GEOMETRIC AND REFLECTANCE SIGNATURE CHARACTERIZATION OF COMPLEX CANOPIES USING HYPERSPECTRAL STEREOSCOPIC IMAGES FROM UAV AND TERRESTRIAL PLATFORMS

Light-weight hyperspectral frame cameras represent novel developments in remote sensing technology. With frame camera technology, when capturing images with stereoscopic overlaps, it is possible to derive 3D hyperspectral reflectance information and 3D geometric data of targets of interest, which enables detailed geometric and radiometric characterization of the object. These technologies are expected to provide efficient tools in various environmental remote sensing applications, such as canopy classification, canopy stress analysis, precision agriculture, and urban material classification. Furthermore, these data sets enable advanced quantitative, physical based retrieval of biophysical and biochemical parameters by model inversion technologies. Objective of this investigation was to study the aspects of capturing hyperspectral reflectance data from unmanned airborne vehicle (UAV) and terrestrial platform with novel hyperspectral frame cameras in complex, forested environment.

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Multispectral Sensor Calibration and Characterization for sUAS Remote Sensing

Sensors ◽

10.3390/s19204453 ◽

2019 ◽

Vol 19 (20) ◽

pp. 4453 ◽

Cited By ~ 7

Author(s):

Mamaghani ◽

Salvaggio

Keyword(s):

Remote Sensing ◽

Near Infrared ◽

Laboratory Method ◽

Sensor Calibration ◽

Radiometric Calibration ◽

End User ◽

Sensing Applications ◽

A Value ◽

Remote Sensing Applications

This paper focuses on the calibration of multispectral sensors typically used for remote sensing. These systems are often provided with "factory" radiometric calibration and vignette correction parameters. These parameters, which are assumed to be accurate when the sensor is new, may change as the camera is utilized in real-world conditions. As a result, regular calibration and characterization of any sensor should be conducted. An end-user laboratory method for computing both the vignette correction and radiometric calibration function is discussed in this paper. As an exemplar, this method for radiance computation is compared to the method provided by MicaSense for their RedEdge series of sensors. The proposed method and the method provided by MicaSense for radiance computation are applied to a variety of images captured in the laboratory using a traceable source. In addition, a complete error propagation is conducted to quantify the error produced when images are converted from digital counts to radiance. The proposed methodology was shown to produce lower errors in radiance imagery. The average percent error in radiance was −10.98%, −0.43%, 3.59%, 32.81% and −17.08% using the MicaSense provided method and their "factory" parameters, while the proposed method produced errors of 3.44%, 2.93%, 2.93%, 3.70% and 0.72% for the blue, green, red, near infrared and red edge bands, respectively. To further quantify the error in terms commonly used in remote sensing applications, the error in radiance was propagated to a reflectance error and additionally used to compute errors in two widely used parameters for assessing vegetation health, NDVI and NDRE. For the NDVI example, the ground reference was computed to be 0.899 ± 0.006, while the provided MicaSense method produced a value of 0.876 ± 0.005 and the proposed method produced a value of 0.897 ± 0.007. For NDRE, the ground reference was 0.455 ± 0.028, MicaSense method produced 0.239 ± 0.026 and the proposed method produced 0.435 ± 0.038.

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THE APPLICATION OF REMOTE SENSING IN PRECISION AGRICULTURE

Vestnik of the Russian agricultural science ◽

10.30850/vrsn/2018/5/10-16 ◽

1970 ◽

pp. 10-16

Author(s):

S. Yu. Blokhina

Keyword(s):

Remote Sensing ◽

Data Storage ◽

Spatial Resolution ◽

Precision Agriculture ◽

Near Infrared ◽

Crop Yields ◽

Temporal Frequency ◽

Organic Matter Content ◽

Sensing Applications ◽

Remote Sensing Applications

The paper provides an overview of foreign literature on the remote sensing applications in precision agriculture. Remote sensing applications in precision agriculture began with sensors for soil organic matter content, and have quickly advanced to include hand held sensors to tractor or aerial or satellite mounted sensors. Wavelengths of electromagnetic radiation initially focused on a few key visible or near infrared bands, and nowadays electromagnetic wavelengths in use range from the ultraviolet to microwave portions of the spectrum. Spectral bandwidth has decreased dramatically with the advent of hyperspectral remote sensing, allowing improved analysis of crop stress, crop biophysical or biochemical characteristics and specific compounds. A variety of spectral indices have been widely implemented within various precision agriculture applications, rather than a focus on only normalized difference vegetation indices. Spatial resolution and temporal frequency of remote sensing imagery has increased significantly, allowing evaluation of soil and crop properties at fine spatial resolution at the expense of increased data storage and processing requirements. At present there is considerable interest in collecting remote sensing for operational management of soil and crop yields, as well as control over the spread of pests and weeds practically in real time.

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X-ray diffraction and infrared characterization of Oxisols from central and southeastern Brazil

Clay Minerals ◽

10.1180/claymin.2008.043.4.03 ◽

2008 ◽

Vol 43 (4) ◽

pp. 549-560 ◽

Cited By ~ 6

Author(s):

R. P. Nitzsche ◽

J. B. Percival ◽

J. K. Torrance ◽

J. A. R. Stirling ◽

J. T. Bowen

Keyword(s):

Remote Sensing ◽

Near Infrared ◽

Microwave Remote Sensing ◽

Short Wave ◽

Southeastern Brazil ◽

X Ray Diffraction ◽

X Ray ◽

Sensing Applications ◽

Remote Sensing Applications

AbstractEleven Oxisols with high clay contents, 2.6–59.7 wt.% Fe2O3, and containing hematite, goethite, magnetite and maghemite, from São Paulo, Minas Gerais and Goiás, Brazil, were studied for the purpose of microwave remote sensing applications in the 0.3 to 300 GHz range. Of special interest are: the pseudosand effect caused by Fe-oxide cementation of clusters of soil particles; the mineralogy; and whether the soil magnetic susceptibility affected by ferromagnetic magnetite and maghemite interferes with microwave propagation. Quantitative mineralogical analyses were conducted using X-ray diffraction with Rietveld refinement. Visible, near infrared and short wave infrared spectroscopic analyses were used to characterize the samples qualitatively for comparison with published spectral radiometry results. Quartz (3–88%), hematite (2–36%) and gibbsite (1–40%) occurred in all soils, whereas kaolinite (2–70%) and anatase (2–13%) occurred in nine samples. Ilmenite (1–8%) was found in eight soils and goethite (2–39%) in seven. Of the ferromagnetic minerals, maghemite occurred in seven soils (1–13%) and three contained magnetite (<2%). These results will be applied to the interpretation of the effect of Fe oxides, particularly the ferromagnetic oxides, on microwave interaction with high-Fe soils, with ultimate application to the monitoring of soil water content by microwave remote sensing.

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Synthesis, growth and characterization of NLO single crystals for Remote Sensing applications

Journal of Physics Conference Series ◽

10.1088/1742-6596/1770/1/012095 ◽

2021 ◽

Vol 1770 (1) ◽

pp. 012095

Author(s):

P Malliga ◽

M Manjula ◽

A Joseph Arul Pragasam ◽

V Dharshan ◽

V Deepika

Keyword(s):

Remote Sensing ◽

Single Crystals ◽

Sensing Applications ◽

Remote Sensing Applications

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REAL-TIME AND POST-PROCESSED GEOREFERENCING FOR HYPERPSPECTRAL DRONE REMOTE SENSING

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-789-2018 ◽

2018 ◽

Vol XLII-2 ◽

pp. 789-795 ◽

Cited By ~ 3

Author(s):

R. A. Oliveira ◽

E. Khoramshahi ◽

J. Suomalainen ◽

T. Hakala ◽

N. Viljanen ◽

...

Keyword(s):

Remote Sensing ◽

Real Time ◽

Precision Agriculture ◽

Low Cost ◽

Remote Sensing Data ◽

Target Object ◽

Post Processing ◽

The Real ◽

Sensing Applications ◽

Remote Sensing Applications

The use of drones and photogrammetric technologies are increasing rapidly in different applications. Currently, drone processing workflow is in most cases based on sequential image acquisition and post-processing, but there are great interests towards real-time solutions. Fast and reliable real-time drone data processing can benefit, for instance, environmental monitoring tasks in precision agriculture and in forest. Recent developments in miniaturized and low-cost inertial measurement systems and GNSS sensors, and Real-time kinematic (RTK) position data are offering new perspectives for the comprehensive remote sensing applications. The combination of these sensors and light-weight and low-cost multi- or hyperspectral frame sensors in drones provides the opportunity of creating near real-time or real-time remote sensing data of target object. We have developed a system with direct georeferencing onboard drone to be used combined with hyperspectral frame cameras in real-time remote sensing applications. The objective of this study is to evaluate the real-time georeferencing comparing with post-processing solutions. Experimental data sets were captured in agricultural and forested test sites using the system. The accuracy of onboard georeferencing data were better than 0.5&thinsp;m. The results showed that the real-time remote sensing is promising and feasible in both test sites.

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