Near-infrared imagery from unmanned aerial systems and satellites can be used to specify fertilizer application rates in tree crops

2011 ◽  
Vol 37 (4) ◽  
pp. 376-386 ◽  
Author(s):  
L. Felderhof ◽  
D. Gillieson
Keyword(s):  
Near Infrared ◽  
Fertilizer Application ◽  
Unmanned Aerial Systems ◽  
Infrared Imagery ◽  
Tree Crops ◽  
Application Rates ◽  
Aerial Systems

scholarly journals Cavity Ring-Down Methane Sensor for Small Unmanned Aerial Systems

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 454 ◽  
Author(s):  
Benjamin Martinez ◽  
Thomas W. Miller ◽  
Azer P. Yalin
Keyword(s):  
Near Infrared ◽  
High Sensitivity ◽  
Unmanned Aerial Systems ◽  
Test Results ◽  
Methane Sensor ◽  
Open Path ◽  
Low Mass ◽  
Aerial Systems ◽  
High Finesse ◽  
Cavity Ring Down

We present the development, integration, and testing of an open-path cavity ring-down spectroscopy (CRDS) methane sensor for deployment on small unmanned aerial systems (sUAS). The open-path configuration used here (without pump or flow-cell) enables a low mass (4 kg) and low power (12 W) instrument that can be readily integrated to sUAS, defined here as having all-up mass of <25 kg. The instrument uses a compact telecom style laser at 1651 nm (near-infrared) and a linear 2-mirror high-finesse cavity. We show test results of flying the sensor on a DJI Matrice 600 hexacopter sUAS. The high sensitivity of the CRDS method allows sensitive methane detection with a precision of ~10–30 ppb demonstrated for actual flight conditions. A controlled release setup, where known mass flows are delivered, was used to simulate point-source methane emissions. Examples of methane plume detection from flight tests suggest that isolated plumes from sources with a mass flow as low as ~0.005 g/s can be detected. The sUAS sensor should have utility for emissions monitoring and quantification from natural gas infrastructure. To the best of our knowledge, it is also the first CRDS sensor directly deployed onboard an sUAS.

scholarly journals Illumination Geometry and Flying Height Influence Surface Reflectance and NDVI Derived from Multispectral UAS Imagery

Drones ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 55 ◽  
Author(s):  
Daniel Stow ◽  
Caroline J. Nichol ◽  
Tom Wade ◽  
Jakob J. Assmann ◽  
Gillian Simpson ◽  
...  
Keyword(s):  
Near Infrared ◽  
Vegetation Indices ◽  
Flying Height ◽  
Unmanned Aerial Systems ◽  
Radiometric Calibration ◽  
Very High Spatial Resolution ◽  
Vegetation Surveys ◽  
Solar Noon ◽  
Aerial Systems ◽  
Reflectance Measurements

Small unmanned aerial systems (UAS) have allowed the mapping of vegetation at very high spatial resolution, but a lack of standardisation has led to uncertainties regarding data quality. For reflectance measurements and vegetation indices (Vis) to be comparable between sites and over time, careful flight planning and robust radiometric calibration procedures are required. Two sources of uncertainty that have received little attention until recently are illumination geometry and the effect of flying height. This study developed methods to quantify and visualise these effects in imagery from the Parrot Sequoia, a UAV-mounted multispectral sensor. Change in illumination geometry over one day (14 May 2018) had visible effects on both individual images and orthomosaics. Average near-infrared (NIR) reflectance and NDVI in regions of interest were slightly lower around solar noon, and the contrast between shadowed and well-illuminated areas increased over the day in all multispectral bands. Per-pixel differences in NDVI maps were spatially variable, and much larger than average differences in some areas. Results relating to flying height were inconclusive, though small increases in NIR reflectance with height were observed over a black sailcloth tarp. These results underline the need to consider illumination geometry when carrying out UAS vegetation surveys.

scholarly journals Technical Configurations of a Helicopter Type Unmanned Aerial System for Pesticide and Fertilizer Application

2021 ◽  
Vol 15 (3) ◽  
pp. 63-72
Author(s):  
L. A. Marchenko ◽  
M. V. Myzin ◽  
I. V. Kuznetsov ◽  
A. Yu. Spiridonov
Keyword(s):  
Farming System ◽  
Fertilizer Application ◽  
Precision Farming ◽  
Unmanned Aerial Systems ◽  
Control Panel ◽  
Limited Area ◽  
Unmanned Aerial System ◽  
Agricultural Field ◽  
Systems Research ◽  
Aerial Systems

It was noted that when forming the configurations of an unmanned aerial system for pesticide and fertilizer application, it is necessary to take into account the interdependence of unmanned and ground-based aerial systems. (Research purpose) To develop the configurations of an unmanned aerial system for pesticide and fertilizer application. (Materials and methods) The authors used Methodological recommendations on the use of chemicals in the precision farming system (VIM), regulatory and technical documentation for unmanned aerial systems. (Results and discussion) The authors developed a flowchart of the algorithm for forming the configurations of a helicopter type unmanned aerial system for fertilizer and pesticide application, including the formation of both unmanned and ground-based aerial systems. The authors calculated the aerodynamic characteristics of an unmanned coaxial rotor aircraft with a take-off weight of 280 kilograms and a payload of 100 kilograms. A modular-designed sprayer was offered. The authors substantiated the structure of the ground-based aerial complex in the form of a mobile transporter-tanker with a basic transport platform, lifting and transporting and refueling modules, and a universal ground control panel for the pilot-operator. (Conclusions) The authors formed reasonable configurations of a helicopter type unmanned aerial system for pesticide and fertilizer differentiated application in the precision farming system. Aircraft performance limitations were identified for the application of fertilizers and pesticides by a helicopter type unmanned aerial vehicle: the payload of at least 100 kilograms, the operating altitude of 1.0-1.5 meters when bypassing the agricultural field topography and avoiding possible obstacles, the operating airspeed kept below 60 kilometers per hour, automatic take-off and landing on a limited area, autoflight at the speed of 60 kilometers per hour at a one meter altitude in a tacking mode. It was showed that the static ceiling margin, without taking the earth influence into account, with a 280-kilogram flight mass, is 1300 meters, which allows flying in mountainous areas, for example, for the treatment of vineyards with pesticides.

Soil Moisture Retrievals from Unmanned Aerial Systems (UAS)

2020 ◽  
Author(s):  
ruodan zhuang ◽  
Salvatore Manfreda ◽  
Yijian Zeng ◽  
Zhongbo Su ◽  
Nunzio Romano ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Near Infrared ◽  
Spatial Scales ◽  
Standard Procedure ◽  
Thermal Inertia ◽  
Unmanned Aerial Systems ◽  
Natural Ecosystems ◽  
Resources Management ◽  
Cropland Area ◽  
Aerial Systems

&lt;p&gt;Quantification of the spatial and temporal behavior of soil moisture is vital for understanding water availability in agriculture, ecosystems research, river basin hydrology and water resources management. Unmanned Aerial Systems (UAS) offer a great potential in monitoring this parameter at sub-meter level and at relatively low cost. The standardization of operational procedures for soil moisture monitoring with UAS can be beneficial to understanding and quantify the quality of retrieved soil moisture (e.g., from different platforms and sensors).&lt;/p&gt;&lt;p&gt;In this study, soil moisture retrieved from UAS using different retrieval algorithms was compared to collocated ground measurements. The thermal inertia model builds upon the dependence of the thermal diffusion on soil moisture. The soil thermal inertia is quantified by processing visible and near-infrared (VIS-NIR) and thermal infrared (TIR) images, acquired at two different times of a day. The temperature&amp;#8211;vegetation trapezoidal model is also used to map soil moisture over vegetated pixels. This trapezoidal model depicts the soil moisture dependence of the surface energy balance. The comparison of the two algorithms helps define a preliminary standard procedure for retrieving soil moisture with UAS.&lt;/p&gt;&lt;p&gt;As a case study, a typical cropland area with olive orchard, cherry and walnut trees in the region of Monteforte Cilento (Italy, Salerno) is used, where optical and thermal images and in situ data were simultaneously acquired. In the Alento observatory, long-term studies on vadose zone hydrology have been conducting across a range of spatial scales. Our findings provide an important contribution towards improving our knowledge on evaluating the ability of UAS to map soil moisture, in support of sustainable natural resources management and climate change studies.&lt;/p&gt;&lt;p&gt;This research is a part of EU COST-Action &amp;#8220;HARMONIOUS: Harmonization of UAS techniques for agricultural and natural ecosystems monitoring&amp;#8221;.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords:&lt;/strong&gt; soil moisture, Unmanned Aerial Systems, thermal inertia, HARMONIOUS&lt;/p&gt;

scholarly journals Nitrogen Management Based on Visible/Near Infrared Spectroscopy in Pear Orchards

2021 ◽  
Vol 13 (5) ◽  
pp. 927
Author(s):  
Jie Wang ◽  
Xiaojun Shi ◽  
Yangchun Xu ◽  
Caixia Dong
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Fertilizer Application ◽  
First Year ◽  
N Application ◽  
N Concentration ◽  
Application Rates ◽  
Leaf N Concentration ◽  
Leaf N

The timely estimation of nitrogen (N) requirements is essential for managing N fertilizer application in pear orchards. Visible/near infrared spectroscopy is a non-destructive and effective technique for real-time assessment of leaf N concentration, but its utility for decisions about fertilizer application in the pear orchards remains to be determined. In this study, we used leaf spectroscopy to determine leaf N concentration, used this value to calculate the amounts of N required for supplementary fertilization, and then evaluated the effects of the application. Over the two-year study, Cuiguan pear trees were treated with N at the following rates: 0 (N0), 100 (N1), 200 (N2), 300 (N3), and 400 (N4) g N per tree, regarded as five “controlled” N application rates. Another four “regulatory” treatments (Nr1-4) were fertilized as the “controlled” N application rates the first year, then given adjusted N application by topdressing as calculated using the N concentrations inferred from visible/near infrared spectroscopy data the second year. A model (R2 = 0.82) was established the first year to relate leaf spectra and N concentration using a partial least squares regression with full bands (350–2500 nm). The amount of N in the topdressing for the supplemental treatments was determined using the predicted leaf N concentration and the topdressing calculation method adapted from the N balance formula. Results showed that adjusted N applications of the Nr1 and Nr2 increased yield by 26% and 23%, respectively, over the controlled treatments N1 and N2. Although treatments Nr3 and Nr4 did not increase yield significantly over N3 and N4, the partial factor productivity of nitrogen in Nr4 was higher than the N4. The transverse diameter of fruit from Nr1 trees was significantly higher than from N1 trees, while the longitudinal diameter of fruit from Nr1, Nr2, and Nr3 trees was significantly higher than from N1, N2 and N3 trees, suggesting that fruit longitudinal growth and single-fruit weight is stimulated by adjusted N applications. However, the soluble solids in fruit from trees receiving adjusted N were not significantly greater than in fruit from non-supplemented trees. In conclusion, our results illustrate that regulatory N management contributes to fruit yield and quality especially in the nitrogen deficiency condition and improves the nitrogen use efficiency in nitrogen surplus. The N prediction model established using the nondestructive visible/near infrared spectroscopy is convenient and economical.

scholarly journals Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3335 ◽  
Author(s):  
Sigfredo Fuentes ◽  
Eden Jane Tongson ◽  
Roberta De Bei ◽  
Claudia Gonzalez Viejo ◽  
Renata Ristic ◽  
...  
Keyword(s):  
Machine Learning ◽  
Pattern Recognition ◽  
Management Practices ◽  
Near Infrared ◽  
Detection System ◽  
Screening Tools ◽  
Unmanned Aerial Systems ◽  
Non Invasive ◽  
Aerial Systems ◽  
Non Destructive

Bushfires are becoming more frequent and intensive due to changing climate. Those that occur close to vineyards can cause smoke contamination of grapevines and grapes, which can affect wines, producing smoke-taint. At present, there are no available practical in-field tools available for detection of smoke contamination or taint in berries. This research proposes a non-invasive/in-field detection system for smoke contamination in grapevine canopies based on predictable changes in stomatal conductance patterns based on infrared thermal image analysis and machine learning modeling based on pattern recognition. A second model was also proposed to quantify levels of smoke-taint related compounds as targets in berries and wines using near-infrared spectroscopy (NIR) as inputs for machine learning fitting modeling. Results showed that the pattern recognition model to detect smoke contamination from canopies had 96% accuracy. The second model to predict smoke taint compounds in berries and wine fit the NIR data with a correlation coefficient (R) of 0.97 and with no indication of overfitting. These methods can offer grape growers quick, affordable, accurate, non-destructive in-field screening tools to assist in vineyard management practices to minimize smoke taint in wines with in-field applications using smartphones and unmanned aerial systems (UAS).

scholarly journals 3D Calibration Test-Field for Digital Cameras Mounted on Unmanned Aerial Systems (UAS)

2018 ◽  
Vol 10 (12) ◽  
pp. 2017 ◽  
Author(s):  
Valeria-Ersilia Oniga ◽  
Norbert Pfeifer ◽  
Ana-Maria Loghin
Keyword(s):  
Near Infrared ◽  
Low Cost ◽  
Digital Camera ◽  
Field Measurements ◽  
Unmanned Aerial Systems ◽  
Test Field ◽  
Digital Cameras ◽  
Self Calibration ◽  
Technological Developments ◽  
Aerial Systems

Due to the large number of technological developments in recent years, UAS systems are now used for monitoring purposes and in projects with high precision demand, such as 3D model-based creation of dams, reservoirs, historical monuments etc. These unmanned systems are usually equipped with an automatic pilot device and a digital camera (photo/video, multispectral, Near Infrared etc.), of which the lens has distortions; but this can be determined in a calibration process. Currently, a method of “self-calibration” is used for the calibration of the digital cameras mounted on UASs, but, by using the method of calibration based on a 3D calibration object, the accuracy is improved in comparison with other methods. Thus, this paper has the objective of establishing a 3D calibration field for the digital cameras mounted on UASs in terms of accuracy and robustness, being the largest reported publication to date. In order to test the proposed calibration field, a digital camera mounted on a low-cost UAS was calibrated at three different heights: 23 m, 28 m, and 35 m, using two configurations for image acquisition. Then, a comparison was made between the residuals obtained for a number of 100 Check Points (CPs) using self-calibration and test-field calibration, while the number of Ground Control Points (GCPs) variedand the heights were interchanged. Additionally, the parameters where tested on an oblique flight done 2 years before calibration, in manual mode at a medium altitude of 28 m height. For all tests done in the case of the double grid nadiral flight, the parameters calculated with the proposed 3D field improved the results by more than 50% when using the optimum and a large number of GCPs, and in all analyzed cases with 75% to 95% when using a minimum of 3 GCP. In this context, it is necessary to conduct accurate calibration in order to increase the accuracy of the UAS projects, and also to reduce field measurements.

scholarly journals Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review

2019 ◽  
Vol 11 (6) ◽  
pp. 676 ◽  
Author(s):  
Theodora Angelopoulou ◽  
Nikolaos Tziolas ◽  
Athanasios Balafoutis ◽  
George Zalidis ◽  
Dionysis Bochtis
Keyword(s):  
Remote Sensing ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Near Infrared ◽  
Cost Effective ◽  
Machine Learning Techniques ◽  
Unmanned Aerial Systems ◽  
Advantages And Disadvantages ◽  
Remote Sensing Techniques ◽  
Aerial Systems

Towards the need for sustainable development, remote sensing (RS) techniques in the Visible-Near Infrared–Shortwave Infrared (VNIR–SWIR, 400–2500 nm) region could assist in a more direct, cost-effective and rapid manner to estimate important indicators for soil monitoring purposes. Soil reflectance spectroscopy has been applied in various domains apart from laboratory conditions, e.g., sensors mounted on satellites, aircrafts and Unmanned Aerial Systems. The aim of this review is to illustrate the research made for soil organic carbon estimation, with the use of RS techniques, reporting the methodology and results of each study. It also aims to provide a comprehensive introduction in soil spectroscopy for those who are less conversant with the subject. In total, 28 journal articles were selected and further analysed. It was observed that prediction accuracy reduces from Unmanned Aerial Systems (UASs) to satellite platforms, though advances in machine learning techniques could further assist in the generation of better calibration models. There are some challenges concerning atmospheric, radiometric and geometric corrections, vegetation cover, soil moisture and roughness that still need to be addressed. The advantages and disadvantages of each approach are highlighted and future considerations are also discussed at the end.

LIGHTER-THAN-AIR (LTA) UNMANNED AERIAL SYSTEM (UAS) CARRIER CONCEPT FOR SURVAILLANCE AND DISASTER MANAGEMENT

2019 ◽  
Vol 3 ◽  
pp. 1255
Author(s):  
Ahmad Salahuddin Mohd Harithuddin ◽  
Mohd Fazri Sedan ◽  
Syaril Azrad Md Ali ◽  
Shattri Mansor ◽  
Hamid Reza Jifroudi ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Disaster Management ◽  
Unmanned Aerial Systems ◽  
Unmanned Aerial System ◽  
Border Control ◽  
Aerial Vehicles ◽  
Operational Safety ◽  
In Situ Methods ◽  
Aerial Systems

Unmanned aerial systems (UAS) has many advantages in the fields of SURVAILLANCE and disaster management compared to space-borne observation, manned missions and in situ methods. The reasons include cost effectiveness, operational safety, and mission efficiency. This has in turn underlined the importance of UAS technology and highlighted a growing need in a more robust and efficient unmanned aerial vehicles to serve specific needs in SURVAILLANCE and disaster management. This paper first gives an overview on the framework for SURVAILLANCE particularly in applications of border control and disaster management and lists several phases of SURVAILLANCE and service descriptions. Based on this overview and SURVAILLANCE phases descriptions, we show the areas and services in which UAS can have significant advantage over traditional methods.

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