Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments

Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments provides an overview of how unmanned aerial systems have revolutionized our capability to monitor river systems, soil characteristics, and related processes at unparalleled spatio-temporal resolutions. This capability has enabled enhancements in our capacity to describe water cycle and hydrological processes. The book includes guidelines, technical advice, and practical experience to support practitioners and scientists in increasing the efficiency of monitoring with the help of UAS. The book contains field survey datasets to use as practical exercises, allowing proposed techniques and methods to be applied to real world case studies.

• Includes a summary of technical UAS issues allowing readers to focus on how the exact technology fits their scientific question
• Provides specific applications enabling readers to understand the benefits and threats within the field
• Includes a comprehensive literature review in each chapter, allowing readers to know the key players and research in the field

• Language: English
• Publisher: Elsevier Science
• Release date: Jan 18, 2023
• ISBN: 9780323852845

Book preview

Introduction

Salvatore Manfreda¹ and Eyal Ben Dor²,³ ¹Department of Civil, Building and Environmental Engineering, University of Napoli Federico II, Naples, Italy ²Department of Geography and Human Environment, Tel Aviv University, Tel Aviv, Israel ³Porter School of Environment and Earth Sciences, Faculty of Exact Science, Tel Aviv University, Tel Aviv, Israel

1 Preface

Just as smartphones changed the world of communication, unmanned aerial systems (UAS) technology has changed the remote sensing discipline. The availability of UAS platforms and the miniaturization of sophisticated sensors that were once operated by heavy manned aircraft, along with their current easy operation, have exponentially advanced the UAS discipline over the past decade (Chabot, 2018; Giones and Brem, 2017; Vergouw et al., 2016). This progress is reflected by aggressive activity in both the academic and commercial sectors and is based on the legacy and maturity already achieved by the military sector (Custers, 2016).

The wide-ranging civilian applications continue to grow daily (Gallacher, 2016). For instance, UASs have been recently exploited for mass disinfection and medical supply delivery assistance during COVID-19 pandemic. Applications range from homeland security to journalism, traffic control, package delivery, precision farming, archeology, and environmental monitoring, and to other fields that have not yet been developed or considered.

This book summarizes outcomes of five years of intense activities carried out within the HARMONIOUS COST Action CA16219 on the Harmonization of UAS techniques for agricultural and natural ecosystems monitoring (https://www.costharmonious.eu/). More than 200 researchers and technicians coming from 36 countries have been involved in the HARMONIOUS Action that has stimulated an incredible number of initiatives and outputs to support UAS users. Results have been collected in the present book with the aim to share the experience gained and provide guidance for all those that are willing to approach the use of UAS-based environmental applications.

It should be noted that rapid expansion of UAS applications in many fields precludes us to cover all issues in this highly specialized field. Rather, the book focuses on the use of UAS in the field of water science providing an overview of selected innovative studies and applications and a foundation for new users to understand the potential of UAS. Accordingly, at the time of the publication of this book, it is likely that more progress will have been made, but not reported herein. We therefore recommend that the readers of this book remain abreast of the most recent advances by following the scientific and commercial literature.

The purpose of this book is to provide an overview of the ways in which UASs have revolutionized our capability to monitor vegetation dynamics, river systems, and soil characteristics and processes at unparalleled spatiotemporal resolutions, which has in turn led to enhancements in our capacity to describe water cycle and hydrological processes. It includes guidelines, technical advice, and practical experience to support practitioners and scientists to raise efficiency of monitoring with the help of UAS.

The book is structured in five sections which cover different arguments starting with basic contents and then moving to more specific applications. The first section (comprising Chapters 1–3) offers a series of introductory contents necessary to provide a general background and also to support applications described in the following chapters. The second section (comprising Chapters 4 and 5) is more devoted to real applications and to the UAS-based mapping of natural and agricultural ecosystems. The third section (including Chapters 6 and 7) tackles the problem of soil mapping offering two options available for this kind of observations which can be carried out using traditional techniques or exploiting UAS. The fourth section (including Chapters 8–10) offers a wide range of contents that will support hydrologist and geomorphologist in the use of UAS for river monitoring. The last section that is Chapter 11 provides a practical guidance in the use of software for UAS applications and includes also some reference dataset that could be used for training.

2 Section 1 on general introduction on the use of unmanned aerial system for environmental monitoring

Chapter 1 introduces the evolution of UAS technology (past, present, and future) illustrating the real advantages connected to the use of UAS nowadays and in the near future. A review of UAS technologies; users community and platform availability (rotor, fixed wing, and hybrid); sensors (passive and active); UAS power supply (e.g., battery and cellular cells); regulations, software; constraints; advantages; disadvantages; and market. Particular emphasis will be given to the utilization fields for scientific and commercial activities (e.g., agriculture, civil engineering, homeland security, water monitoring, ground truth for satellite calibration), and cost-effectiveness relative to other remotely sensed datasets, safe crush (e.g., parachutes).

Chapter 2 provides a review of all available protocols, a Taylor made protocol for several missions based on the current knowledge, and users’ experience gained within the HARMONIOUS COST Action. It highlights issues such as regulation requirements; platform restriction and operation (multiple sensors); ground truth (spectral and spatial); and environmental issues (weather, sun elevation, night acquisition, field of sight, etc.). Suggestions and guidance on flight mission planning, safety measures, camera setting and choice, and software available will be given.

Chapter 3 illustrates the use of the photogrammetric technique, called Structure-from-Motion (SfM), and has produced a significant revolution in the field of geomatics and the study of earth surface processes; whereby high-resolution topography can be reconstructed for even low-budget research and applications. SfM may be adopted to produce orthoimagery and digital surface/elevation models at very high spatial resolution in the order of centimeters, which is crucial for many applications, especially for change detection studies. Therefore the use and the methods for a proper application of the SfM algorithms will be at the core of this chapter.

3 Section 2 on vegetation monitoring

Chapter 4 focuses on methods and algorithms for vegetation mapping highlighting the most appropriate sensors, platforms, available algorithms, and examples of research results using several algorithms for vegetation mapping. This chapter also presents comparison with other remote sensing methods highlighting the advantages and disadvantages using UAS for these missions.

Chapter 5 provides complementary knowledge for agricultural ecosystems monitoring. in fact, UAS may help and support a high-resolution mapping of the agricultural ecosystems providing canopy-scale data about plant status, stress, biomass, and evapotranspiration. This chapter will provide a guidance about platform and sensors available for these applications. Moreover, research examples will be given to illustrate UAS’s potential to this end using thermal and optical passive sensors.

4 Section 3 on soil mapping

Chapter 6 tackles the issue of soil texture mapping. The importance of soil texture and soil hydraulic properties will be discussed along with the traditional and proxy ways to evaluate soil texture at the field scale. In this chapter, we introduce a case study that demonstrates the potential of UAS to monitor soil texture and related properties (e.g., porosity, clay content, and water infiltration rate).

Chapter 7 discusses the importance of soil moisture mapping on field scale, alternative methods and their constraining, a review on UAS SMC applications, a field study that present the potential of UAS to extract SMC. Different algorithms for soil moisture retrieval will be introduced and discussed. Moreover, indications about the best monitoring strategy will be provided given the available data and environmental conditions.

5 Section 4 on river monitoring

Chapter 8 introduces the issue of geometric correction and stabilization of images collected by UAS for image velocimetry. UAS possess many advantages in flow river monitoring, big areas can be covered, and videos can be safely collected during high flows. However, images collected by UAS have to be preprocessed in order to remove perspective and radial distortions. Furthermore, displacements induced by wind or UAS vibrations have also to be stabilized. The static portions of the image (e.g., river shore) have to remain static before applying algorithms to measure the surface flow velocity of rivers. This chapter reviews different calibration and stabilization procedures and explores the possibility to simplify camera calibration when using UAS. In most of the cases it is not possible to completely remove camera movement, therefore uncertainty in flow measurements resulting from camera instability and lens distortions is also discussed.

Chapter 9 addresses the monitoring river flow velocity with UAS. The chapter explains the benefits and peculiarities of river monitoring with UAS. It contains information about the fluvial properties that can be monitored and analyzed such as flow velocity distribution and inundation extents. We introduce a generalized river monitoring workflow, from flight planning, data acquisition, through to postprocessing and analysis of results, and shortly describe the state-of-the-art techniques applied at each stage. Such techniques include stabilization and orthorectification of acquired footage, image enhancement, image velocimetry, aggregation of image velocimetry results, data validation, and presentation of results. A case study is included into the chapter to illustrate the application of selected techniques.

Chapter 10 introduces the monitoring of river channel dynamics by UAS. Actively eroding river channels can intensively change their landscapes. Yet accurate monitoring of extensive river channel morphodynamics can be a challenge using ground-based survey techniques, and satellite remote sensing may not be appropriate when the river channel width and rate of erosion are below the spatial resolution of available imagery. However, UASs provide the opportunity to gain timely and high-resolution datasets quantifying river channel changes, bank erosion, point bar and island development, and even bathymetric variations in clearwater conditions, but more studies are needed to assess their overall accuracy. In this chapter, we introduce the use of UAS for monitoring channel change and evaluate the effectiveness of UAS surveys for precisely quantifying river morphodynamics when compared to data derived from terrestrial laser scanning surveys.

6 Section 5 on tools and datasets

The last section complements all contents provided in previous chapters with several tools and data available for UAS applications. In addition, several technical useful information are provided in the appendix of the book. Chapter 11 introduces tools and datasets for UAS applications. It provides a comprehensive description of processing the UAS data from raw DN (digital number) to thematic maps: geometric correction, radiometric calibration, reflectance and brightness temperature extraction, mosaicking, merging data from different UAS and other RS sensors (data fusion), available commercial software for each process, available open codes, and sharing data policy.

References

Chabot, 2018 Chabot D. Trends in drone research and applications as the Journal of Unmanned Vehicle Systems turns five. Journal of Unmanned Vehicle Systems. 2018;6(1):vi–xv.

Custers, 2016 Custers B. Future of Drone Use The Hague, The Netherlands: TMC Asser Press; 2016;.

Giones and Brem, 2017 Giones F, Brem A. From toys to tools: The co-evolution of technological and entrepreneurial developments in the drone industry. In: 2017;:875–884. Cohen B, Amorós JE, Lundy L, eds. The Generative Potential of Emerging Technology. 60.

Vergouw et al., 2016 Vergouw, B., Huub, N., Bondt, G. and Custer, B., 2016. Drone Technology: Types, Payloads, Applications, Frequency Spectrum Issues and Future Developments in Future of Drone use (Ed): 21–45.

Section 1

General introduction on the use of UAS for environmental monitoring

Outline

Chapter 1 Remote sensing of the environment using unmanned aerial systems

Chapter 2 Protocols for UAS-based observation

Chapter 3 Using structure-from-motion workflows for 3D mapping and remote sensing

Chapter 1

Remote sensing of the environment using unmanned aerial systems

Salvatore Manfreda¹ and Eyal Ben Dor²,³,    ¹Department of Civil, Building and Environmental Engineering, University of Napoli Federico II, Naples, Italy,    ²Department of Geography and Human Environment, Tel Aviv University, Tel Aviv, Israel,    ³Porter School of Environment and Earth Sciences, Faculty of Exact Science, Tel Aviv University, Tel Aviv, Israel

Abstract

Unmanned aerial systems (UASs), also termed unmanned aerial vehicles (UAVs) or, more commonly, drones, are rapidly—and even aggressively—penetrating the civilian, commercial, and military fields. The spread of this technology is due mainly to its simplicity, cost-effectiveness, and availability relative to other remote sensing means, such as manned air platforms or satellites. Accordingly, the demand for this technology by many users in many disciplines is growing rapidly. The commercial drone market is projected to be worth $13 billion by 2025, highlighting the importance of understanding all about drones’ characteristics—from technology to products. A wide range of practical civilian applications—including agriculture, aerial photography, and surveillance—are already in use, while others are evolving daily. Almost any application of manned aviation can be adopted by the UAS technology with clear advantages in terms of risk and cost reduction. Monitoring of the environment is one of the most important pillars of UAS today, as it provides routine and continuous coverage cost-effectively and in real-time. The practical stages for operating UAS for environmental monitoring, including technical aspects, scientific bases, and valuable recommendations, are thus critical. The purpose of this book is to provide this information, as well as a wide range of overviews for optimal utilization of the UAS for environmental monitoring, followed by technical aspects and the most recent information and examples. This introductory chapter aims to provide the background for this technology by covering the history of UAS, their commercial and social aspects, and currently available sensors and platforms along with their applications. This chapter provides a comprehensive literature review from the first UAS in 1849 (the balloon bomb) till today.

Keywords

UAS; UAV; drones; environmental monitoring; remote sensing; social and economic issues

1.1 A brief history of unmanned aerial systems

Unmanned aerial systems (UAS) refers to aviation platforms that are controlled remotely (Newcome, 2004). Synonyms are remotely piloted aerial vehicle or remotely piloted aircraft system (RPAS), remote airborne system, and the popularly used drone and unmanned aerial vehicle (UAV). The term UAS was adopted by the United States Department of Defense and the United States Federal Aviation Administration (FAA) in 2005, according to their Unmanned Aircraft Systems Roadmap 2005–2030. The International Civil Aviation Organization and the British Civil Aviation Authority also adopted it, and it is used in the European Union’s Single European Sky Air-Traffic Management Research (SESAR Joint Undertaking) Roadmap for 2020. The term UAS emphasizes the importance of elements other than the aircraft, such as ground-control stations, data links, positioning systems, and other supporting equipment. The term drone stems from old English, referring to the sound of the UAS being similar to the buzzing sound of the male bee (Bloomberg, 2015). Whereas a UAS can be any flying platform that is remotely controlled for any purpose (game, flight, remote sensing, etc.), we refer to the UAS as a platform that carries sensors, in particular sensors that provide spatial information using passive and active means across the optical and thermal ranges (cameras).

Although significant progress has been reported in this discipline over the last 5 years, the use of UAS goes back to the 19th century. In 1880 Arthur Batut acquired aerial photographs from a camera that was attached to a kite and later mounted to a pigeon (Dalamagkidis et al., 2012). The military niche was (and is) the driving force for this technology, with the first reported use of UAS for this purpose dating back to 1849, when Austria attempted to attack Venice using unmanned balloons carrying explosives (Elish, 2017). Later, in the Spanish–American War, a kite was used for this purpose on the battlefield. When the aviation industry emerged in around 1900, the ground was surveyed mainly by human pilots, and the idea of UAS was set aside. Nonetheless, as the option to transfer wireless signals emerged, renewed interest by the military was manifested in the development of aerodynamic platforms operated by radio-controlled assemblies. In 1917 the British tested a small radio-controlled aircraft but did not actually use it in World War I. In 1935 both the United States and England produced small radio-controlled aircraft to serve as targets for pilot training. The UAS was then further developed during the Vietnam War, for reconnaissance missions, to serve as decoys in combat, to launch missiles, and to drop leaflets in psychological operations. The UAS technology became more user-friendly in the early 1980s and late 1990s, when it served as an entrainment game, which advanced its development for simple civilian applications (Giones and Brem, 2017). At the same time, its military applications also improved, with significant progress in reconnaissance applications and weapon-carrying platforms. It should be noted that the UAS technology has, without a doubt, earned top ranking as one of the deadliest tools in the military arsenal. A chronological summary of UAS history and milestones is summarized in Table 1.1.

Table 1.1

The use of UAS in the industry sector mainly progressed with military demand, and the civilian sector did not remain stagnant. The main evolution in this latter sector came with the understanding that UAS technology can overcome the limitations of the remote sensing means offered by orbital and manned aircraft, including resolution (spatial, spectral, and temporal), accessibility, and operational costs. Accordingly, UAS satisfies the growing need for accurate and high-resolution temporal and spatial data that can be obtained under (almost) all-sky conditions and at any time of the day by nonskilled personal. A good comparison between orbital sensor and UAS capabilities is provided by Bansod et al. (2017). With the growing availability of UAS technology to combine platforms and sensors, alongside the progress in electronic and IoT approaches, significant advances have been achieved in the utilization of UAS technology. This includes miniaturization of sensors, power-saving platforms, strong computing power, and advanced positioning systems. Accordingly, UAS technology is rapidly attracting many users, prompting new and innovative applications which had stayed off the shelves due to lack of development. Thus UAS activity has blossomed in the last decade. The increasing interest toward UAS is testified by the rate of increase in scientific articles published over the last decades according to the Web of Science database (accessed on May 2022) using the keywords UAS, UAV, and Environment for the years 1990 to 2022 (Fig. 1.1). A relative slowdown in the number of publications in 2021 has been largely due to the limitation introduced by the COVID-19 restrictions, while the 2022 is still incomplete as a reference value. The observed trend gives a good indication of the current state and expected growth of this technology which is becoming a relevant discipline in the field of remote sensing (see also Chabot, 2018; Manfreda et al., 2018). In addition, it is worthy to mention that the discipline has evolved throughout time, and this can be observed from the distribution of the specific fields where these articles have been published. At the beginning of the current century, most of the publications were in the field of precision agriculture, while many new areas of environmental studies are now exploiting UAS and an increasing number of remote sensing scientists, traditionally using only satellite data, is now using UAS data also.

Figure 1.1 The number of papers in the last two decades (till May 2022) using the keywords UAS, UAV, and Environment, reflecting their increasing ratio.

The availability of the UAS, along with its relatively low-cost operation, has made it very popular for disciplines that were outside the remote sensing arena, such as journalism, rescue missions, fire extinguishing, delivery flights, fishing, communication, and even shepherding and medicine (e.g., Holton et al., 2015; Levin et al., 2016; Anbaroğlu, 2017; Collins et al., 2017; Gupta et al., 2015; Yaxley et al., 2021; Balasingam, 2017). In the remote sensing disciplines, the UAS has the advantage of high temporal and spatial resolution and recent upgrades toward high spectral resolution (Lucieer et al., 2014). This capability has come about with the advances in electro-optical technology, producing better sensors that weigh less. Consequently, many remote sensing fields have started using this technology as either main or secondary systems in their products. In the environmental discipline, UAS technology has become very popular and has contributed quite a lot, especially as a complement to satellite sensors. It should be noted that as the popularity of UAS increased, the safety problems became more and more significant (Huang et al., 2021). Accordingly, regulations and legislation for drone operation are now the bottlenecks in UAS utilization, and future activity depends on the resolution of this issue, as noted by Tsiamis et al. (2019). Nevertheless, the advantages of UAS technology, despite these—mainly legislative—limitations, place this technology at the forefront of the new remote sensing era; pending resolution of the limitations imposed by regulations, its applications are almost infinite.

This book thus focuses on how this technology can be used to solve several specific environmental problems in soil, vegetation, and water scenarios and shows how these applications can pave the way for other topics to evolve in the future.

1.2 Evolution of unmanned aerial systems for monitoring of natural and agricultural ecosystems

Natural and agricultural ecosystems are influenced by climatic forcing, physical characteristics, and management practices that are highly variable in time and space with abrupt shifts (Estrany et al., 2019; Manfreda et al., 2017; Manfreda and Caylor, 2013) due to unfavorable growing conditions or climatic extremes (e.g., heat waves, heavy storms, wildfires, etc.). Therefore monitoring systems need to provide accurate information over large areas with a high revisit frequency (Atzberger, 2013).

UAS platforms provide one such technology that is enabling new horizons in agriculture and the environment applications. For instance, the high resolution of UAS imagery has led to a significant increase in the overall accuracy in species-level vegetation classification, monitoring vegetation status, weed infestations, estimating biomass, predicting yields, detecting crop water stress and/senescent leaves, reviewing herbicide applications, and pest control.

It is well known that remote sensing from orbit and air domains provides important information about vegetation status, such as green coverage, photosynthetic activity, plant stress, yield estimation, and phenology (Fawcett et al., 2021), as well as for many environmental monitoring applications. Whereas the traditional remote sensing means and applications are backed by a physical foundation that can explain interactions of vegetation, water, and soil with electromagnetic radiation, there are several significant limitations: poor temporal resolution of satellite or airborne platforms due to long revisit times (10–15 days for polar satellites, depending on the altitude), the problem of cloud coverage, and the cost of manned aircraft flight hours. The spatial resolution of satellites is also limited mostly to free available data and precise information regarding the calibration and validation of the sensor. In addition, poor spectral resolution hinders accurate analyses of specific targets. Using a manned airborne system that might solve some of these problems is still complicated, due to cost and mainly conditions of operation, such as obtaining permission to fly, mission planning, and good weather conditions. Accordingly, the traditional remote sensing means cannot serve as an optimal tool for individuals such as farmers or environment watchers who are interested in a particular area or a specific application. Therefore potential users who could learn a lot from remote sensing means have never even considered using them, thus missing out on many of the technology’s advantages. The evolution of UAS in the market, first for professionals and later for almost anyone, opened up the remote sensing field to many new users. With time, UASs have solved the problems encountered with other remote sensing means and, fortuitously, is providing an effective tool, such that potential users are slowly but surely coming to understand the impact of remote sensing technology on their revenue.

With the advent of autopilot systems that can carry out an entire mission autonomously, UASs are becoming even more accessible. As previously mentioned, regulatory issues are the only barrier to massive UAS operation and the development of more applications. The latter involve postprocessing of the data into a final product, such as water deficiency in selected plants or in the soil parcel. Today, the first processing stage relies on highly user-friendly software that mosaics the images and assesses geometric attenuation, rectifying it accordingly. Methods such as atmospheric or geometric corrections are also valid. In agriculture, the ability to fly the UAS throughout the growing season on a regular temporal basis provides a remarkable advantage over traditional remote sensing means. The new hyperspectral light sensors entering the UAS field provide high spectral resolution and new horizons in mapping accuracy. The emergence of companies providing services to farmers, such as basic flight coverage, pre- and postprocessing, and thematic mapping (Saari et al., 2011), demonstrates a promising forecasted market revenue for UAS technology. It is expected that new generations of farmers will have the capability to operate UAS themselves, including all or some of their technical aspects (Nintanavongsa and Pitimon, 2017). Closure of the postprocessing gap will enable dummy users to smoothly exploit the UAS chain from mission planning to flight operation and data analysis. Problems such as vegetative stress monitoring in high spatial resolution, as well as irrigation management, nutrient stress monitoring, soil salinity mapping, and yield estimation are only a few examples of applications that are already in use. We anticipate that all the current barriers will be eliminated and in the near future, the UAS discipline will be an integral part of agricultural and environmental activities, just as it became an integral part of every platoon in the military.

1.2.1 Precision agriculture

Precision agriculture has been the most common application of UAS (Zhang and Kovacs, 2012). High-spatial-resolution UAS imagery enables much earlier and more cost-effective detection, diagnosis, and corrective action of agricultural management problems compared to low-resolution satellite imagery. Therefore UAS can address the needs of farmers or other users, enabling them to make better management decisions with minimal costs and environmental impact (Huang et al., 2013; Link et al., 2013; Zhang et al., 2014).

Vegetation state can be evaluated and quantified through different vegetation indices from images acquired in the visible, red edge, near-infrared (NIR), and short infrared spectral bands. Depending on their formulation, these can display a strong correlation with soil coverage and Leaf and Green Area Index, Crop Nitrogen Uptake, chlorophyll content, water stress detection, canopy structure, photosynthesis, yield, and/or growing conditions (e.g., Helman et al., 2015; Gago et al., 2015).

Among the many available vegetation indices, the Normalized Difference Vegetation Index (NDVI) and its derivations (e.g., SAVI) is one that is most widely used (Lacaze et al., 1996; Gigante et al., 2009; Helman, 2018). UAS-NDVI maps can be at least comparable to those obtained from satellite visible observations and become highly relevant for a timely assessment of crop health status, with capacity to provide immediate feedback to the farmer. NDVI surveys performed with UAS, aircraft, and satellite demonstrate that low-resolution images generally fail in representing intrafield variability and patterns in fields characterized by small vegetation gradients and high vegetation patchiness (Matese et al., 2015).

An example of the achievable resolution obtained from UAS is given in Fig. 1.2, where also some available high-resolution commercial satellite imagery are displayed for comparison. The observed differences between vegetation patterns and resolvable resolution observed by UAS are clearly identified. The relative advantages of UAS in providing a level of detail that is comparable to field observations are illustrated by its capability of capturing both within and between canopy characteristics.

Figure 1.2 Multispectral false color (near infrared, red, green) imagery collected over a date palm farm in Saudi Arabia. Imagery (from L to R) shows the resolution differences between: (A) UAS mounted Parrot Sequoia sensor at 50 m height (resolution of 0.05 m); (B) a WorldView-3 image (resolution of 1.24 m); and (C) Planet CubeSat data (resolution of approx. 3 m). Source: Extracted from Manfreda, S., McCabe, M.F., Miller, P.E., Lucas, R., Pajuelo Madrigal, V., Mallinis, G., et al., 2018. On the use of unmanned aerial systems for environmental monitoring. Remote. Sens., 10(4), 641. https://doi.org/10.3390/rs10040641.

In this context, Zarco-Tejada et al. (2013a,b,c,d) demonstrated the potential of UAS for monitoring specific variables of vineyards, such as crop water stress index (CWSI), photosynthetic activity, and carotenoid content in vineyards using multispectral, hyperspectral, and thermal cameras. Several of these indices described earlier may be used for rapid detection of crop pest outbreaks or for mapping the status of crops.

Likewise, monitoring soil water content is critical for determining efficient irrigation scheduling. The topsoil moisture content can be derived using RGB, NIR, and thermal bands (Hassan-Esfahani et al., 2015). The effective amount of water stored in the subsurface can be obtained using mathematical relationships or data assimilation and modeling (e.g., Manfreda et al., 2014, Baldwin et al., 2017; Martens et al., 2017). More details about the soil moisture monitoring can be found in Chapter 6 and 7.

The thermal infrared (TIR) emittance displays a negative correlation with soil water content, stomatal conductance, and canopy closure, indicating increasing canopy stress as stomatal conductance and canopy closure decreased (Sullivan et al., 2007). UAS equipped with a thermal camera (mostly broad band) can be used to derive the CWSI (Jackson et al.,1981; Cohen et al., 2017), which can be used not only to define watering needs but also to quantify the physiological status of plants, and, more specifically, leaf water potential in experimental vineyards or orchards (Baluja et al., 2012; Bellvert et al., 2014; Gonzalez-Dugo et al., 2013; Zarco-Tejada et al.,