scholarly journals A 10-nm Spectral Resolution Hyperspectral LiDAR System Based on an Acousto-Optic Tunable Filter

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1620 ◽  
Author(s):  
Yuwei Chen ◽  
Wei Li ◽  
Juha Hyyppä ◽  
Ning Wang ◽  
Changhui Jiang ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
Near Infrared ◽  
Spatial Information ◽  
Tunable Filter ◽  
High Spectral Resolution ◽  
Spectral Information ◽  
Time Dimension ◽  
Lidar System ◽  
Full Spectrum ◽  
Comparison Results

Hyperspectral LiDAR (HSL) technology can obtain spectral and ranging information from targets by processing the recorded waveforms and measuring the time of flight (ToF). With the development of the supercontinuum laser (SCL), it is technically easier to develop an active hyperspectral LiDAR system that can simultaneously collect both spatial information and extensive spectral information from targets. Compared with traditional LiDAR technology, which can only obtain range and intensity information at the selected spectral wavelengths, HSL detection technology has demonstrated its potential and adaptability for various quantitative applications from its spectrally resolved waveforms. However, with most previous HSLs, the collected spectral information is discrete, and such information might be insufficient and restrict the further applicability of the HSLs. In this paper, a tunable HSL technology using an acousto-optic tunable filter (AOTF) as a spectroscopic device was proposed, designed, and tested to address this issue. Both the general range precision and the accuracy of the spectral measurement were evaluated. By tuning the spectroscopic device in the time dimension, the proposed AOTF-HSL could achieve backscattered echo with continuous coverage of the full spectrum of 500–1000 nm, which had the unique characteristics of a continuous spectrum in the visible and near infrared (VNIR) regions with 10 nm spectral resolution. Yellow and green leaves from four plants (aloe, dracaena, balata, and radermachera) were measured using the AOTF-HSL to assess its feasibility in agriculture application. The spectral profiles measured by a standard spectrometer (SVC© HR-1024) were used as a reference for evaluating the measurements of the AOTF-HSL. The difference between the spectral measurements collected from active and passive instruments was minor. The comparison results show that the AOTF-based consecutive and high spectral resolution HSL was effective for this application.

scholarly journals Study of a High Spectral Resolution Hyperspectral LiDAR in Vegetation Red Edge Parameters Extraction

2019 ◽  
Vol 11 (17) ◽  
pp. 2007 ◽  
Author(s):  
Changhui Jiang ◽  
Yuwei Chen ◽  
Haohao Wu ◽  
Wei Li ◽  
Hui Zhou ◽  
...  
Keyword(s):  
Spectral Range ◽  
Spectral Resolution ◽  
Spatial Information ◽  
Research Direction ◽  
Parameter Extraction ◽  
Tunable Filter ◽  
High Spectral Resolution ◽  
Red Edge ◽  
Parameters Extraction ◽  
Vegetation Parameter

Non-contact and active vegetation or plant parameters extraction using hyperspectral information is a prospective research direction among the remote sensing community. Hyperspectral LiDAR (HSL) is an instrument capable of acquiring spectral and spatial information actively, which could mitigate the environmental illumination influence on the spectral information collection. However, HSL usually has limited spectral resolution and coverage, which is vital for vegetation parameter extraction. In this paper, to broaden the HSL spectral range and increase the spectral resolution, an Acousto-optical Tunable Filter based Hyperspectral LiDAR (AOTF-HSL) with 10 nm spectral resolution, consecutively covering from 500–1000 nm, was designed. The AOTF-HSL was employed and evaluated for vegetation parameters extraction. “Red Edge” parameters of four different plants with green and yellow leaves were extracted in the lab experiments for evaluating the HSL vegetation parameter extraction capacity. The experiments were composed of two parts. Firstly, the first-order derivative of the spectral reflectance was employed to extract the “Red Edge” position (REP), “Red Edge” slope (RES) and “Red Edge” area (REA) of these green and yellow leaves. The results were compared with the referenced value from a standard SVC© HR-1024 spectrometer for validation. Green leaf parameter differences between HSL and SVC results were minor, which supported that notion the HSL was practical for extracting the employed parameter as an active method. Secondly, another two different REP extraction methods, Linear Four-point Interpolation technology (LFPIT) and Linear Extrapolation technology (LET), were utilized for further evaluation of using the AOTF-HSL spectral profile to determine the REP value. The differences between the plant green leaves’ REP results extracted using the three methods were all below 10%, and the some of them were below 1%, which further demonstrated that the spectral data collected from HSL with this spectral range and resolution settings was applicable for “Red Edge” parameters extraction.

scholarly journals Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information

2020 ◽  
Vol 12 (6) ◽  
pp. 1009
Author(s):  
Xiaoxiao Feng ◽  
Luxiao He ◽  
Qimin Cheng ◽  
Xiaoyi Long ◽  
Yuxin Yuan
Keyword(s):  
Image Fusion ◽  
Spatial Resolution ◽  
Spectral Resolution ◽  
Spatial Information ◽  
Spectral Unmixing ◽  
High Spectral Resolution ◽  
Remote Sensing Image Fusion ◽  
Fusion Methods ◽  
Invariant Regions ◽  
The Difference

Hyperspectral (HS) images usually have high spectral resolution and low spatial resolution (LSR). However, multispectral (MS) images have high spatial resolution (HSR) and low spectral resolution. HS–MS image fusion technology can combine both advantages, which is beneficial for accurate feature classification. Nevertheless, heterogeneous sensors always have temporal differences between LSR-HS and HSR-MS images in the real cases, which means that the classical fusion methods cannot get effective results. For this problem, we present a fusion method via spectral unmixing and image mask. Considering the difference between the two images, we firstly extracted the endmembers and their corresponding positions from the invariant regions of LSR-HS images. Then we can get the endmembers of HSR-MS images based on the theory that HSR-MS images and LSR-HS images are the spectral and spatial degradation from HSR-HS images, respectively. The fusion image is obtained by two result matrices. Series experimental results on simulated and real datasets substantiated the effectiveness of our method both quantitatively and visually.

Spectrum Filter Performance Analysis on Near-Infrared High-Spectral-Resolution Lidar

2016 ◽  
Vol 43 (4) ◽  
pp. 0414004
Author(s):  
张与鹏 Zhang Yupeng ◽  
刘东 Liu Dong ◽  
杨甬英 Yang Yongying ◽  
罗敬 Luo Jing ◽  
成中涛 Cheng Zhongtao ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Spectral Resolution ◽  
Near Infrared ◽  
High Spectral Resolution ◽  
Filter Performance ◽  
High Spectral Resolution Lidar

scholarly journals Global monitoring of terrestrial chlorophyll fluorescence from moderate spectral resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2

2013 ◽  
Vol 6 (2) ◽  
pp. 3883-3930 ◽  
Author(s):  
J. Joiner ◽  
L. Guanter ◽  
R. Lindstrot ◽  
M. Voigt ◽  
A. P. Vasilkov ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Spectral Resolution ◽  
Near Infrared ◽  
High Spectral Resolution ◽  
High Signal ◽  
Good Precision ◽  
Atmospheric Absorption ◽  
Red Fluorescence ◽  
Fluorescence Measurements ◽  
Global Mapping

Abstract. Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. In addition, fluorescence can contaminate photon path estimates from the O2 A-band that has become an integral part of missions to accurately measure greenhouse gas concentrations. Global mapping of far-red (~ 755–770 nm) terrestrial vegetation solar-induced fluorescence from space has been accomplished using the high spectral resolution (ν/Δ ν > 35 000) interferometer on the Japanese Greenhouse gases Observing SATellite (GOSAT). These satellite retrievals of fluorescence rely solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data to disentangle the spectral signatures of three basic components in and surrounding the O2 A-band: atmospheric absorption, surface reflectance, and fluorescence radiance. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate spectral resolution measurements with a relatively high signal-to-noise ratio within and outside the O2 A-band can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with GOSAT. GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. It should be noted that both GOME-2 and GOSAT were designed to make atmospheric trace gas measurements and were not optimized for fluorescence measurements. Our approach can be applied to other existing and future space-based instruments that provide moderate spectral resolution observations in the near-infrared region.

Indium Antimonide (InSb) Focal Plane Array (FPA) Detection for Near-Infrared Imaging Microscopy

1994 ◽  
Vol 48 (5) ◽  
pp. 607-615 ◽  
Author(s):  
Patrick J. Treado ◽  
Ira W. Levin ◽  
E. Neil Lewis
Keyword(s):  
Indium Antimonide ◽  
High Speed ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Optical Microscope ◽  
Tunable Filter ◽  
Model Systems ◽  
High Spectral Resolution ◽  
Spectral Interval ◽  
Wide Range

Near-infrared spectroscopy is a sensitive, noninvasive method for chemical analyses, and its integration with imaging technologies represents a potent tool for the study of a wide range of materials. In this communication the use of an indium antimonide (InSb) multichannel imaging detector for near-infrared absorption spectroscopic microscopy is described. In particular, a 128 × 128 pixel InSb staring array camera has been combined with a refractive optical microscope and an acousto-optic tunable filter (AOTF) to display chemically discriminative, spatially resolved, vibrational spectroscopic images of biological and polymeric systems. AOTFs are computer-controlled bandpass filters that provide high speed, random wavelength access, wide spectral coverage, and high spectral resolution. Although AOTFs inherently have a wide range of spectroscopic applications, we apply this technology to NIR absorption microscopy between 1 and 2.5 μm. The spectral interval is well matched to the optical characteristics of both the NIR refractive microscope and the AOTF, thereby providing near-diffraction-limited performance with a practical spatial resolution of 1 to 2 μm. Design principles of this novel instrumentation and representative applications of the technique are presented for various model systems.

scholarly journals Development of High Spectral Resolution Lidar System for Measuring Aerosol and Cloud

2015 ◽  
Vol 19 (6) ◽  
pp. 695-699 ◽  
Author(s):  
Ming Zhao ◽  
Chen-Bo Xie ◽  
Zhi-Qing Zhong ◽  
Bang-Xin Wang ◽  
Zhen-Zhu Wang ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
High Spectral Resolution ◽  
Lidar System ◽  
High Spectral Resolution Lidar

scholarly journals Development of a high spectral resolution surface albedo product for the ARM Southern Great Plains central facility

2011 ◽  
Vol 4 (3) ◽  
pp. 3097-3145
Author(s):  
S. A. McFarlane ◽  
K. L. Gaustad ◽  
E. J. Mlawer ◽  
C. N. Long ◽  
J. Delamere
Keyword(s):  
Great Plains ◽  
Spectral Resolution ◽  
Surface Albedo ◽  
Vegetation Index ◽  
Near Infrared ◽  
High Spectral Resolution ◽  
Surface Type ◽  
Southern Great Plains ◽  
Green Vegetation ◽  
Visible Wavelengths

Abstract. We present a method for identifying dominant surface type and estimating high spectral resolution surface albedo at the Atmospheric Radiation Measurement (ARM) facility at the Southern Great Plains (SGP) site in Oklahoma for use in radiative transfer calculations. Given a set of 6-channel narrowband visible and near-infrared irradiance measurements from upward and downward looking multi-filter radiometers (MFRs), four different surface types (snow-covered, green vegetation, partial vegetation, non-vegetated) can be identified. A normalized difference vegetation index (NDVI) is used to distinguish between vegetated and non-vegetated surfaces, and a scaled NDVI index is used to estimate the percentage of green vegetation in partially vegetated surfaces. Based on libraries of spectral albedo measurements, a piecewise continuous function is developed to estimate the high spectral resolution surface albedo for each surface type given the MFR albedo values as input. For partially vegetated surfaces, the albedo is estimated as a linear combination of the green vegetation and non-vegetated surface albedo values. The estimated albedo values are evaluated through comparison to high spectral resolution albedo measurements taken during several Intensive Observational Periods (IOPs) and through comparison of the integrated spectral albedo values to observed broadband albedo measurements. The estimated spectral albedo values agree well with observations for the visible wavelengths constrained by the MFR measurements, but have larger biases and variability at longer wavelengths. Additional MFR channels at 1100 nm and/or 1600 nm would help constrain the high resolution spectral albedo in the near infrared region.

scholarly journals Spatial Sharpening of KOMPSAT-3A MIR Images Using Optimal Scaling Factor

2020 ◽  
Vol 12 (22) ◽  
pp. 3772
Author(s):  
Kwan-Young Oh ◽  
Hyung-Sup Jung ◽  
Sung-Hwan Park ◽  
Kwang-Jae Lee
Keyword(s):  
Spectral Resolution ◽  
Visual Analysis ◽  
Spatial Information ◽  
Optimal Scaling ◽  
Scaling Factor ◽  
High Spectral Resolution ◽  
Qualitative Assessment ◽  
Dimensional Synthesis ◽  
The One ◽  
Comparison Of The Results

This paper present efficient methods for merging KOMPSAT-3A (Korea Multi-Purpose Satellite) medium wave Infrared (MIR) and panchromatic (PAN) images. Spatial sharpening techniques have been developed to create an image with both high spatial and high spectral resolution by combining the desired qualities of a PAN image with high spatial and low spectral resolution and an MS/MIR image with low spatial and high spectral resolution. The proposed methods can extract an optimal scaling factor, and uses the tactics of appropriately controlling the balance between the spatial and spectral resolutions. KOMPSAT-3A PAN and MIR images were used to test and evaluate the performance of the proposed methods. A qualitative assessment were performed using the image quality index (Q4), the cross correlation index (CC) and the relative global dimensional synthesis error (Spectral/Spatial ERGAS). These tests indicate that the proposed methods preserve the spectral and spatial characteristics of the original MIR and PAN images. Visual analysis reveals that the spectral and spatial information derived from the proposed methods were well retained in the test images. A comparison of the results of the proposed methods with those obtained from applying existing ones such as the Multi Sensor Fusion (MSF) technique or the Guide Filter Based Fusion (GF) show the efficiency of the new fusion process to be superior to the one of the others. The results showed a significant improvement in fusion capability for KOMPSAT-3A MIR imagery.

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