Automatic Identification and Monitoring of Plant Diseases Using Unmanned Aerial Vehicles: A Review

Disease diagnosis is one of the major tasks for increasing food production in agriculture. Although precision agriculture (PA) takes less time and provides a more precise application of agricultural activities, the detection of disease using an Unmanned Aerial System (UAS) is a challenging task. Several Unmanned Aerial Vehicles (UAVs) and sensors have been used for this purpose. The UAVs’ platforms and their peripherals have their own limitations in accurately diagnosing plant diseases. Several types of image processing software are available for vignetting and orthorectification. The training and validation of datasets are important characteristics of data analysis. Currently, different algorithms and architectures of machine learning models are used to classify and detect plant diseases. These models help in image segmentation and feature extractions to interpret results. Researchers also use the values of vegetative indices, such as Normalized Difference Vegetative Index (NDVI), Crop Water Stress Index (CWSI), etc., acquired from different multispectral and hyperspectral sensors to fit into the statistical models to deliver results. There are still various drifts in the automatic detection of plant diseases as imaging sensors are limited by their own spectral bandwidth, resolution, background noise of the image, etc. The future of crop health monitoring using UAVs should include a gimble consisting of multiple sensors, large datasets for training and validation, the development of site-specific irradiance systems, and so on. This review briefly highlights the advantages of automatic detection of plant diseases to the growers

AggieAir: Towards Low-cost Cooperative Multispectral Remote Sensing Using Small Unmanned Aircraft Systems

Non

An investigation of solar panel thermal images collected from an unmanned aerial vehicle

As the population of the world continues to increase, so does energy consumption. At the same time, available fossil fuels continue to be depleted. Knowing these two facts, there is a need to find additional sources of energy. Photovoltaic panels (solar panels) are front and center of the renewable energy available options. Exploring the practical use of infrared thermal imaging for data collection and maintenance of photovoltaic panels is the main objective of this study. In this research, three unmanned aerial vehicle (UAV) flights were completed to obtain thermal imaging of the Cedar Falls Utilities Solar Field with various dates and weather. The images obtained by the UAV show varying temperatures of solar panels. The comparison between the power output of the solar garden and the temperature of the panels themselves, did not show any significant correlation. The research opened up more questions and shows the need for more research on the topic of how to utilize drone and thermography technology to assist utility companies

Autonomous real-time infrared detection of sub-surface vessels for unmanned aircraft systems

The threat of small self-propelled semi-submersible vessels cannot be understated; payloads from drugs to weapons of mass destruction could be housed in these small, inconspicuous vessels. With a current apprehension rate of approximately 10%, a method resulting in increased interdiction of this illegal traffic is required for national security both in the ports along the coastlines of Canada, as well as the rest of North America. A smart, autonomous payload containing an infrared imaging device, designed for use in small unmanned aircraft systems for the specific mission of detecting self-propelled semi-submersibles over the vast ocean coastline will address the current security needs. Thermal imagery of the disturbed colder water layers, driven to the surface by the vessel will allow for the detection of this traffic using long wave infrared technology. Infrared signatures of ship wakes are highly variable in both persistence and temperature contrast as compared to the surrounding surface water, thus infrared imaging devices with a high resolution, a high responsivity, and a very low minimum resolvable temperature will be required to provide high quality imagery for airborne detection of the thermal wake. A theoretical understanding of the physics associated with the energy collected by the infrared sensor and the resulting infrared images is provided. Explanation of the factors affecting the resulting image with respect to the camera properties are detailed. A variety of examples of airborne thermal images are presented, with detailed explanations of the imaged scenes based on theory and sensor characteristics provided in the previous sections. Infrared images taken over the Atlantic and Pacific oceans from manned and unmanned aircraft platforms are presented. Temperature measurements taken using Vemco Minilog II temperature loggers confirmed the thermal stratification of the upper 5 meters of the water. Thermal scarring due to upwelled colder water to the surface was noted during the day time under normal conditions, with temperature differences found to be consistent with the measured temperature profile. A custom gimbal system, with corresponding ground control station for real-time, visual feedback is presented. An algorithm for the detection of submerged vessel ship wakes using a LWIR camera, specifically for a small unmanned aircraft, with limited power, space, and computing power is developed. A time sequential processing method is presented to reduce the required computing, while allowing high frame rate, real-time operation. Moreover, a windowed triple-vote method is continually applied to ensure that the detection mode is correctly set by the algorithm, while ignoring unexpected targets in the image. A simple background estimation method is presented to remove any nonuniformity in the captured images, resulting in a high detection rate with low false alarms. Finally, a complete, mission-ready payload system is prepared for small UA platforms, with an accuracy rate greater than 97% for the detection of self-propelled semi-submersible vessels

Remote Sensing of the Aquatic Environments

The book highlights recent research efforts in the monitoring of aquatic districts with remote sensing observations and proximal sensing technology integrated with laboratory measurements. Optical satellite imagery gathered at spatial resolutions down to few meters has been used for quantitative estimations of harmful algal bloom extent and Chl-a mapping, as well as winds and currents from SAR acquisitions. The knowledge and understanding gained from this book can be used for the sustainable management of bodies of water across our planet

CMOS Image Sensors in Surveillance System Applications

Recent technology advances in CMOS image sensors (CIS) enable their utilization in the most demanding of surveillance fields, especially visual surveillance and intrusion detection in intelligent surveillance systems, aerial surveillance in war zones, Earth environmental surveillance by satellites in space monitoring, agricultural monitoring using wireless sensor networks and internet of things and driver assistance in automotive fields. This paper presents an overview of CMOS image sensor-based surveillance applications over the last decade by tabulating the design characteristics related to image quality such as resolution, frame rate, dynamic range, signal-to-noise ratio, and also processing technology. Different models of CMOS image sensors used in all applications have been surveyed and tabulated for every year and application.https://doi.org/10.3390/s2102048

High-throughput estimation of crop traits: A review of ground and aerial phenotyping platforms

Crop yields need to be improved in a sustainable manner to meet the expected worldwide increase in population over the coming decades as well as the effects of anticipated climate change. Recently, genomics-assisted breeding has become a popular approach to food security; in this regard, the crop breeding community must better link the relationships between the phenotype and the genotype. While high-throughput genotyping is feasible at a low cost, highthroughput crop phenotyping methods and data analytical capacities need to be improved. High-throughput phenotyping offers a powerful way to assess particular phenotypes in large-scale experiments, using high-tech sensors, advanced robotics, and imageprocessing systems to monitor and quantify plants in breeding nurseries and field experiments at multiple scales. In addition, new bioinformatics platforms are able to embrace large-scale, multidimensional phenotypic datasets. Through the combined analysis of phenotyping and genotyping data, environmental responses and gene functions can now be dissected at unprecedented resolution. This will aid in finding solutions to currently limited and incremental improvements in crop yields

Tactical Satellite (TacSat) feasibility study a scenario driven approach

The objective of this project was to examine the feasibility of developing a tactically controlled, operationally responsive satellite system. A specific mission scenario, the Philippine Sea Scenario, was chosen to guide and bound the analysis. Within the bounds of this scenario, this high level space systems engineering exercise provided insights into operations and military utility as well as enough granularity to estimate costs for such a system. The operational approach and high level design concept is based on the Space Mission Analysis and Design (SMAD) process authored by Wiley J. Larson and Kames R. Wertz. The study shows that there are tactical scenarios in which space capabilities provide military utility and cost effectiveness above what is provided by traditional tactical assets such as UAVs. This is particularly true when large operational areas are involved and long periods of service are required.http://archive.org/details/tacticalsatellit109456927N

Feature Papers of Drones - Volume II

[EN] The present book is divided into two volumes (Volume I: articles 1–23, and Volume II: articles 24–54) which compile the articles and communications submitted to the Topical Collection ”Feature Papers of Drones” during the years 2020 to 2022 describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles (drones). Articles 24–41 are focused on drone applications, but emphasize two types: firstly, those related to agriculture and forestry (articles 24–35) where the number of applications of drones dominates all other possible applications. These articles review the latest research and future directions for precision agriculture, vegetation monitoring, change monitoring, forestry management, and forest fires. Secondly, articles 36–41 addresses the water and marine application of drones for ecological and conservation-related applications with emphasis on the monitoring of water resources and habitat monitoring. Finally, articles 42–54 looks at just a few of the huge variety of potential applications of civil drones from different points of view, including the following: the social acceptance of drone operations in urban areas or their influential factors; 3D reconstruction applications; sensor technologies to either improve the performance of existing applications or to open up new working areas; and machine and deep learning development

Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences

The aim of the Special Issue “Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences” was to present a selection of innovative studies using hyperspectral imaging (HSI) in different thematic fields. This intention reflects the technical developments in the last three decades, which have brought the capacity of HSI to provide spectrally, spatially and temporally detailed data, favoured by e.g., hyperspectral snapshot technologies, miniaturized hyperspectral sensors and hyperspectral microscopy imaging. The present book comprises a suite of papers in various fields of environmental sciences—geology/mineral exploration, digital soil mapping, mapping and characterization of vegetation, and sensing of water bodies (including under-ice and underwater applications). In addition, there are two rather methodically/technically-oriented contributions dealing with the optimized processing of UAV data and on the design and test of a multi-channel optical receiver for ground-based applications. All in all, this compilation documents that HSI is a multi-faceted research topic and will remain so in the future