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Toward Improved Crop Management Using Spectral Sensing With Unmanned Aerial Systems
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Book Synopsis Toward Improved Crop Management Using Spectral Sensing with Unmanned Aerial Systems by : Robert Ormal Chancia
Download or read book Toward Improved Crop Management Using Spectral Sensing with Unmanned Aerial Systems written by Robert Ormal Chancia and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Remote sensing applications in agriculture are established for large-scale monitoring with satellite and airborne imagery, but unmanned aerial systems (UAS) are poised to bring in-field mapping capabilities to the hands of individual farmers. UAS imaging holds several advantages over traditional methods, including centimeter-scale resolution, reduced atmospheric absorption, flexible timing of data acquisitions, and ease of use. In this work, we present two studies using UAS imaging of specialty crops in upstate New York to work towards improved crop management applications. The first study is an investigation of multispectral imagery obtained over table beet fields in Batavia, NY during the 2018 and 2019 seasons to be used in root yield modeling. We determined optimal growth stages for future observations and establish the importance of quantifying early growth via determination of canopy area, a feature unattainable with lower resolution imaging. We developed models for root mass and count based on area-augmented imagery of our raw study plots and their corresponding ground truth data for practical testing with independent data sets. The second study was designed to determine an optimal subset of wavelengths derived from hyperspectral imagery that are related to grapevine nutrients for improved vineyard nutrient monitoring. Our ensemble wavelength selection and regression algorithm chose wavelengths consistent with known absorption features related to nitrogen content in vegetation. Our model achieved a leave-one-out cross-validation root-mean-squared error of 0.17% nitrogen in our dried vine-leaf samples with 2.4-3.6% nitrogen. This is an improvement upon published studies of typical UAS multispectral sensors used to assess grapevine nitrogen status. With further testing on new data, we can determine consistently selected wavelengths and guide the design of specialty multispectral sensors for improved grapevine nutrient management."--Abstract.
Book Synopsis UAS-Remote Sensing Methods for Mapping, Monitoring and Modeling Crops by : Francisco Javier Mesas Carrascosa
Download or read book UAS-Remote Sensing Methods for Mapping, Monitoring and Modeling Crops written by Francisco Javier Mesas Carrascosa and published by MDPI. This book was released on 2021-04-22 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advances in unmanned aerial vehicle (UAV) platforms and onboard sensors in the past few years have greatly increased our ability to monitor and map crops. The ability to register images at ultrahigh spatial resolution at any moment has made remote sensing techniques increasingly useful in crop management. These technologies have revolutionized the way in which remote sensing is applied in precision agriculture, allowing for decision-making in a matter of days instead of weeks. However, it is still necessary to continue research to improve and maximize the potential of UAV remote sensing in agriculture. This Special Issue of Remote Sensing includes different applications of UAV remote sensing for crop management, covering RGB, multispectral, hyperspectral and light detection and ranging (LiDAR) sensor applications aboard UAVs. The papers reveal innovative techniques involving image analysis and cloud points. However, it should be emphasized that this Special Issue is a small sample of UAV applications in agriculture and that there is much more to investigate.
Book Synopsis Unmanned Aerial Systems in Agriculture by : Dionysis Bochtis
Download or read book Unmanned Aerial Systems in Agriculture written by Dionysis Bochtis and published by Elsevier. This book was released on 2023-09-02 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned Aerial Systems in Agriculture: Eyes Above Fields bridges the gap between knowledge of concept and real-world use and operations of UASs in agri-production. Based on a valuable combination of themes presented at the 13th European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) and supplemented by targeted invited articles of key-scientists, this book presents a full-spectrum view of the use of unmanned aerial systems (UAS) for agricultural applications. It integrates dispersed knowledge in the field, providing a holistic approach regarding UAVs and other UAS and their use in sustainable decisions. The integrated approach of the book provides a fresh look on contemporary agriculture-related issues, following precision farming approaches, by educating on a range of different issues of remote sensing and its use in agriculture. Furthermore, the operational planning aspects for UAS in agriculture focus part of the book provides information that is missing from other resources. Addresses practical issues and the latest technology application insights Provides specialized and comprehensive information for daily use-cases Ties remote sensing using aerial systems and precision farming issues
Book Synopsis Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments by : Salvatore Manfreda
Download or read book Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments written by Salvatore Manfreda and published by Elsevier. This book was released on 2023-01-18 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Understanding the Value Proposition Unmanned Aerial Systems Provide During the Phases of the Crop Cycle by : Tobias J. Walters
Download or read book Understanding the Value Proposition Unmanned Aerial Systems Provide During the Phases of the Crop Cycle written by Tobias J. Walters and published by . This book was released on 2015 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasing crop productivity is a challenge as old as human history. Advancements in technology have allowed farmers to produce ever-increasing amounts of food on a given amount of land. With the world's population expected to reach roughly nine billion by 2050 (United Nations 2013), the demand for food will require increasingly improved methods of agricultural production. One of these potential methods is the use of unmanned aerial vehicles (UAVs) to monitor crop health and identify potential issues. This thesis will explore how current stakeholders plan to utilize this technology and the perceived value they believe it will deliver across the various phases of the crop cycle. This thesis begins by reviewing modem precision agriculture management practices and discussing how remote sensing plays a role in improving the efficiency of these types of farming methods. It also identifies a number of challenges facing the industry to include the impact of current regulations on the market. This thesis develops a stakeholder value network that clarifies the tangible and intangible value exchanges between the focal organization and its stakeholders. As well as constructing an OPM (Object Process Methodology) model to describe the system and demonstrate the stakeholder interactions and system process and sub-process decomposition. It also provides visual display of how the value is delivered across these processes. The final aspect of the research for this thesis is to identifies the lead users for these systems and determines how they measure the value of the data provided by UAVs for remote sensing and crop management decisions in support of farming operations. The value proposition for the various crop phases and the ideal uses cases discussed by lead users in this thesis may be used to guide future research in agriculture technology development, and drive further innovation in the emerging field of commercial unmanned aerial system use.
Book Synopsis Toward Structural Characterization of Broadacre Crops Using UAS-based 3D Point Clouds by : Fei Zhang
Download or read book Toward Structural Characterization of Broadacre Crops Using UAS-based 3D Point Clouds written by Fei Zhang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The use of unmanned aerial systems (UAS)-based remote sensing methods in precision agriculture (PA) has seen rapid development in recent years. These technologies are expected to revolutionize crop management by capturing imagery data with a high spatial, temporal, and spectral resolution, thereby enabling the decision-making of farm inputs at the sub-field level and on an almost daily basis. However, in real-world operational applications, the potential of UAS-based remote sensing methods has not yet been fully exploited. One of the main research avenues is that of structural characterization of crops in order to assess plant density, leaf density, i.e., overall crop health, and ultimately, crop yield. Using a UAS-based imagery system, we concurrently collected multi-source imagery data. We used structure-from-motion (SfM; photogrammetry) and light detection and ranging (LiDAR) point clouds to observe snap bean fields across two years. We hypothesized that the 3D point clouds represent essential structural information of the crop and that by extracting various features from the oversampled (dense) 3D data, we could retrieve critical structural characteristics of the crops and eventually relate them to high-level objectives, including disease risk and yield modeling. We further explored the effectiveness of feature-level data fusion between LiDAR point clouds and multispectral imagery, coupled with machine learning algorithms, for yield modeling and disease detection applications. We found that both SfM and LiDAR point clouds achieved similar high accuracies for assessment of crop height (CH) and row width (RW) (RMSE of ~0.02 m for CH and ~0.05 m for RW). For measuring the leaf area index (LAI), the LiDAR-derived models achieved the highest accuracy (R2= 0.61, nRMSE = 19%), while the SfM-derived models exhibited slightly lower values with a predicted R2≈0.5 and nRMSE ≈22%. We found that the fusion of LiDAR and MSI data yielded good results for prediction of the snap bean yield, with an Adj. R2 = 0.827 and nRMSE = 9.4%. This work demonstrated the potential of 3D point cloud data in PA applications and the performance of a UAS-based remote sensing system in monitoring short broadacre crops, such as snap bean."--Abstract.
Book Synopsis Unmanned Aerial Systems in Precision Agriculture by : Zhao Zhang
Download or read book Unmanned Aerial Systems in Precision Agriculture written by Zhao Zhang and published by Springer Nature. This book was released on 2022-05-17 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, consisting of 8 chapters, describes the state-of-the-art technological progress and applications of unmanned aerial vehicles (UAVs) in precision agriculture. It focuses on the UAV application in agriculture, such as crop disease detection, mid-season yield estimation, crop nutrient status, and high-throughput phenotyping. Different from individual papers focusing on a specific application, this book provides a holistic view for readers with a wide range of subjects. In addition to researchers in the areas of plant science, plant pathology, breeding, engineering, it is also intended for undergraduates and graduates who are interested in imaging processing, artificial intelligence in agriculture, precision agriculture, agricultural automation, and robotics.
Book Synopsis On the Use of Imaging Spectroscopy from Unmanned Aerial Systems (UAS) to Model Yield and Assess Growth Stages of a Broadacre Crop by : Amirhossein Hassanzadeh
Download or read book On the Use of Imaging Spectroscopy from Unmanned Aerial Systems (UAS) to Model Yield and Assess Growth Stages of a Broadacre Crop written by Amirhossein Hassanzadeh and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Snap bean production was valued at $363 million in 2018. Moreover, the increasing need in food production, caused by the exponential increase in population, makes this crop vitally important to study. Traditionally, harvest time determination and yield prediction are performed by collecting limited number of samples. While this approach could work, it is inaccurate, labor-intensive, and based on a small sample size. The ambiguous nature of this approach furthermore leaves the grower with under-ripe and over-mature plants, decreasing the final net profit and the overall quality of the product. A more cost-effective method would be a site-specific approach that would save time and labor for farmers and growers, while providing them with exact detail to when and where to harvest and how much is to be harvested (while forecasting yield). In this study we used hyperspectral (i.e., point-based and image-based), as well as biophysical data, to identify spectral signatures and biophysical attributes that could schedule harvest and forecast yield prior to harvest. Over the past two decades, there have been immense advances in the field of yield and harvest modeling using remote sensing data. Nevertheless, there still exists a wide gap in the literature covering yield and harvest assessment as a function of time using both ground-based and unmanned aerial systems. There is a need for a study focusing on crop-specific yield and harvest assessment using a rapid, affordable system. We hypothesize that a down-sampled multispectral system, tuned with spectral features identified from hyperspectral data, could address the mentioned gaps. Moreover, we hypothesize that the airborne data will contain noise that could negatively impact the performance and the reliability of the utilized models. Thus, We address these knowledge gaps with three objectives as below: 1. Assess yield prediction of snap bean crop using spectral and biophysical data and identify discriminating spectral features via statistical and machine learning approaches. 2. Evaluate snap bean harvest maturity at both the plant growth stage and pod maturity level, by means of spectral and biophysical indicators, and identify the corresponding discriminating spectral features. 3. Assess the feasibility of using a deep learning architecture for reducing noise in the hyperspectral data. In the light of the mentioned objectives, we carried out a greenhouse study in the winter and spring of 2019, where we studied temporal change in spectra and physical attributes of snap-bean crop, from Huntington cultivar, using a handheld spectrometer in the visible- to shortwave-infrared domain (400-2500 nm). Chapter 3 of this dissertation focuses on yield assessment of the greenhouse study. Findings from this best-case scenario yield study showed that the best time to study yield is approximately 20-25 days prior to harvest that would give out the most accurate yield predictions. The proposed approach was able to explain variability as high as R2 = 0.72, with spectral features residing in absorption regions for chlorophyll, protein, lignin, and nitrogen, among others. The captured data from this study contained minimal noise, even in the detector fall-off regions. Moving the focus to harvest maturity assessment, Chapter 4 presents findings from this objective in the greenhouse environment. Our findings showed that four stages of maturity, namely vegetative growth, budding, flowering, and pod formation, are distinguishable with 79% and 78% accuracy, respectively, via the two introduced vegetation indices, as snap-bean growth index (SGI) and normalized difference snap-bean growth index (NDSI), respectively. Moreover, pod-level maturity classification showed that ready-to-harvest and not-ready-to-harvest pods can be separated with 78% accuracy with identified wavelengths residing in green, red edge, and shortwave-infrared regions. Moreover, Chapters 5 and 6 focus on transitioning the learned concepts from the mentioned greenhouse scenario to UAS domain. We transitioned from a handheld spectrometer in the visible to short-wave infrared domain (400-2500 nm) to a UAS-mounted hyperspectral imager in the visible-to-near-infrared region (400-1000 nm). Two years worth of data, at two different geographical locations, were collected in upstate New York and examined for yield modeling and harvest scheduling objectives. For analysis of the collected data, we introduced a feature selection library in Python, named “Jostar”, to identify the most discriminating wavelengths. The findings from the yield modeling UAS study show that pod weight and seed length, as two different yield indicators, can be explained with R2 as high as 0.93 and 0.98, respectively. Identified wavelengths resided in blue, green, red, and red edge regions, and 44-55 days after planting (DAP) showed to be the optimal time for yield assessment. Chapter 6, on the other hand, evaluates maturity assessment, in terms of pod classification, from the UAS perspective. Results from this study showed that the identified features resided in blue, green, red, and red-edge regions, contributing to F1 score as high as 0.91 for differentiating between ready-to-harvest vs. not ready-to-harvest. The identified features from this study is in line with those detected from the UAS yield assessment study. In order to have a parallel comparison of the greenhouse study against the UAS study, we adopted the methodology employed for UAS studies and applied it to the greenhouse studies, in Chapter 7. Since the greenhouse data were captured in the visible-to-shortwave-infrared (400-2500 nm) domain, and the UAS study data were captured in the VNIR (400-1000 nm) domain, we truncated the spectral range of the collected data from the greenhouse study to the VNIR domain. The comparison experiment between the greenhouse study and the UAS studies for yield assessment, at two harvest stages early and late, showed that spectral features in 450-470, 500-520, 650, 700-730 nm regions were repeated on days with highest coefficient of determination. Moreover, 46-48 DAP with high coefficient of determination for yield prediction were repeated in five out of six data sets (two early stages, each three data sets). On the other hand, the harvest maturity comparison between the greenhouse study and the UAS data sets showed that similar identified wavelengths reside in ∼450, ∼530, ∼715, and ∼760 nm regions, with performance metric (F1 score) of 0.78, 0.84, and 0.9 for greenhouse, 2019 UAS, and 2020 UAS data, respectively. However, the incorporated noise in the captured data from the UAS study, along with the high computational cost of the classical mathematical approach employed for denoising hyperspectral data, have inspired us to leverage the computational performance of hyperspectral denoising by assessing the feasibility of transferring the learned concepts to deep learning models. In Chapter 8, we approached hyperspectral denoising in spectral domain (1D fashion) for two types of noise, integrated noise and non-independent and non-identically distributed (non-i.i.d.) noise. We utilized Memory Networks due to their power in image denoising for hyperspectral denoising, introduced a new loss and benchmarked it against several data sets and models. The proposed model, HypeMemNet, ranked first - up to 40% in terms of signal-to-noise ratio (SNR) for resolving integrated noise, and first or second, by a small margin for resolving non-i.i.d. noise. Our findings showed that a proper receptive field and a suitable number of filters are crucial for denoising integrated noise, while parameter size was shown to be of the highest importance for non-i.i.d. noise. Results from the conducted studies provide a comprehensive understanding encompassing yield modeling, harvest scheduling, and hyperspectral denoising. Our findings bode well for transitioning from an expensive hyperspectral imager to a multispectral imager, tuned with the identified bands, as well as employing a rapid deep learning model for hyperspectral denoising."--Abstract.
Book Synopsis Remote Sensing in Precision Agriculture by : Salim Lamine
Download or read book Remote Sensing in Precision Agriculture written by Salim Lamine and published by Elsevier. This book was released on 2023-10-20 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote Sensing in Precision Agriculture: Transforming Scientific Advancement into Innovation compiles the latest applications of remote sensing in agriculture using spaceborne, airborne and drones’ geospatial data. The book presents case studies, new algorithms and the latest methods surrounding crop sown area estimation, determining crop health status, assessment of vegetation dynamics, crop diseases identification, crop yield estimation, soil properties, drone image analysis for crop damage assessment, and other issues in precision agriculture. This book is ideal for those seeking to explore and implement remote sensing in an effective and efficient manner with its compendium of scientifically and technologically sound information. Presents a well-integrated collection of chapters, with quality, consistency and continuity Provides the latest RS techniques in Precision Agriculture that are addressed by leading experts Includes detailed, yet geographically global case studies that can be easily understood, reproduced or implemented Covers geospatial data, with codes available through shared links
Book Synopsis Unmanned Aerial Systems in Agriculture by : Lav R. Khot
Download or read book Unmanned Aerial Systems in Agriculture written by Lav R. Khot and published by . This book was released on 2017 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emergence of unmanned aerial systems (UAS) has enhanced possibilities of acquiring high-resolution multispectral (i.e., few spectral bands) images of agricultural fields at a temporal resolution controlled by the user. It can lead to easier and faster monitoring of large farms and agricultural decision making. UAS have evolved into an important technology in precision agriculture with multiple companies and agricultural service providers exploring how to integrate it into production management decision making. Sensors are an integral part of UAS technology for its meaningful and efficient use in agriculture.
Book Synopsis Applications of Computer Vision and Drone Technology in Agriculture 4.0 by : Siddharth Singh Chouhan
Download or read book Applications of Computer Vision and Drone Technology in Agriculture 4.0 written by Siddharth Singh Chouhan and published by Springer Nature. This book was released on with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Food and Agriculture Organization of the United Nations Publisher :Food & Agriculture Org. ISBN 13 :9251098409 Total Pages :94 pages Book Rating :4.2/5 (51 download)
Book Synopsis Review of the available remote sensing tools, products, methodologies and data to improve crop production forecasts by : Food and Agriculture Organization of the United Nations
Download or read book Review of the available remote sensing tools, products, methodologies and data to improve crop production forecasts written by Food and Agriculture Organization of the United Nations and published by Food & Agriculture Org.. This book was released on 2018-05-31 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Timely and reliable agricultural production forecasts are critical to make informed food policy decisions and enable rapid responses to emerging food shortfalls. Sub-Saharan Africa is subject to highly variable yield, production and consumption, occasioned by high climate variability, rapidly increasing populations, and limited financial capacity. This review examines the current status of the remote sensing (RS) tools, products, methodologies and data that can help to improve agricultural crop production forecasting systems.
Book Synopsis Soil and Crop Sensing for Precision Crop Production by : Minzan Li
Download or read book Soil and Crop Sensing for Precision Crop Production written by Minzan Li and published by Springer Nature. This book was released on 2022-09-07 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soil and crop sensing is a fundamental component and the first important step in precision agriculture. Unless the level of soil and crop variability is known, appropriate management decisions cannot be made and implemented. In the last few decades, various ground-based sensors have been developed to measure spatial variability in soil properties and nutrients, crop growth and yield, and pest conditions. Remote sensing as an important data collection tool has been increasingly used to map soil and crop growth variability as spatial, spectral and temporal resolutions of image data have improved significantly in recent years. While identifying spatial variability of soil and crop growth within fields is an important first step towards precision management, using that variability to formulate variable rate application plans of farming inputs such as fertilizers and pesticides is another essential step in precision agriculture.The purpose of this book is to present the historical, current and future developments of soil and crop sensing technologies with fundamentals and practical examples. The first chapter gives an overview of soil and crop sensing technologies for precision crop production. The next six chapters provide details on theories, methods, practical applications, as well as challenges and future research needs for all aspects of soil and crop sensing. The last two chapters show how soil and crop sensing technologies can be used for plant phenotyping and precision fertilization. The chapters are written by some of the world’s leading experts who have contributed significantly to the developments of precision agriculture technologies, especially in the area of soil and crop sensing. They use their knowledge, experiences, and successful stories to present informative and up-to-date information on relevant topics. Therefore, this book is an invaluable addition to the literature and can be used as a reference by scientists, engineers, practitioners, and college students for the dissemination and advancement of precision agriculture technologies for practical applications.
Book Synopsis An Autonomous Unmanned Aerial Vehicle-based Imagery System Development and Remote Sensing Images Classification for Agricultural Applications by : Yiding Han
Download or read book An Autonomous Unmanned Aerial Vehicle-based Imagery System Development and Remote Sensing Images Classification for Agricultural Applications written by Yiding Han and published by . This book was released on 2009 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work concentrates on the topic of remote sensing using a multispectral imaging system for water management and agriculture applications. The platform, which is a light-weight inexpensive runway-free unmanned aerial vehicle (UAV), namely, AggieAir, is presented initially. A major portion of this work focuses on the development of a lightweight multispectral imager payload for the AggieAir platform, called GhostFoto. The imager is band-reconfigurable, covering both visual red, green, and blue (RGB) and near infrared (NIR) spectrum, and interfaced with UAV on-board computer. The development of the image processing techniques, which are based on the collected multispectral aerial images, is also presented in this work. One application is to perform fully autonomous river tracking for applications such as river water management. Simulation based on aerial multispectral images is done to demonstrate the feasibility of the developed algorithm. Other effort is made to create a systematic method to generate normalized difference vegetation index (NDVI) using the airborne imagery. The GhostFoto multispectral imaging system based on AggieAir architecture is proven to be an innovative and useful tool.
Book Synopsis An Evaluation of Unmanned Aerial System Multispectral and Thermal Infrared Data as Information for Agricultural Crop and Irrigation Management by : Mitchell S. Maguire
Download or read book An Evaluation of Unmanned Aerial System Multispectral and Thermal Infrared Data as Information for Agricultural Crop and Irrigation Management written by Mitchell S. Maguire and published by . This book was released on 2018 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial irrigation management has been steadily advancing over the last several years. A current issue with managing irrigation spatially on sub-field scale is the inability to readily collect the spatial field data necessary to properly manage irrigation. Multispectral and thermal infrared imagery used in informing irrigation management decisions was previously collected by satellite and manned aircraft remote sensing platforms. These remote sensing platforms pose issues concerning economic feasibility, revisit intervals, and weather factors that inhibit the collection of data. Recent developments in unmanned aerial systems, which provide an additional means of collecting multispectral and thermal infrared data, have the potential to provide supplemental data during periods of missing satellite data or to completely replace satellite and manned aircraft remote sensing platforms. As unmanned aerial system remote sensing platforms are a relatively new technology, there are uncertainties regarding how these systems compare to previous and more well-known remote sensing platforms. Some of these uncertainties include how to properly collect, process, and calibrate data acquired by these systems so that the end products are accurate and can by used in scientific applications. This work evaluated two different unmanned aerial systems with integrated multispectral and thermal infrared cameras to determine the best methods of collecting, processing, and calibrating data. Three different multispectral image calibration methods were evaluated and compared against Landsat satellite reflectance products and ground-based reflectance tarps. The thermal infrared image calibration consisted of correcting for emissivity and atmospheric effects, and was compared to in-field infrared thermometers. Relationships for estimating maize leaf area index, crop height, and fraction of vegetation cover were redefined and evaluated based on various vegetation indices derived from the unmanned aerial system calibrated multispectral imagery. This work also addressed some of the challenges and obstacles related to deploying unmanned aerial systems for remote sensing in agricultural applications.
Book Synopsis Recent Advances in Remote Sensing for Crop Growth Monitoring by : Tao Cheng
Download or read book Recent Advances in Remote Sensing for Crop Growth Monitoring written by Tao Cheng and published by MDPI. This book was released on 2018-09-28 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Recent Advances in Remote Sensing for Crop Growth Monitoring" that was published in Remote Sensing
Book Synopsis Sensing Approaches for Precision Agriculture by : Ruth Kerry
Download or read book Sensing Approaches for Precision Agriculture written by Ruth Kerry and published by Springer Nature. This book was released on 2021-11-23 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensing Approaches for Precision Agriculture aims to bring together the ‘state of the art’ of the most popular sensing techniques and the current state of research on the application of sensors in Precision Agriculture (PA). Sensing is of great value in PA because it provides cheap and immediate data for management. This book gives a broad overview of sensing in PA and a coherent introduction for new professionals and research scientists. Readers are introduced to the potential applications of a range of different sensors, how they should be used properly and their limitations for use in PA. Chapters on specific topics and case studies provide depth and enable implementation of the methods by users. A general introduction about sensing techniques in PA is followed by Chapters 2–9 on the most important specific techniques in sensing and Chapters 10–13 include mini-case studies, each showing cutting-edge applications for different sensing methods. Finally, there is an Epilogue on how we expect sensors and analysis to develop.
