Traditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy was firstly used in satellites and later in manned aircraft, which are significantly expensive platforms and extremely restrictive due to availability limitations and/or complex logistics. More recently, UAS have emerged as a very popular and cost-effective remote sensing technology, composed of aerial platforms capable of carrying small-sized and lightweight sensors. Meanwhile, hyperspectral technology developments have been consistently resulting in smaller and lighter sensors that can currently be integrated in UAS for either scientific or commercial purposes. The hyperspectral sensors’ ability for measuring hundreds of bands raises complexity when considering the sheer quantity of acquired data, whose usefulness depends on both calibration and corrective tasks occurring in pre- and post-flight stages. Further steps regarding hyperspectral data processing must be performed towards the retrieval of relevant information, which provides the true benefits for assertive interventions in agricultural crops and forested areas. Considering the aforementioned topics and the goal of providing a global view focused on hyperspectral-based remote sensing supported by UAV platforms, a survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestry—wherein the combination of UAV and hyperspectral sensors plays a center role—is presented in this paper. Firstly, the advantages of hyperspectral data over RGB imagery and multispectral data are highlighted. Then, hyperspectral acquisition devices are addressed, including sensor types, acquisition modes and UAV-compatible sensors that can be used for both research and commercial purposes. Pre-flight operations and post-flight pre-processing are pointed out as necessary to ensure the usefulness of hyperspectral data for further processing towards the retrieval of conclusive information. With the goal of simplifying hyperspectral data processing—by isolating the common user from the processes’ mathematical complexity—several available toolboxes that allow a direct access to level-one hyperspectral data are presented. Moreover, research works focusing the symbiosis between UAV-hyperspectral for agriculture and forestry applications are reviewed, just before the paper’s conclusions.

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Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry

Remotely Piloted Aircraft (RPA) is presently in continuous development at a rapid pace. Unmanned Aerial Vehicles (UAVs) or more extensively Unmanned Aerial Systems (UAS) are platforms considered under the RPAs paradigm. Simultaneously, the development of sensors and instruments to be installed onboard such platforms is growing exponentially. These two factors together have led to the increasing use of these platforms and sensors for remote sensing applications with new potential. Thus, the overall goal of this paper is to provide a panoramic overview about the current status of remote sensing applications based on unmanned aerial platforms equipped with a set of specific sensors and instruments. First, some examples of typical platforms used in remote sensing are provided. Second, a description of sensors and technologies is explored which are onboard instruments specifically intended to capture data for remote sensing applications. Third, multi-UAVs in collaboration, coordination, and cooperation in remote sensing are considered. Finally, a collection of applications in several areas are proposed, where the combination of unmanned platforms and sensors, together with methods, algorithms, and procedures provide the overview in very different remote sensing applications. This paper presents an overview of different areas, each independent from the others, so that the reader does not need to read the full paper when a specific application is of interest

Overview and Current Status of Remote Sensing Applications Based on Unmanned Aerial Vehicles (UAVs)

Arthur Chickering is Distinguished Professor of Higher Education at Memphis State University. On leave from the Directorship of the Center for the Study of Higher Education at Memphis State, he is Visiting Professor at George Mason University. Zelda Gamson is a sociologist who holds appointments at the John W. McCormack Institute of Public Affairs at the University of Massachusetts-Boston and in the Center for the Study of Higher and Postsecondary Education at the University of Michigan.

Seven Principles for Good Practice in Undergraduate Education: Faculty Inventory. Institutional Inventory.

Precision Viticulture is experiencing substantial growth thanks to the availability of improved and cost-effective instruments and methodologies for data acquisition and analysis, such as Unmanned Aerial Vehicles (UAV), that demonstrated to compete with traditional acquisition platforms, such as satellite and aircraft, due to low operational costs, high operational flexibility and high spatial resolution of imagery. In order to optimize the use of these technologies for precision viticulture, their technical, scientific and economic performances need to be assessed. The aim of this work is to compare NDVI surveys performed with UAV, aircraft and satellite, to assess the capability of each platform to represent the intra-vineyard vegetation spatial variability. NDVI images of two Italian vineyards were acquired simultaneously from different multi-spectral sensors onboard the three platforms, and a spatial statistical framework was used to assess their degree of similarity. Moreover, the pros and cons of each technique were also assessed performing a cost analysis as a function of the scale of application. Results indicate that the different platforms provide comparable results in vineyards characterized by coarse vegetation gradients and large vegetation clusters. On the contrary, in more heterogeneous vineyards, low-resolution images fail in representing part of the intra-vineyard variability. The cost analysis showed that the adoption of UAV platform is advantageous for small areas and that a break-even point exists above five hectares; above such threshold, airborne and then satellite have lower imagery cost.

Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture

Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI), chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs) equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping.

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Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

The miniaturization of electronics, computers and sensors has created new opportunities for remote sensing applications. Despite the current restrictions on regulation, the use of unmanned aerial vehicles equipped with small thermal, laser or spectral sensors has emerged as a promising alternative for assisting modeling, mapping and monitoring applications in rangelands, forests and agricultural environments. This review provides an overview of recent research that has reported UAV flight experiments on the remote sensing of vegetated areas. To provide a differential trend to other reviews, this paper is not limited to crops and precision agriculture applications, but also includes forest and rangeland applications. This work follows a top-down categorization strategy and attempts to fill the gap between application requirements and the characteristics of selected tools, payloads and platforms. Furthermore, correlations between common requirements and the most frequently used solutions are highlighted.

https://www.mdpi.com/2072-4292/6/11/11051/pdf

UAV Flight Experiments Applied to the Remote Sensing of Vegetated Areas

Nowadays, Unmanned Aerial Vehicles (UAVs) are used in many different applications. Using systems of multiple UAVs is the next obvious step in the process of applying this technology for variety of ...

https://www.worldscientific.com/doi/pdf/10.1142/S2301385020500090

Multiple UAV Systems: A Survey

H.264/AVC is a new international video coding standard that provides higher coding efficiency with respect to previous standards at the expense of a higher computational complexity. The complexity is even higher when H.264/AVC is used in applications with high bandwidth and high quality like high definition (HD) video decoding. In this paper, we analyze the computational requirements of H.264 decoder with a special emphasis in HD video and we compare it with previous standards and lower resolutions. The analysis was done with a SIMD optimized decoder using hardware performance monitoring. The main objective is to identify the application bottlenecks and to suggest the necessary support in the architecture for processing HD video efficiently. We have found that H.264/AVC decoding of HD video perform many more operations per frame than MPEG-4 and MPEG-2, has new kernels with more demanding memory access patterns and has a lot data dependent branches that are difficult to predict. In order to improve the H.264/AVC decoding process at HD it is necessary to explore a better support in media instructions, specialized prefetching techniques and possibly, the use of some kind of multiprocessor architecture.

/pdf/a-performance-characterization-of-high-definition-digital-3r6mnhr0vx.pdf

A performance characterization of high definition digital video decoding using H.264/AVC

HD-VideoBench is a benchmark devoted to high definition (HD) digital video processing. It includes a set of video encoders and decoders (Codecs) for the MPEG-2, MPEG-4 and H.264 video standards. The applications were carefully selected taken into account the quality and portability of the code, the representativeness of the video application domain, the availability of high performance optimizations and the distribution under a free license. Additionally, HD-VideoBench defines a set of input sequences and configuration parameters of the video Codecs which are appropriate for the HD video domain.

/pdf/hd-videobench-a-benchmark-for-evaluating-high-definition-3tjucx6gzn.pdf

HD-VideoBench. A Benchmark for Evaluating High Definition Digital Video Applications

Forest fires are an important problem for many countries. The economical loss is the most visible impact in the short term. The ecological damage and the impact on the wild life diversity and climate change are the most important factors in the long term. Up to now, satellites like NASA's MODIS (moderate-resolution imaging spectroradiometer) system have been the primary source for strategic large area thermal imaging. Tactical monitoring has been until recently reduced to observation from the ground or from some dedicated aerial resource like command and control helicopters. However, little technological support has been available to those in charge of these monitoring tasks. An unmanned aerial systems (UAS) platform capable of overflying the area of a forest fire and with capacity of operating from non-prepared terrains would be an extremely valuable information gathering asset in several well-defined circumstances: surveillance during day and specially night, and early morning or late afternoon monitori...

Esther Salamí

Papers

UAV Flight Experiments Applied to the Remote Sensing of Vegetated Areas

Multiple UAV Systems: A Survey

A performance characterization of high definition digital video decoding using H.264/AVC

HD-VideoBench. A Benchmark for Evaluating High Definition Digital Video Applications

Architecture for a helicopter-based unmanned aerial systems wildfire surveillance system