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"drone remote sensing"
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Unmanned aerial vehicles
\"Unmanned Aerial Vehicles presents concepts important to any individual endeavoring to use unmanned aerial vehicles in work or research for the first time. The capability of using unmanned aerial vehicles in performing atmospheric chemical measurements and in the design of sensor and sampling payloads is discussed, and a review of recent trends is provided. The authors explore the concept of a universal flight and navigation system for small and ultra-small unmanned aerial vehicles with open architecture both in hardware and software terms. The closing study details unmanned aerial vehicle photogrammetry, its idiosyncrasies, and its applicability in the conservation of archaeological objects\"-- Provided by publisher.
Book
Unmanned Aerial Remote Sensing
Unmanned Aircraft Systems (UASs) are a rapidly evolving technology with an expanding array of diverse applications. In response to the continuing evolution of this technology, this book discusses unmanned aerial vehicles (UAVs) and similar systems, platforms, and sensors, as well as exploring some of their environmental applications. It explains how they can be used for mapping, monitoring, and modelling a wide variety of different environmental aspects and, at the same time, addresses some of the current constraints placed on realising the potential use of the technology such as flight duration and distance, safety, and the invasion of privacy.
Features:
Provides necessary theoretical foundations for pertinent subject matter areas
Introduces the role and value of UAVs for geographical data acquisition and the ways to acquire and process the data
Provides a synthesis of ongoing research and a focus on the use of technology for small-scale image and spatial data acquisition in an environmental context
Written by experts of the technology who bring together UAS tools and resources for environmental specialists.
Unmanned Aerial Remote Sensing: UAS for Environmental Applications is an excellent resource for any practitioner utilising remote sensing and other geospatial technologies for environmental applications, such as conservation, research, and planning. Students and academics in information science, environment and natural resources, geosciences, and geography will likewise find this comprehensive book a useful and informative resource.
eBook
Fundamentals of capturing and processing drone imagery and data
\"Unmanned Aircraft Systems are rapidly emerging as flexible platforms for capturing imagery and other data across sciences. Many colleges and universities are developing courses on UAS-based data acquisition. This book is a comprehensive, introductory text on how to use unmanned aircraft systems for data capture and analysis. It provides best practices for planning data capture missions and hands-on learning modules geared toward UAS data collection, processing, and applications. Readers will learn how to process different types of UAS imagery for applications such as Precision Agriculture, Forestry, Urban Landscapes, and apply this knowledge in environmental monitoring and land-use studies\"-- Provided by publisher.
Book
A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing
The Normalized Difference Vegetation Index (NDVI), one of the earliest remote sensing analytical products used to simplify the complexities of multi-spectral imagery, is now the most popular index used for vegetation assessment. This popularity and widespread use relate to how an NDVI can be calculated with any multispectral sensor with a visible and a near-IR band. Increasingly low costs and weights of multispectral sensors mean they can be mounted on satellite, aerial, and increasingly—Unmanned Aerial Systems (UAS). While studies have found that the NDVI is effective for expressing vegetation status and quantified vegetation attributes, its widespread use and popularity, especially in UAS applications, carry inherent risks of misuse with end users who received little to no remote sensing education. This article summarizes the progress of NDVI acquisition, highlights the areas of NDVI application, and addresses the critical problems and considerations in using NDVI. Detailed discussion mainly covers three aspects: atmospheric effect, saturation phenomenon, and sensor factors. The use of NDVI can be highly effective as long as its limitations and capabilities are understood. This consideration is particularly important to the UAS user community.
Journal Article
Coastal and Environmental Remote Sensing from Unmanned Aerial Vehicles: An Overview
Klemas, V.V., 2015. Coastal and environmental remote sensing from unmanned aerial vehicles: An overview. Unmanned aerial vehicles (UAVs) offer a viable alternative to conventional platforms for acquiring high-resolution remote-sensing data at lower cost and increased operational flexibility. UAVs include various configurations of unmanned aircraft, multirotor helicopters (e.g., quadcopters), and balloons/blimps of different sizes and shapes. Quadcopters and balloons fill a gap between satellites and aircraft when a stationary monitoring platform is needed for relatively long-term observation of an area. UAVs have advanced designs to carry small payloads and integrated flight control systems, giving them semiautonomous or fully autonomous flight capabilities. Miniaturized sensors are being developed/adapted for UAV payloads, including hyperspectral imagers, LIDAR, synthetic aperture radar, and thermal infrared sensors. UAVs are now used for a wide range of environmental applications, such as coastal wetland mapping, LIDAR bathymetry, flood and wildfire surveillance, tracking oil spills, urban studies, and Arctic ice investigations.
Journal Article
Agricultural drones
Explains how drones help farmers maximize efficiencies and bring abundant harvests.
Book
An Improved TransMVSNet Algorithm for Three-Dimensional Reconstruction in the Unmanned Aerial Vehicle Remote Sensing Domain
It is important to achieve the 3D reconstruction of UAV remote sensing images in deep learning-based multi-view stereo (MVS) vision. The lack of obvious texture features and detailed edges in UAV remote sensing images leads to inaccurate feature point matching or depth estimation. To address this problem, this study improves the TransMVSNet algorithm in the field of 3D reconstruction by optimizing its feature extraction network and costumed body depth prediction network. The improvement is mainly achieved by extracting features with the Asymptotic Pyramidal Network (AFPN) and assigning weights to different levels of features through the ASFF module to increase the importance of key levels and also using the UNet structured network combined with an attention mechanism to predict the depth information, which also extracts the key area information. It aims to improve the performance and accuracy of the TransMVSNet algorithm’s 3D reconstruction of UAV remote sensing images. In this work, we have performed comparative experiments and quantitative evaluation with other algorithms on the DTU dataset as well as on a large UAV remote sensing image dataset. After a large number of experimental studies, it is shown that our improved TransMVSNet algorithm has better performance and robustness, providing a valuable reference for research and application in the field of 3D reconstruction of UAV remote sensing images.
Journal Article
Drones : science, technology, engineering
\"Learn about the history of drones and find out what it takes to make it in this exciting career field\"-- Provided by publisher.
Book
Climate-Change-Driven Droughts and Tree Mortality: Assessing the Potential of UAV-Derived Early Warning Metrics
Protecting and enhancing forest carbon sinks is considered a natural solution for mitigating climate change. However, the increasing frequency, intensity, and duration of droughts due to climate change can threaten the stability and growth of existing forest carbon sinks. Extreme droughts weaken plant hydraulic systems, can lead to tree mortality events, and may reduce forest diversity, making forests more vulnerable to subsequent forest disturbances, such as forest fires or pest infestations. Although early warning metrics (EWMs) derived using satellite remote sensing data are now being tested for predicting post-drought plant physiological stress and mortality, applications of unmanned aerial vehicles (UAVs) are yet to be explored extensively. Herein, we provide twenty-four prospective approaches classified into five categories: (i) physiological complexities, (ii) site-specific and confounding (abiotic) factors, (iii) interactions with biotic agents, (iv) forest carbon monitoring and optimization, and (v) technological and infrastructural developments, for adoption, future operationalization, and upscaling of UAV-based frameworks for EWM applications. These UAV considerations are paramount as they hold the potential to bridge the gap between field inventory and satellite remote sensing for assessing forest characteristics and their responses to drought conditions, identifying and prioritizing conservation needs of vulnerable and/or high-carbon-efficient tree species for efficient allocation of resources, and optimizing forest carbon management with climate change adaptation and mitigation practices in a timely and cost-effective manner.
Journal Article