scholarly journals Evaluation of Incident Light Sensors on Unmanned Aircraft for Calculation of Spectral Reflectance

2019 ◽  
Vol 11 (22) ◽  
pp. 2622
Author(s):  
E. Raymond Hunt ◽  
Alan J. Stern
Keyword(s):  
Near Infrared ◽  
Incident Light ◽  
Accurate Determination ◽  
Ground Level ◽  
Unmanned Aircraft ◽  
Landsat 8 ◽  
The Sun ◽  
Area Index ◽  
Flight Direction ◽  
Aircraft System

Including incident light sensors (ILS) with multispectral sensors is an important development for agricultural remote sensing because spectral reflectances are necessary for accurate determination of plant biophysical variables such as leaf area index and leaf chlorophyll content. Effects of different aircraft flight conditions on accuracy of surface reflectances retrieved using an ILS are not known. The objectives of this study were to assess the effects of ILS orientation with respect to sun and aircraft altitude. A Tetracam Miniature Multiple Camera Array (Mini-MCA) was mounted on a fixed-wing unmanned aircraft system (UAS) with the ILS mounted on top of the aircraft’s fuselage. On two dates the aircraft flew over six 50-ha agricultural fields with center-pivot irrigation at three different altitudes (450, 650 and 1800 m above ground level (AGL)). Ground reflectances were estimated using atmospherically corrected Landsat 8 Operational Land Imager data acquired at or near the time of the aircraft overflights. Because the aircraft had a positive pitch during flight, the ILS pointed opposite to the flight direction. The first date had flight lines closely oriented towards and away from the sun. The second date had flight lines oriented perpendicularly to the solar azimuth. On the first date, red and near-infrared (NIR) reflectances were significantly higher when the ILS was oriented away from the sun, whereas ILS orientation had little effect on the second date. For both dates, red and near-infrared reflectances were significantly greater at 450 m compared to 1800 m. Both the effects of ILS orientation and flight altitude are correctable during image processing because the physical basis is well known.

Structural mapping of rock walls imaged with a LiDAR mounted on an unmanned aircraft system

2019 ◽  
Vol 7 (1) ◽  
pp. 21-38 ◽  
Author(s):  
Connor McAnuff ◽  
Claire Samson ◽  
Dave Melanson ◽  
Christopher Polowick ◽  
Erin Bethell
Keyword(s):  
Point Cloud ◽  
Ground Level ◽  
Unmanned Aircraft ◽  
Reconstruction Method ◽  
Angle Of Incidence ◽  
Fracture Density ◽  
Mining Operations ◽  
Structural Mapping ◽  
Geological Information ◽  
Aircraft System

Structural mapping of rock walls to determine fracture orientation provides critical geological information in support of mining operations. A helicopter-style UAS (rotor diameter 2 m; take-off mass 35 kg; payload mass 11 kg) instrumented with a high-resolution LiDAR imaged a 75 m long and 10–15 m high series of four adjacent rock walls at the Canadian Wollastonite mine. A point cloud with a density of 484 point/m2 acquired at an angle of incidence of ∼41.7° from a flight altitude of 41.7 m above ground level was selected for structural mapping. The point cloud was first meshed using the Poisson surface reconstruction method and then remeshed to achieve an even element size distribution. Visualization of the remeshed Poisson mesh using a 360° hue–saturation–lightness colour wheel highlighted areas of higher fracture density, whereas visualization using a 180° colour wheel accentuated sliver-like geological features. Two joint sets were identified at 156/82 and 241/86 (strike/dip in degrees). A total of 18 virtual strike measurements and 13 virtual dip measurements were within 10% of manual compass measurements. This study demonstrated that the task of structural mapping of large rock walls can be automated by processing 3D images acquired with a LiDAR mounted on a UAS.

Spectral Reflectance Estimation of UAS Multispectral Imagery Using Satellite Cross-Calibration Method

2021 ◽  
Vol 87 (10) ◽  
pp. 735-746
Author(s):  
Saket Gowravaram ◽  
Haiyang Chao ◽  
Andrew Molthan ◽  
Tiebiao Zhao ◽  
Pengzhi Tian ◽  
...  
Keyword(s):  
Spectral Reflectance ◽  
Near Infrared ◽  
Low Cost ◽  
Calibration Method ◽  
Unmanned Aircraft ◽  
Landsat 8 ◽  
Multispectral Imagery ◽  
Data Set ◽  
Cross Calibration ◽  
Mean Square Errors

This paper introduces a satellite-based cross-calibration (SCC) method for spectral reflectance estimation of unmanned aircraft system (UAS) multispectral imagery. The SCC method provides a low-cost and feasible solution to convert high-resolution UAS images in digital numbers (DN) to reflectance when satellite data is available. The proposed method is evaluated using a multispectral data set, including orthorectified KHawk UAS DN imagery and Landsat 8 Operational Land Imager Level-2 surface reflectance (SR) data over a forest/grassland area. The estimated UAS reflectance images are compared with the National Ecological Observatory Network's imaging spectrometer (NIS) SR data for validation. The UAS reflectance showed high similarities with the NIS data for the near-infrared and red bands with Pearson's r values being 97 and 95.74, and root-mean-square errors being 0.0239 and 0.0096 over a 32-subplot hayfield.

scholarly journals Comparison of CFD Simulation to UAS Measurements for Wind Flows in Complex Terrain: Application to the WINSENT Test Site

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1992 ◽  
Author(s):  
Asmae El Bahlouli ◽  
Alexander Rautenberg ◽  
Martin Schön ◽  
Kjell zum Berge ◽  
Jens Bange ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Cfd Simulation ◽  
Test Site ◽  
Unmanned Aircraft ◽  
Navier Stokes ◽  
Area Index ◽  
Flow Features ◽  
High Turbulence ◽  
Computational Fluid Dynamics Cfd ◽  
Aircraft System

This investigation presents a modelling strategy for wind-energy studies in complex terrains using computational fluid dynamics (CFD). A model, based on an unsteady Reynolds Averaged Navier-Stokes (URANS) approach with a modified version of the standard k-ε model, is applied. A validation study based on the Leipzig experiment shows the ability of the model to simulate atmospheric boundary layer characteristics such as the Coriolis force and shallow boundary layer. By combining the results of the model and a design of experiments (DoE) method, we could determine the degree to which the slope, the leaf area index, and the forest height of an escarpment have an effect on the horizontal velocity, the flow inclination angle, and the turbulent kinetic energy at critical positions. The DoE study shows that the primary contributor at a turbine-relevant height is the slope of the escarpment. In the second step, the method is extended to the WINSENT test site. The model is compared with measurements from an unmanned aircraft system (UAS). We show the potential of the methodology and the satisfactory results of our model in depicting some interesting flow features. The results indicate that the wakes with high turbulence levels downstream of the escarpment are likely to impact the rotor blade of future wind turbines.

Review of Unmanned Aircraft System (UAS)

2013 ◽  
Author(s):  
Suraj G. Gupta ◽  
Mangesh Ghonge ◽  
Pradip M. Jawandhiya
Keyword(s):  
Unmanned Aircraft ◽  
Unmanned Aircraft System ◽  
Aircraft System

scholarly journals An Assessment of Drought Stress in Tea Estates Using Optical and Thermal Remote Sensing

2021 ◽  
Vol 13 (14) ◽  
pp. 2730
Author(s):  
Animesh Chandra Das ◽  
Ryozo Noguchi ◽  
Tofael Ahamed
Keyword(s):  
Remote Sensing ◽  
Drought Stress ◽  
Land Surface ◽  
Climatic Factors ◽  
Standardized Precipitation Index ◽  
Landsat 8 ◽  
Drought Frequency ◽  
Moisture Index ◽  
Area Index ◽  
Drought Period

Drought is one of the detrimental climatic factors that affects the productivity and quality of tea by limiting the growth and development of the plants. The aim of this research was to determine drought stress in tea estates using a remote sensing technique with the standardized precipitation index (SPI). Landsat 8 OLI/TIRS images were processed to measure the land surface temperature (LST) and soil moisture index (SMI). Maps for the normalized difference moisture index (NDMI), normalized difference vegetation index (NDVI), and leaf area index (LAI), as well as yield maps, were developed from Sentinel-2 satellite images. The drought frequency was calculated from the classification of droughts utilizing the SPI. The results of this study show that the drought frequency for the Sylhet station was 38.46% for near-normal, 35.90% for normal, and 25.64% for moderately dry months. In contrast, the Sreemangal station demonstrated frequencies of 28.21%, 41.02%, and 30.77% for near-normal, normal, and moderately dry months, respectively. The correlation coefficients between the SMI and NDMI were 0.84, 0.77, and 0.79 for the drought periods of 2018–2019, 2019–2020 and 2020–2021, respectively, indicating a strong relationship between soil and plant canopy moisture. The results of yield prediction with respect to drought stress in tea estates demonstrate that 61%, 60%, and 60% of estates in the study area had lower yields than the actual yield during the drought period, which accounted for 7.72%, 11.92%, and 12.52% yield losses in 2018, 2019, and 2020, respectively. This research suggests that satellite remote sensing with the SPI could be a valuable tool for land use planners, policy makers, and scientists to measure drought stress in tea estates.

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