scholarly journals SPECTROPHOTOMETRIC REMOTE SENSING OF PLANETS AND SATELLITES

1981 ◽  
Vol 96 ◽  
pp. 57-87 ◽  
Author(s):  
T. B. McCord ◽  
D. P. Cruikshank

Near infrared spectrophotometry has vastly increased our knowledge of the composition and structure of asteroids, satellites and planetary surfaces over the past ten years. In this article we will attempt to summarize the most recent comprehensive results. We will emphasize the interpretations and present only examples of the data.

1977 ◽  
Vol 4 (1) ◽  
pp. 229-232
Author(s):  
William K. Hartmann

Analysis of cratering on all terrestrial planets and satellites has produced tools to study (1) the past meteoroid and planetesimal environment, (2) the erosive environments of planetary surfaces, and (3) the relative and absolute ages of planetary surface units. Important findings include a decline in lunar crater production rate from a value 4 x 109years ago that was thousands of times higher than the present, to present values which have been relatively constant for 2 to 3 x 109years; evidence for an erosive period or periods on Mars that degraded many Martian craters but declined substantially at some time in the past; and the concept of destruction of primeval planetary surfaces by early intense cratering and production of a mega-regolith.


2017 ◽  
Vol 32 (S2) ◽  
pp. S3-S8
Author(s):  
Helen E. Maynard-Casely ◽  
Norman Booth ◽  
Leo Anderberg ◽  
Helen E.A. Brand ◽  
Daniel V. Cotton

Knowledge of the surface composition of planetary bodies comes from a number of sources; such as landers, remote sensing and meteorites. However, the bulk mapping of the composition of planetary surfaces has been undertaken by analysis of reflected sunlight and these data—principally collected in the near-infra-red (IR) region—are notoriously broad and ambiguous. Hence, if laboratory spectra could be tied to physical properties measurements, such as diffraction, this would substantially aid our understanding of processes occurring in these extra-terrestrial environments. This contribution presents the capability of collecting near-IR data at the same time as neutron and synchrotron X-ray diffraction in a range of conditions (low temperature, vacuum, and humidity variations) and highlights two examples where this capability could enhance our understanding of planetary surfaces.


2020 ◽  
Author(s):  
Bhabagrahi Sahoo ◽  
Debi Prasad Sahoo ◽  
Manoj Kumar Tiwari

<p>Streamflow is the fundamental variable for any hydro-informatics based decision making to manage catchment-scale water resources. However, with the significant reduction in the number of streamflow gauging stations in many world-rivers, emphasis has now been shifted toward obtaining river discharges along the ungauged / scantily-gauged river reaches using innovative hydroinformatics tools. Many rivers which were gauged in the past, are now ungauged. In this context, this study considers a typical real-river, namely, the 48 km Bolani-Gomlai reach of the Brahmani River in eastern India, where a few historical concurrent streamflow hydrographs are available at the upstream and downstream gauging stations, which are defunct at present. Therefore, the main focus of this study is to generate spatially distributed high-frequent daily-scale river discharges along the selected ungauged river reach using the real-time optical remote sensing (RS) based imageries. To achieve this objective, the MIKE11 hydrodynamic (HD) model is setup and used in the selected reach to route the past streamflow records, available at the upstream section, so as to obtain the corresponding spatially distributed past discharges at 1 km resolution downstream. These routed historical streamflow records at each 1 km interval form the observed flow database for that specific RS-based virtual streamflow measurement station (VMS). For establishing the VMSs at each 1 km interval to estimate daily-scale river discharges, an RS-based methodology has been advocated that uses the spectral reflectances of the fused MODIS and Landsat satellite imageries and the MIKE11-HD derived corresponding routed past streamflows for calibration and validation. The different spectral behavior of land (C) and water (W) pixels in the near infrared of the electromagnetic spectrum is exploited by computing the (C/W) ratio of the fused imageries between two pixels located within (W) and outside (C), but close to the river. The values of C/W increase with the presence of water and, hence, with discharge. Moreover, in order to reduce the noise effect, an exponential smoothening filter is applied to obtain C/W<sub>*</sub>. Finally, the real-time filtered pixel ratios are used in the RS-based framework to estimate recent high-frequent streamflows in the ungauged river reach. The results reveal that the developed model has a very good potential which can be extended for high-frequent discharge estimation at any ungauged world-river reaches.</p>


Nanoscale ◽  
2021 ◽  
Author(s):  
Jinsong Xiong ◽  
Qinghuan Bian ◽  
Shuijin Lei ◽  
Yatian Deng ◽  
Kehan Zhao ◽  
...  

Near-infrared (NIR) light induced photothermal cancer therapy using nanomaterials as photothermal agents has attracted considerable research interest over the past few years. As the key factor in the photothermal therapy...


2021 ◽  
Vol 13 (13) ◽  
pp. 2570
Author(s):  
Teng Li ◽  
Bozhong Zhu ◽  
Fei Cao ◽  
Hao Sun ◽  
Xianqiang He ◽  
...  

Based on characteristics analysis about remote sensing reflectance, the Secchi Disk Depth (SDD) in the Qiandao Lake was predicted from the Landsat8/OLI data, and its changing rates on a pixel-by-pixel scale were obtained from satellite remote sensing for the first time. Using 114 matchups data pairs during 2013–2019, the SDD satellite algorithms suitable for the Qiandao Lake were obtained through both the linear regression and machine learning (Support Vector Machine) methods, with remote sensing reflectance (Rrs) at different OLI bands and the ratio of Rrs (Band3) to Rrs (Band2) as model input parameters. Compared with field observations, the mean absolute relative difference and root mean squared error of satellite-derived SDD were within 20% and 1.3 m, respectively. Satellite-derived results revealed that SDD in the Qiandao Lake was high in boreal spring and winter, and reached the lowest in boreal summer, with the annual mean value of about 5 m. Spatially, high SDD was mainly concentrated in the southeast lake area (up to 13 m) close to the dam. The edge and runoff area of the lake were less transparent, with an SDD of less than 4 m. In the past decade (2013–2020), 5.32% of Qiandao Lake witnessed significant (p < 0.05) transparency change: 4.42% raised with a rate of about 0.11 m/year and 0.9% varied with a rate of about −0.09 m/year. Besides, the findings presented here suggested that heavy rainfall would have a continuous impact on the Qiandao Lake SDD. Our research could promote the applications of land observation satellites (such as the Landsat series) in water environment monitoring in inland reservoirs.


Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 922
Author(s):  
William Querido ◽  
Shital Kandel ◽  
Nancy Pleshko

Advances in vibrational spectroscopy have propelled new insights into the molecular composition and structure of biological tissues. In this review, we discuss common modalities and techniques of vibrational spectroscopy, and present key examples to illustrate how they have been applied to enrich the assessment of connective tissues. In particular, we focus on applications of Fourier transform infrared (FTIR), near infrared (NIR) and Raman spectroscopy to assess cartilage and bone properties. We present strengths and limitations of each approach and discuss how the combination of spectrometers with microscopes (hyperspectral imaging) and fiber optic probes have greatly advanced their biomedical applications. We show how these modalities may be used to evaluate virtually any type of sample (ex vivo, in situ or in vivo) and how “spectral fingerprints” can be interpreted to quantify outcomes related to tissue composition and quality. We highlight the unparalleled advantage of vibrational spectroscopy as a label-free and often nondestructive approach to assess properties of the extracellular matrix (ECM) associated with normal, developing, aging, pathological and treated tissues. We believe this review will assist readers not only in better understanding applications of FTIR, NIR and Raman spectroscopy, but also in implementing these approaches for their own research projects.


Author(s):  
Nidhi Rajesh Mavani ◽  
Jarinah Mohd Ali ◽  
Suhaili Othman ◽  
M. A. Hussain ◽  
Haslaniza Hashim ◽  
...  

AbstractArtificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry–related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers.


Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 231
Author(s):  
Can Trong Nguyen ◽  
Amnat Chidthaisong ◽  
Phan Kieu Diem ◽  
Lian-Zhi Huo

Bare soil is a critical element in the urban landscape and plays an essential role in urban environments. Yet, the separation of bare soil and other land cover types using remote sensing techniques remains a significant challenge. There are several remote sensing-based spectral indices for barren detection, but their effectiveness varies depending on land cover patterns and climate conditions. Within this research, we introduced a modified bare soil index (MBI) using shortwave infrared (SWIR) and near-infrared (NIR) wavelengths derived from Landsat 8 (OLI—Operational Land Imager). The proposed bare soil index was tested in two different bare soil patterns in Thailand and Vietnam, where there are large areas of bare soil during the agricultural fallow period, obstructing the separation between bare soil and urban areas. Bare soil extracted from the MBI achieved higher overall accuracy of about 98% and a kappa coefficient over 0.96, compared to bare soil index (BSI), normalized different bare soil index (NDBaI), and dry bare soil index (DBSI). The results also revealed that MBI considerably contributes to the accuracy of land cover classification. We suggest using the MBI for bare soil detection in tropical climatic regions.


2013 ◽  
Vol 59 (215) ◽  
pp. 467-479 ◽  
Author(s):  
Jeffrey S. Deems ◽  
Thomas H. Painter ◽  
David C. Finnegan

AbstractLaser altimetry (lidar) is a remote-sensing technology that holds tremendous promise for mapping snow depth in snow hydrology and avalanche applications. Recently lidar has seen a dramatic widening of applications in the natural sciences, resulting in technological improvements and an increase in the availability of both airborne and ground-based sensors. Modern sensors allow mapping of vegetation heights and snow or ground surface elevations below forest canopies. Typical vertical accuracies for airborne datasets are decimeter-scale with order 1 m point spacings. Ground-based systems typically provide millimeter-scale range accuracy and sub-meter point spacing over 1 m to several kilometers. Many system parameters, such as scan angle, pulse rate and shot geometry relative to terrain gradients, require specification to achieve specific point coverage densities in forested and/or complex terrain. Additionally, snow has a significant volumetric scattering component, requiring different considerations for error estimation than for other Earth surface materials. We use published estimates of light penetration depth by wavelength to estimate radiative transfer error contributions. This paper presents a review of lidar mapping procedures and error sources, potential errors unique to snow surface remote sensing in the near-infrared and visible wavelengths, and recommendations for projects using lidar for snow-depth mapping.


Weed Science ◽  
2004 ◽  
Vol 52 (4) ◽  
pp. 492-497 ◽  
Author(s):  
E. Raymond Hunt ◽  
James E. McMurtrey ◽  
Amy E. Parker Williams ◽  
Lawrence A. Corp

Leafy spurge can be detected during flowering with either aerial photography or hyperspectral remote sensing because of the distinctive yellow-green color of the flower bracts. The spectral characteristics of flower bracts and leaves were compared with pigment concentrations to determine the physiological basis of the remote sensing signature. Compared with leaves of leafy spurge, flower bracts had lower reflectance at blue wavelengths (400 to 500 nm), greater reflectance at green, yellow, and orange wavelengths (525 to 650 nm), and approximately equal reflectances at 680 nm (red) and at near-infrared wavelengths (725 to 850 nm). Pigments from leaves and flower bracts were extracted in dimethyl sulfoxide, and the pigment concentrations were determined spectrophotometrically. Carotenoid pigments were identified using high-performance liquid chromatography. Flower bracts had 84% less chlorophylla, 82% less chlorophyllb, and 44% less total carotenoids than leaves, thus absorptance by the flower bracts should be less and the reflectance should be greater at blue and red wavelengths. The carotenoid to chlorophyll ratio of the flower bracts was approximately 1:1, explaining the hue of the flower bracts but not the value of reflectance. The primary carotenoids were lutein, β-carotene, and β-cryptoxanthin in a 3.7:1.5:1 ratio for flower bracts and in a 4.8:1.3:1 ratio for leaves, respectively. There was 10.2 μg g−1fresh weight of colorless phytofluene present in the flower bracts and none in the leaves. The fluorescence spectrum indicated high blue, red, and far-red emission for leaves compared with flower bracts. Fluorescent emissions from leaves may contribute to the higher apparent leaf reflectance in the blue and red wavelength regions. The spectral characteristics of leafy spurge are important for constructing a well-documented spectral library that could be used with hyperspectral remote sensing.


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