scholarly journals Measurement of Cotton Canopy Temperature Using Radiometric Thermal Sensor Mounted on the Unmanned Aerial Vehicle (UAV)

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Anjin Chang ◽  
Jinha Jung ◽  
Murilo M. Maeda ◽  
Juan A. Landivar ◽  
Henrique D. R. Carvalho ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Precision Agriculture ◽  
Water Status ◽  
Canopy Temperature ◽  
Sensor Technology ◽  
Stress Index ◽  
Cotton Field ◽  
Radiometric Calibration ◽  
Great Opportunity ◽  
Aerial Vehicle

Canopy temperature is an important variable directly linked to a plant’s water status. Recent advances in Unmanned Aerial Vehicle (UAV) and sensor technology provides a great opportunity to obtain high-quality imagery for crop monitoring and high-throughput phenotyping (HTP) applications. In this study, a UAV-based thermal system was developed to directly measure canopy temperature, skipping the traditional radiometric calibration process which is time-consuming and complicates data processing. Raw thermal imagery collected over a cotton field was converted to surface temperature using the Software Development Kit (SDK) provided by the sensor company. Canopy temperature map was generated using Structure from Motion (SfM), and Thermal Stress Index (TSI) was calculated for the test site. UAV temperature measurements were compared to ground measurements acquired by net radiometers and thermocouples. Temperature differences between UAV and ground measurements were less than 5%, and UAV measurements proved to be more stable. The proposed UAV system was successful in showing temperature differences between the cotton genotype. In conclusion, the system described in this study could possibly be used to monitor crop water status in a field setting, which should prove helpful for precision agriculture and crop research.

scholarly journals Improved Accuracy of Riparian Zone Mapping Using Near Ground Unmanned Aerial Vehicle and Photogrammetry Method

2021 ◽  
Vol 13 (10) ◽  
pp. 1997
Author(s):  
Joan Grau ◽  
Kang Liang ◽  
Jae Ogilvie ◽  
Paul Arp ◽  
Sheng Li ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Precision Agriculture ◽  
Riparian Zone ◽  
Agricultural Landscapes ◽  
Agricultural Watershed ◽  
Riparian Zones ◽  
Surface Model ◽  
Low Resolution ◽  
Channel Network ◽  
Aerial Vehicle

In agriculture-dominant watersheds, riparian ecosystems provide a wide array of benefits such as reducing soil erosion, filtering chemical compounds, and retaining sediments. Traditionally, the boundaries of riparian zones could be estimated from Digital Elevation Models (DEMs) or field surveys. In this study, we used an Unmanned Aerial Vehicle (UAV) and photogrammetry method to map the boundaries of riparian zones. We first obtained the 3D digital surface model with a UAV. We applied the Vertical Distance to Channel Network (VDTCN) as a classifier to delineate the boundaries of the riparian area in an agricultural watershed. The same method was also used with a low-resolution DEM obtained with traditional photogrammetry and two more LiDAR-derived DEMs, and the results of different methods were compared. Results indicated that higher resolution UAV-derived DEM achieved a high agreement with the field-measured riparian zone. The accuracy achieved (Kappa Coefficient, KC = 63%) with the UAV-derived DEM was comparable with high-resolution LiDAR-derived DEMs and significantly higher than the prediction accuracy based on traditional low-resolution DEMs obtained with high altitude aerial photos (KC = 25%). We also found that the presence of a dense herbaceous layer on the ground could cause errors in riparian zone delineation with VDTCN for both low altitude UAV and LiDAR data. Nevertheless, the study indicated that using the VDTCN as a classifier combined with a UAV-derived DEM is a suitable approach for mapping riparian zones and can be used for precision agriculture and environmental protection over agricultural landscapes.

On-the-go thermal imaging for water status assessment in commercial vineyards

2017 ◽  
Vol 8 (2) ◽  
pp. 520-524
Author(s):  
S. Gutiérrez ◽  
M. P. Diago ◽  
J. Fernández-Novales ◽  
J. Tardaguila
Keyword(s):  
Thermal Imaging ◽  
Water Status ◽  
Canopy Temperature ◽  
Stress Index ◽  
Coefficient Of Determination ◽  
Stem Water Potential ◽  
Water Stress Index ◽  
Status Assessment ◽  
Commercial Vineyard ◽  
East And West

The goal of this work was the assessment of commercial vineyard water status using on-the-go thermal imaging. On-the-go thermal imaging acquisition was conducted with a thermal camera operating at 1.20 m distance from the canopy, mounted on a quad moving at 5 km/h. Canopy temperature, cross water stress index (CWSI) and stomatal conductance index (Ig) were strongly and significantly correlated to stem water potential (Ψstem) in east and west side of the canopy. For CWSI, the values of the coefficient of determination (R2) were 0.88*** and 0.73*** for east and west sides, respectively. As regards the index Ig, its relationships with Ψstem showed R2=0.89*** and R2=0.77*** for east and west sides, respectively. These results are promising and evidence the potential of on-the-go thermal imaging to become a new tool to evaluate the vineyard water status.

scholarly journals Leveraging Very-High Spatial Resolution Hyperspectral and Thermal UAV Imageries for Characterizing Diurnal Indicators of Grapevine Physiology

2020 ◽  
Vol 12 (19) ◽  
pp. 3216 ◽  
Author(s):  
Matthew Maimaitiyiming ◽  
Vasit Sagan ◽  
Paheding Sidike ◽  
Maitiniyazi Maimaitijiang ◽  
Allison J. Miller ◽  
...  
Keyword(s):  
Canopy Temperature ◽  
Crop Productivity ◽  
In Situ Measurements ◽  
Sensor Technology ◽  
Stress Index ◽  
Coefficient Of Determination ◽  
Neural Net ◽  
Water Stress Index ◽  
Very High

Efficient and accurate methods to monitor crop physiological responses help growers better understand crop physiology and improve crop productivity. In recent years, developments in unmanned aerial vehicles (UAV) and sensor technology have enabled image acquisition at very-high spectral, spatial, and temporal resolutions. However, potential applications and limitations of very-high-resolution (VHR) hyperspectral and thermal UAV imaging for characterization of plant diurnal physiology remain largely unknown, due to issues related to shadow and canopy heterogeneity. In this study, we propose a canopy zone-weighting (CZW) method to leverage the potential of VHR (≤9 cm) hyperspectral and thermal UAV imageries in estimating physiological indicators, such as stomatal conductance (Gs) and steady-state fluorescence (Fs). Diurnal flights and concurrent in-situ measurements were conducted during grapevine growing seasons in 2017 and 2018 in a vineyard in Missouri, USA. We used neural net classifier and the Canny edge detection method to extract pure vine canopy from the hyperspectral and thermal images, respectively. Then, the vine canopy was segmented into three canopy zones (sunlit, nadir, and shaded) using K-means clustering based on the canopy shadow fraction and canopy temperature. Common reflectance-based spectral indices, sun-induced chlorophyll fluorescence (SIF), and simplified canopy water stress index (siCWSI) were computed as image retrievals. Using the coefficient of determination (R2) established between the image retrievals from three canopy zones and the in-situ measurements as a weight factor, weighted image retrievals were calculated and their correlation with in-situ measurements was explored. The results showed that the most frequent and the highest correlations were found for Gs and Fs, with CZW-based Photochemical reflectance index (PRI), SIF, and siCWSI (PRICZW, SIFCZW, and siCWSICZW), respectively. When all flights combined for the given field campaign date, PRICZW, SIFCZW, and siCWSICZW significantly improved the relationship with Gs and Fs. The proposed approach takes full advantage of VHR hyperspectral and thermal UAV imageries, and suggests that the CZW method is simple yet effective in estimating Gs and Fs.

scholarly journals Assessment of Multi-Image Unmanned Aerial Vehicle Based High-Throughput Field Phenotyping of Canopy Temperature

2020 ◽  
Vol 11 ◽  
Author(s):  
Gregor Perich ◽  
Andreas Hund ◽  
Jonas Anderegg ◽  
Lukas Roth ◽  
Martin P. Boer ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
High Throughput ◽  
Canopy Temperature ◽  
Field Phenotyping ◽  
Aerial Vehicle

Assessing canopy temperature-based water stress indices for soybeans under subhumid conditions

2020 ◽  
Author(s):  
Angela Morales Santos ◽  
Reinhard Nolz
Keyword(s):  
Water Stress ◽  
Soil Water ◽  
Water Status ◽  
Canopy Temperature ◽  
Irrigation Scheduling ◽  
Stress Index ◽  
Crop Water ◽  
Stress Indices ◽  
Soil Water Status ◽  
Crop Water Stress

<p>Sustainable irrigation water management is expected to accurately meet crop water requirements in order to avoid stress and, consequently, yield reduction, and at the same time avoid losses of water and nutrients due to deep percolation and leaching. Sensors to monitor soil water status and plant water status (in terms of canopy temperature) can help planning irrigation with respect to time and amounts accordingly. The presented study aimed at quantifying and comparing crop water stress of soybeans irrigated by means of different irrigation systems under subhumid conditions.</p><p>The study site was located in Obersiebenbrunn, Lower Austria, about 30 km east of Vienna. The region is characterized by a mean temperature of 10.5°C with increasing trend due to climate change and mean annual precipitation of 550 mm. The investigations covered the vegetation period of soybean in 2018, from planting in April to harvest in September. Measurement data included precipitation, air temperature, relative humidity and wind velocity. The experimental field of 120x120 m<sup>2</sup> has been divided into four sub-areas: a plot of 14x120 m<sup>2</sup> with drip irrigation (DI), 14x120 m<sup>2</sup> without irrigation (NI), 36x120 m<sup>2</sup> with sprinkler irrigation (SI), and 56x120 m<sup>2</sup> irrigated with a hose reel boom with nozzles (BI). A total of 128, 187 and 114 mm of water were applied in three irrigation events in the plots DI, SI and BI, respectively. Soil water content was monitored in 10 cm depth (HydraProbe, Stevens Water) and matric potential was monitored in 20, 40 and 60 cm depth (Watermark, Irrometer). Canopy temperature was measured every 15 minutes using infrared thermometers (IRT; SI-411, Apogee Instruments). The IRTs were installed with an inclination of 45° at 1.8 m height above ground. Canopy temperature-based water stress indices for irrigation scheduling have been successfully applied in arid environments, but their use is limited in humid areas due to low vapor pressure deficit (VPD). To quantify stress in our study, the Crop Water Stress Index (CWSI) was calculated for each plot and compared to the index resulting from the Degrees Above Canopy Threshold (DACT) method. Unlike the CWSI, the DACT method does not consider VPD to provide a stress index nor requires clear sky conditions. The purpose of the comparison was to revise an alternative method to the CWSI that can be applied in a humid environment.</p><p>CWSI behaved similar for the four sub-areas. As expected, CWSI ≥ 1 during dry periods (representing severe stress) and it decreased considerably after precipitation or irrigation (representing no stress). The plot with overall lower stress was BI, producing the highest yield of the four plots. Results show that DACT may be a more suitable index since all it requires is canopy temperature values and has strong relationship with soil water measurements. Nevertheless, attention must be paid when defining canopy temperature thresholds. Further investigations include the development and test of a decision support system for irrigation scheduling combining both, plant-based and soil water status indicators for water use efficiency analysis.</p>

scholarly journals Assessment of Vineyard Water Status by Multispectral and RGB Imagery Obtained from an Unmanned Aerial Vehicle

2021 ◽  
pp. ajev.2021.20063
Author(s):  
Patricia López-García ◽  
Diego S. Intrigliolo ◽  
Miguel A. Moreno ◽  
Alejandro Martínez-Moreno ◽  
Jose F. Ortega ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Water Status ◽  
Aerial Vehicle
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