaardigheid van die onbemande vliegtuig nie, maar wat die bedryfbaarheid in geheel van die OVS as stelsel aanspreek, asook die bedryfbaarheid van die OVS se lug sub-stelsels, nie-lug sub-stelsels en loonvragte. In die praktyk kan die raamwerk in die OVS ingenieursdomein gebruik word om gepaste bedryfbaarheids-elemente vir 'n OVS te kies. Daarna kan die bedryfbaarheidsriglyne gebruik word om gepaste prosesse, prosedures, vereistes en spesifikasies te ontwikkel om die OVS se aanvanklike en voortgesette bedryfbaarheid te bewerkstellig. Alhoewel die doelwit vir die navorsing bereik is, moet die OVS bedryfbaarheidsraamwerk nog op werklike OVS projekte getoets word. Waar nodig, moet die raamwerk dan hersien word om tekortkominge, asook nuwe en unieke ontwikkelinge in OVS ingenieurstegnologie, aan te spreek.

This thesis investigates new convex optimisation techniques for motion and pose estimation. Numerous computer vision problems can be formulated as optimisation problems. These optimisation problems are generally solved via linear techniques using the singular value decomposition or iterative methods under an L2 norm minimisation. Linear techniques have the advantage of offering a closed-form solution that is simple to implement. The quantity being minimised is, however, not geometrically or statistically meaningful. Conversely, L2 algorithms rely on iterative estimation, where a cost function is minimised using algorithms such as Levenberg-Marquardt, Gauss-Newton, gradient descent or conjugate gradient. The cost functions involved are geometrically interpretable and can statistically be optimal under an assumption of Gaussian noise. However, in addition to their sensitivity to initial conditions, these algorithms are often slow and bear a high probability of getting trapped in a local minimum or producing infeasible solutions, even for small noise levels. In light of the above, in this thesis we focus on developing new techniques for finding solutions via a convex optimisation framework that are globally optimal. Presently convex optimisation techniques in motion estimation have revealed enormous advantages. Indeed, convex optimisation ensures getting a global minimum, and the cost function is geometrically meaningful. Moreover, robust optimisation is a recent approach for optimisation under uncertain data. In recent years the need to cope with uncertain data has become especially acute, particularly where real-world applications are concerned. In such circumstances, robust optimisation aims to recover an optimal solution whose feasibility must be guaranteed for any realisation of the uncertain data. Although many researchers avoid uncertainty due to the added complexity in constructing a robust optimisation model and to lack of knowledge as to the nature of these uncertainties, and especially their propagation, in this thesis robust convex optimisation, while estimating the uncertainties at every step is investigated for the motion estimation problem. First, a solution using convex optimisation coupled to the recursive least squares (RLS) algorithm and the robust H filter is developed for motion estimation. In another solution, uncertainties and their propagation are incorporated in a robust L convex optimisation framework for monocular visual motion estimation. In this solution, robust least squares is combined with a second order cone program (SOCP). A technique to improve the accuracy and the robustness of the fundamental matrix is also investigated in this thesis. This technique uses the covariance intersection approach to fuse feature location uncertainties, which leads to more consistent motion estimates. Loop-closure detection is crucial in improving the robustness of navigation algorithms. In practice, after long navigation in an unknown environment, detecting that a vehicle is in a location it has previously visited gives the opportunity to increase the accuracy and consistency of the estimate. In this context, we have developed an efficient appearance-based method for visual loop-closure detection based on the combination of a Gaussian mixture model with the KD-tree data structure. Deploying this technique for loop-closure detection, a robust L convex posegraph optimisation solution for unmanned aerial vehicle (UAVs) monocular motion estimation is introduced as well. In the literature, most proposed solutions formulate the pose-graph optimisation as a least-squares problem by minimising a cost function using iterative methods. In this work, robust convex optimisation under the L norm is adopted, which efficiently corrects the UAV’s pose after loop-closure detection. To round out the work in this thesis, a system for cooperative monocular visual motion estimation with multiple aerial vehicles is proposed. The cooperative motion estimation employs state-of-the-art approaches for optimisation, individual motion estimation and registration. Three-view geometry algorithms in a convex optimisation framework are deployed on board the monocular vision system for each vehicle. In addition, vehicle-to-vehicle relative pose estimation is performed with a novel robust registration solution in a global optimisation framework. In parallel, and as a complementary solution for the relative pose, a robust non-linear H solution is designed as well to fuse measurements from the UAVs’ on-board inertial sensors with the visual estimates. The suggested contributions have been exhaustively evaluated over a number of real-image data experiments in the laboratory using monocular vision systems and range imaging devices. In this thesis, we propose several solutions towards the goal of robust visual motion estimation using convex optimisation. We show that the convex optimisation framework may be extended to include uncertainty information, to achieve robust and optimal solutions. We observed that convex optimisation is a practical and very appealing alternative to linear techniques and iterative methods.

Doctor of Philosophy / Department of Agronomy / Ignacio Ciampitti / The adoption of Remote Sensing (RS) in agriculture have been mainly utilized to inference about biological processes in a scalable manner over space and time. In this context, this work first explores two non-traditional approaches for rapid derivation of plant performance under field conditions. Both approaches focus on plant metrics extraction exploiting high spatial resolution from Unmanned Aerial Systems (UAS). Second, we investigate the spatial-temporal dynamics of corn (Zea mays L.) phenology and yield in the corn belt region utilizing high temporal resolution from satellite. To evaluate the impact of the adoption of RS for deriving plant/crop performance the following objectives were established: i) investigate the implementation of digital aerial photogrammetry to derive plant metrics (plant height and biomass) in corn; ii) implement and test a methodology for detecting and counting corn plants via very high spatial resolution imagery in the context of precision agriculture; iii) derive key phenological metrics of corn via high temporal resolution satellite imagery and identify links between the derived metrics and yield trends over the last 14 years for corn within the corn belt region. For the first objective, main findings indicate that digital aerial photogrammetry can be utilized to derive plant height and assist in plant biomass estimation. Results also suggest that plant biomass predictability significantly increases when integrating the aerial plant height estimate and ground stem diameter. For the second objective, the workflow implemented demostrates adequate performance to detect and count corn plants in the image. Its robustness highly dependends on the spatial resolution of the image, limitations and future research paths are further discussed. Lastly, for the third objective, outcomes evidenced that for a long-term perspective (14 years), an extended reproductive stage significantly correlates with high yield for corn. When considering a shorter-term period (last 4 years) mainly characterized by optimal growth conditions, early season green-up rate and late season senescence rate positively describe yield trend in the region. The significance of the variables changed according to the time-span considered. It is noticed that when optimal growth conditions are met, modern-hybrids can capitalize by increasing yield, due to primarily a faster (green-up) rate before flowering and on senescence rate better describes yield under these conditions. The entire research project investigates opportunities and needs for integrating remote sensing into the agronomic-based inference process.