scholarly journals Caracterización espectral de Quillaja saponaria (Mol.)

2016 ◽  
pp. 65
Author(s):  
T. Acuña ◽  
C. Mattar ◽  
H. J. Hernández
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Spectral Response ◽  
Health State ◽  
High Concentration ◽  
Health States ◽  
Plant Vigour ◽  
Quillaja Saponaria ◽  
Spectral Signatures

<p align="justify">This paper presents a spectral reflectance characterization of the specie Quillaja saponaria (Mol.), endemic tree of Chile and valued by society due to its provision of several ecosystem services that gives to society and also for its high concentration of saponins in cortex widely used in the pharmacological industry. For spectral characterization a foliar spectral signatures protocol was designed which included standardized instrumental and environmental parameters. The spectral response of different individuals was measured to evaluate the spectral behaviour and degree of variability within species in the visible and near infrared ranges (VNIR; 400-990 nm) with two hyperspectral sensors (ASD HH and camera PDF-65-V10E). The resulting spectral signatures obtained with ASD HH showed a variation less than 5% of reflectance in VNIR and lesser than that in the transition zone from red to near infrared (red-edge; 680-730 nm). Additionally, two distinctive spectral features were detected for the specie, the first is related to a fast increase of reflectance in bands 450-480 nm and the second, to a marked decrease in the 920-970 nm range associated with water absorption features. At branch level, these distinctive features are maintained but with a smaller magnitude of reflectance, which could indicate that they are useful characteristic spectral patterns that can eventually be used for monitoring the physical health state of the specie using remote sensing. On the other hand, we used a PDF-65 camera for study the plant vigour from different health states (healthy, ill, died) with spectral vegetation index. The Plant Senescence Reflectance Index detected stress on leaves, and Triangular Vegetation Index allows for a gradually characterization of every state. This work provides the first spectral reference for one of the most important sclerophyll species of Chile.</p>

scholarly journals Enriching Low-Density Terrain Maps from Satellite with Autonomous Robots Data

2021 ◽  
Vol 6 (1) ◽  
pp. 66
Author(s):  
Edmundo Guerra ◽  
Antoni Grau ◽  
Yolanda Bolea ◽  
Rodrigo Munguia
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Autonomous Robots ◽  
High Density ◽  
Low Density ◽  
Soil Features ◽  
Density Maps ◽  
Learning Techniques ◽  
Radar Information

Satellite imagery and remote sensoring have been used for some years in agriculture to create terrain maps for different soil features (humidity, vegetation index, etc.). Multichannel information provides lots of data, but with a big drawback: the low density of information per surface unit; that is, the multi-channeled pixels correspond to a large surface, and a fine characterization of the targeted areas is not possible. In this research, the authors propose the enrichment of such data by the use of autonomous robots that explore and sense the same targeted area of the satellite but yielding a finer detail of terrain, complementing and fusing both information sources. The sensory elements of the autonomous robots are in the visual spectrum as well as in the near-infrared spectrum, together with Lidar and radar information. This enrichment will provide a high-density map of the soil to the final user to improve crops, irrigation, seeding and other agricultural processes. The methodology to fuse data and create high-density maps will be deep learning techniques. The system will be validated in real fields with the use of real sensors to measure the data given by satellites and robots’ sensors.

scholarly journals Measurement Method for Height-Independent Vegetation Indices Based on an Active Light Source

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1830
Author(s):  
Yongqian Ding ◽  
Yizhuo Jiang ◽  
Hongfeng Yu ◽  
Chuanlei Yang ◽  
Xueni Wu ◽  
...  
Keyword(s):  
Light Source ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Spectral Response ◽  
Vegetation Indices ◽  
Application Rate ◽  
Test Point ◽  
Central Wavelength ◽  
Nitrogen Application Rate

A coefficient CW, which was defined as the ratio of NIR (near infrared) to the red reflected spectral response of the spectrometer, with a standard whiteboard as the measuring object, was introduced to establish a method for calculating height-independent vegetation indices (VIs). Two criteria for designing the spectrometer based on an active light source were proposed to keep CW constant. A designed spectrometer, which was equipped with an active light source, adopting 730 and 810 nm as the central wavelength of detection wavebands, was used to test the Normalized Difference Vegetation Index (NDVI) and Ratio Vegetation Index (RVI) in wheat fields with two nitrogen application rate levels (NARLs). Twenty test points were selected in each kind of field. Five measuring heights (65, 75, 85, 95, and 105 cm) were set for each test point. The mean and standard deviation of the coefficient of variation (CV) for NDVI in each test point were 3.85% and 1.39% respectively, the corresponding results for RVI were 2.93% and 1.09%. ANOVA showed the measured VIs possessed a significant ability to discriminate the NARLs and had no obvious correlation with the measurement heights. The experimental results verified the feasibility and validity of the method for measuring height-independent VIs.

scholarly journals Identification of Metal Stresses in Arabidopsis thaliana Using Hyperspectral Reflectance Imaging

2021 ◽  
Vol 12 ◽  
Author(s):  
Anne M. Ruffing ◽  
Stephen M. Anthony ◽  
Lucas M. Strickland ◽  
Ian Lubkin ◽  
Carter R. Dietz
Keyword(s):  
Arabidopsis Thaliana ◽  
Metal Contamination ◽  
Near Infrared ◽  
Spectral Response ◽  
Metal Stress ◽  
Multivariate Curve Resolution ◽  
Hyperspectral Reflectance ◽  
Industrial Accidents ◽  
Spectral Signatures ◽  
Natural Flora

Industrial accidents, such as the Fukushima and Chernobyl disasters, release harmful chemicals into the environment, covering large geographical areas. Natural flora may serve as biological sensors for detecting metal contamination, such as cesium. Spectral detection of plant stresses typically employs a few select wavelengths and often cannot distinguish between different stress phenotypes. In this study, we apply hyperspectral reflectance imaging in the visible and near-infrared along with multivariate curve resolution (MCR) analysis to identify unique spectral signatures of three stresses in Arabidopsis thaliana: salt, copper, and cesium. While all stress conditions result in common stress physiology, hyperspectral reflectance imaging and MCR analysis produced unique spectral signatures that enabled classification of each stress. As the level of potassium was previously shown to affect cesium stress in plants, the response of A. thaliana to cesium stress under variable levels of potassium was also investigated. Increased levels of potassium reduced the spectral response of A. thaliana to cesium and prevented changes to chloroplast cellular organization. While metal stress mechanisms may vary under different environmental conditions, this study demonstrates that hyperspectral reflectance imaging with MCR analysis can distinguish metal stress phenotypes, providing the potential to detect metal contamination across large geographical areas.

scholarly journals Identificación de perturbaciones en el bosque húmedo tropical colombiano usando series temporales de imágenes satelitales Landsat mediante el algoritmo Landtrendr

2019 ◽  
pp. 25
Author(s):  
L. Hurtado ◽  
I. Lizarazo
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Forest Disturbance ◽  
Spectral Response ◽  
Short Wave ◽  
Forest Vegetation ◽  
Landsat Images ◽  
Spectral Bands

<p>Time series analysis of satellite images for detection of deforestation and forest disturbances at specific dates has been a subject of research over the last few years. There are many limitations to identify the exact date of deforestation due mainly to the large volume of data and the criteria required for its correct characterization. A further limitation in the analysis of multispectral time series is the identification of true deforestation considering that forest vegetation may undergo different changes over time. This study analyzes deforestation in a zone within the Colombian Amazon using the Normalized Difference Vegetation Index (NDVI) based on semestral median mosaics generated from Landsat images collected from 2000 to 2017. Several samples representing trends of change over the time series were extracted and classified according to their degree of change and persistence in the series, using four categories: (i) deforestation, (ii) degradation, (iii) forest plantation, and (iv) regeneration. Specific deforestation samples were analyzed in the same way using the soil-adjusted vegetation index (SAVI) to reduce the effect of spectral response variations due to soil reflectance changes. It is concluded that the two indices used, together with the near infrared (NIR) and short-wave infrared (SWIR 1) spectral bands, allow to extract values and intervals where the change produced by deforestation on forest vegetation is identified with acceptable accuracy. The analysis of time series using the Landtrendr algorithm confirmed a reliable change detection in each of the forest disturbance categories.</p>

Classification multi-spectrale et apport de la bande TM7, dans la distinction des dépôts meubles de l'île d'Anticosti, Québec

1985 ◽  
Vol 22 (8) ◽  
pp. 1139-1148 ◽  
Author(s):  
Sylvain Perras ◽  
Ferdinand Bonn ◽  
Hugh Gwyn ◽  
Jean-Marie Dubois
Keyword(s):  
Vegetation Index ◽  
Forest Cover ◽  
Near Infrared ◽  
Spectral Simulation ◽  
Alluvial Deposits ◽  
Strong Reflection ◽  
Infrared Wavelengths ◽  
Anticosti Island ◽  
Surficial Deposits

The differentiation between various surficial deposits and bedrock on Anticosti Island is difficult because of the dense and homogeneous forest cover and because of the subdued topography. Remote sensing allows us to solve this problem by making use of the physical characteristics of Quaternary deposits and the weathered bedrock, which influence internal drainage and the availability of soil moisture to the vegetation. A spectral simulation of LANDSAT-4 was made using an airborne Daedalus 1260, 11-channel scanner. Several supervised classifications of the digital images were made using test sites studied in the field. Using the raw data from Thematic Mapper bands TM2, TM3, TM4, and TM7, the geologic environments and the ecodynamic units could be distinguished with 70% accuracy. However, the integration of bands TM2 and TM4 with the vegetation index (VI) = [(TM4 – TM3)/(TM4 + TM3)] and the algorithme (A) = [(TM7 − VI)/(TM7 + VI)] resulted in a classification accuracy of 80%. Band TM7 (2,08–2,35 μm) distinguishes itself from the other bands by having a strong reflection over bare bedrock and an absorption by water, which allow the characterization of modern alluvial deposits. The characteristics of TM7 can also be distinguished from those of the near-infrared wavelengths of TM4, which are absorbed by forest vegetation.

scholarly journals Experimental Evaluation and Consistency Comparison of UAV Multispectral Minisensors

2020 ◽  
Vol 12 (16) ◽  
pp. 2542
Author(s):  
Han Lu ◽  
Tianxing Fan ◽  
Prakash Ghimire ◽  
Lei Deng
Keyword(s):  
Precision Agriculture ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Spectral Response ◽  
Change Analysis ◽  
Vegetation Monitoring ◽  
Ground Point ◽  
Highly Correlated

In recent years, the use of unmanned aerial vehicles (UAVs) has received increasing attention in remote sensing, vegetation monitoring, vegetation index (VI) mapping, precision agriculture, etc. It has many advantages, such as high spatial resolution, instant information acquisition, convenient operation, high maneuverability, freedom from cloud interference, and low cost. Nowadays, different types of UAV-based multispectral minisensors are used to obtain either surface reflectance or digital number (DN) values. Both the reflectance and DN values can be used to calculate VIs. The consistency and accuracy of spectral data and VIs obtained from these sensors have important application value. In this research, we analyzed the earth observation capabilities of the Parrot Sequoia (Sequoia) and DJI Phantom 4 Multispectral (P4M) sensors using different combinations of correlation coefficients and accuracy assessments. The research method was mainly focused on three aspects: (1) consistency of spectral values, (2) consistency of VI products, and (3) accuracy of normalized difference vegetation index (NDVI). UAV images in different resolutions were collected using these sensors, and ground points with reflectance values were recorded using an Analytical Spectral Devices handheld spectroradiometer (ASD). The average spectral values and VIs of those sensors were compared using different regions of interest (ROIs). Similarly, the NDVI products of those sensors were compared with ground point NDVI (ASD-NDVI). The results show that Sequoia and P4M are highly correlated in the green, red, red edge, and near-infrared bands (correlation coefficient (R2) > 0.90). The results also show that Sequoia and P4M are highly correlated in different VIs; among them, NDVI has the highest correlation (R2 > 0.98). In comparison with ground point NDVI (ASD-NDVI), the NDVI products obtained by both of these sensors have good accuracy (Sequoia: root-mean-square error (RMSE) < 0.07; P4M: RMSE < 0.09). This shows that the performance of different sensors can be evaluated from the consistency of spectral values, consistency of VI products, and accuracy of VIs. It is also shown that different UAV multispectral minisensors can have similar performances even though they have different spectral response functions. The findings of this study could be a good framework for analyzing the interoperability of different sensors for vegetation change analysis.

Management and engineering solutions to improve stripping equipment efficiency in Chernogorksy open pit mine

2018 ◽  
pp. 36-48
Author(s):  
G. N. Shapovalenko ◽  
S. N. Radionov ◽  
V. V. Gorbunov ◽  
V. A. Khazhiev ◽  
V. Yu. Zalyadnov ◽  
...  
Keyword(s):  
Open Pit Mine ◽  
Open Pit ◽  
High Concentration ◽  
Open Pit Mines ◽  
Blasting Operation ◽  
Internal Dump ◽  
Mining Conditions ◽  
Mining Front ◽  
Comparison Of Equipment

Chernogosky open pit mine integrates truck-and-shovel system of mining with overburden rehandling to internal dump with a set of walking excavators for rehandling of overburden to mined-out area of the pit. It is possible to improve efficiency of stripping in the conditions of Chernogorsky OPM by reducing percentage of stripping with more expensive handling system. The relevant research and solutions to this effect are presented in this article. Comparative characterization of mining conditions and parameters of mining systems applied is given for open pit mines Chernogorsky, Turnui, Nazarovsky, Vostochno-Beisky and Izykh. The comparative analysis points at the need to account for difficulty of mining and process sites in comparison of equipment productivity. High concentration of mining machines, which is conditioned by narrow mining front and simultaneous operation of five faces, as well as blasting operation implemented every 1-2 days, are recognized as the main constraints of excavator capacity in mining with direct dumping in Chernogorsky open pit mine. The management and engineering solutions implemented in the mine and resulted in higher efficiency of draglines are described.

Highly Fluorescent Au25-xAgx Nanoclusters Protected with Poly(ethylene glycol) - and Zwitterion-Modified Thiolate Ligands

2018 ◽  
Author(s):  
Dinesh Mishra ◽  
Sisi Wang ◽  
Zhicheng Jin ◽  
Eric Lochner ◽  
Hedi Mattoussi
Keyword(s):  
Quantum Yield ◽  
Near Infrared ◽  
Small Diameter ◽  
Binding Energies ◽  
Thiolate Ligands ◽  
Nir Emission ◽  
Thiolate Complexes ◽  
Long Lifetime ◽  
Poly Ethylene

<p>We describe the growth and characterization of highly fluorescing, near-infrared-emitting nanoclusters made of bimetallic Au<sub>25-x</sub>Ag<sub>x</sub> cores, prepared using various monothiol-appended hydrophobic and hydrophilic ligands. The reaction uses well-defined triphenylphosphine-protected Au<sub>11</sub> clusters (as precursors), which are reacted with Ag(I)-thiolate complexes. The prepared nanoclusters are small (diameter < 2nm, as characterized by TEM) with emission peak at 760 nm and long lifetime (~12 µs). The quantum yield measured for these materials was 0.3 - 0.4 depending on the ligand. XPS measurements show the presence of both metal atoms in the core, with measured binding energies that agree with reported values for nanocluster materials. The NIR emission combined with high quantum yield, small size and ease of surface functionalization afforded by the coating, make these materials suitable to implement investigations that address fundamental questions and potentially useful for biological sensing and imaging applications.<br></p>

Photon Emission Spectral Signatures of AlGaN/GaN HEMT for Functional and Reliability Analysis

2008 ◽  
Author(s):  
Arkadiusz Glowacki ◽  
Christian Boit ◽  
Richard Lossy ◽  
Joachim Würfl
Keyword(s):  
Reliability Analysis ◽  
Gate Voltage ◽  
Near Infrared ◽  
Photon Emission ◽  
Electrical Characterization ◽  
Spectral Signatures ◽  
Operating Modes ◽  
Gan Hemt ◽  
Spectrally Resolved ◽  
Performance Variations

Abstract Non-degraded and degraded AlGaN/GaN HEMT devices have been characterized electrically and investigated in various operating modes using integral and spectrally resolved photon emission (PE). In degraded devices the PE dependence on the gate voltage differs from the non-degraded devices. Various types of dependencies on the gate voltage have been identified when investigating local degradation sites. PE spectroscopy was performed at various bias conditions. For both devices broad spectra have been obtained in a wavelength regime from visible to near-infrared, including local performance variations. Signatures of the degradation have been determined in the electrical characterization, in integral PE distribution and in the PE spectrum.

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