New method of sea-water natural admixture concentration determination by remote sensing without atmospheric correction

1999 ◽  
Author(s):  
Vadim N. Pelevin ◽  
Vera V. Rostovtseva
Keyword(s):  
Remote Sensing ◽  
Sea Water ◽  
Atmospheric Correction ◽  
New Method ◽  
Admixture Concentration ◽  
Concentration Determination

An Antisubmarine Detection Method Using IR Spectrometer in Ocean Remote Sensing

2012 ◽  
Vol 490-495 ◽  
pp. 1337-1341
Author(s):  
Zhi Wu Ke ◽  
Rui Yu ◽  
Rui Xiang ◽  
Ke Long Zhang ◽  
Yong Ma
Keyword(s):  
Remote Sensing ◽  
Ir Spectrum ◽  
Detection Method ◽  
Sea Water ◽  
Atmospheric Correction ◽  
Correction Algorithm ◽  
Ir Imaging ◽  
Detection Approach ◽  
Infrared Spectrometer ◽  
Ocean Remote Sensing

According to the reduction of submarine noise level, Non-acoustics antisubmarine detection method becomes more important for the ocean remote sensing, especially infrared (IR) imaging remote sensing detection method. Conventional IR imaging remote sensing antisubmarine detection is more difficult because modern advanced submarine IR thermal radiance is not obvious. In this paper, our main purpose is to develop the advanced IR imaging remote sensing antisubmarine detection approach by using infrared spectrometer. The IR spectrum information derived from IR spectrometer in sea water and then retrieves the water-leaving spectra by the standard atmospheric correction algorithm. The submarine is detected by analyzing the water-leaving spectrum information. Results of comparisons with conventional IR imaging remote sensing antisubmarine detection, the modified approach is available to estimate the spectrum properties and effective to antisubmarine detection in sea water

scholarly journals Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean

2021 ◽  
Vol 13 (2) ◽  
pp. 184
Author(s):  
Rongjie Liu ◽  
Jie Zhang ◽  
Tingwei Cui ◽  
Haocheng Yu
Keyword(s):  
Remote Sensing ◽  
Indian Ocean ◽  
Infrared Imaging ◽  
Atmospheric Correction ◽  
Spatiotemporal Pattern ◽  
Anthropogenic Aerosols ◽  
Remote Sensing Reflectance ◽  
The Indian Ocean ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Modis

Spectral remote sensing reflectance (Rrs(λ), sr−1) is one of the most important products of ocean color satellite missions, where accuracy is essential for retrieval of in-water, bio-optical, and biogeochemical properties. For the Indian Ocean (IO), where Rrs(λ) accuracy has not been well documented, the quality of Rrs(λ) products from Moderate Resolution Imaging Spectroradiometer onboard both Terra (MODIS-Terra) and Aqua (MODIS-Aqua), and Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-Orbiting Partnership spacecraft (VIIRS-NPP), is evaluated and inter-compared based on a quality assurance (QA) system, which can objectively grade each individual Rrs(λ) spectrum, with 1 for a perfect spectrum and 0 for an unusable spectrum. Taking the whole year of 2016 as an example, spatiotemporal pattern of Rrs(λ) quality in the Indian Ocean is characterized for the first time, and the underlying factors are elucidated. Specifically, QA analysis of the monthly Rrs(λ) over the IO indicates good quality with the average scores of 0.93 ± 0.02, 0.92 ± 0.02 and 0.92 ± 0.02 for VIIRS-NPP, MODIS-Aqua, and MODIS-Terra, respectively. Low-quality (~0.7) data are mainly found in the Bengal Bay (BB) from January to March, which can be attributed to the imperfect atmospheric correction due to anthropogenic absorptive aerosols transported by the northeasterly winter monsoon. Moreover, low-quality (~0.74) data are also found in the clear oligotrophic gyre zone (OZ) of the south IO in the second half of the year, possibly due to residual sun-glint contributions. These findings highlight the effects of monsoon-transported anthropogenic aerosols, and imperfect sun-glint removal on the Rrs(λ) quality. Further studies are advocated to improve the sun-glint correction in the oligotrophic gyre zone and aerosol correction in the complex ocean–atmosphere environment.

STARS: A New Method for Multitemporal Remote Sensing

2013 ◽  
Vol 51 (4) ◽  
pp. 1897-1913 ◽  
Author(s):  
Marcio Pupin Mello ◽  
Carlos A. O. Vieira ◽  
Bernardo F. T. Rudorff ◽  
Paul Aplin ◽  
Rafael D. C. Santos ◽  
...  
Keyword(s):  
Remote Sensing ◽  
New Method ◽  
Multitemporal Remote Sensing

scholarly journals A New Method on Calibrating PSF of Remote Sensing Space Plane Arraycamera

2017 ◽  
Vol 114 ◽  
pp. 03011
Author(s):  
Wei Liu ◽  
HuiTing Gao ◽  
ShiXiang Cao ◽  
Wei Tan ◽  
YunFei Bao
Keyword(s):  
Remote Sensing ◽  
New Method

scholarly journals Remote sensing of <i>Trichodesmium</i> spp. mats in the western tropical South Pacific

2018 ◽  
Vol 15 (16) ◽  
pp. 5203-5219 ◽  
Author(s):  
Guillaume Rousset ◽  
Florian De Boissieu ◽  
Christophe E. Menkes ◽  
Jérôme Lefèvre ◽  
Robert Frouin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
New Caledonia ◽  
Hot Spot ◽  
Regional Scale ◽  
Atmospheric Correction ◽  
South Pacific ◽  
Aggregation Processes ◽  
Modis Imagery ◽  
Generate Surface

Abstract. Trichodesmium is the major nitrogen-fixing species in the western tropical South Pacific (WTSP) region, a hot spot of diazotrophy. Due to the paucity of in situ observations, remote-sensing methods for detecting Trichodesmium presence on a large scale have been investigated to assess the regional-to-global impact of this organism on primary production and carbon cycling. A number of algorithms have been developed to identify Trichodesmium surface blooms from space, but determining with confidence their accuracy has been difficult, chiefly because of the scarcity of sea-truth information at the time of satellite overpass. Here, we use a series of new cruises as well as airborne surveys over the WTSP to evaluate their ability to detect Trichodesmium surface blooms in the satellite imagery. The evaluation, performed on MODIS data at 250 m and 1 km resolution acquired over the region, shows limitations due to spatial resolution, clouds, and atmospheric correction. A new satellite-based algorithm is designed to alleviate some of these limitations, by exploiting optimally spectral features in the atmospherically corrected reflectance at 531, 645, 678, 748, and 869 nm. This algorithm outperforms former ones near clouds, limiting false positive detection and allowing regional-scale automation. Compared with observations, 80 % of the detected mats are within a 2 km range, demonstrating the good statistical skill of the new algorithm. Application to MODIS imagery acquired during the February-March 2015 OUTPACE campaign reveals the presence of surface blooms northwest and east of New Caledonia and near 20∘ S–172∘ W in qualitative agreement with measured nitrogen fixation rates. Improving Trichodesmium detection requires measuring ocean color at higher spectral and spatial (<250 m) resolution than MODIS, taking into account environment properties (e.g., wind, sea surface temperature), fluorescence, and spatial structure of filaments, and a better understanding of Trichodesmium dynamics, including aggregation processes to generate surface mats. Such sub-mesoscale aggregation processes for Trichodesmium are yet to be understood.

scholarly journals SIFSpec: Measuring Solar-Induced Chlorophyll Fluorescence Observations for Remote Sensing of Photosynthesis

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 3009 ◽  
Author(s):  
Shanshan Du ◽  
Liangyun Liu ◽  
Xinjie Liu ◽  
Jian Guo ◽  
Jiaochan Hu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Chlorophyll Fluorescence ◽  
Seasonal Variations ◽  
Photosynthetic Activity ◽  
Gross Primary Production ◽  
Atmospheric Correction ◽  
Gansu Province ◽  
Optical Measurements ◽  
Calibration Data ◽  
Flux Measurements

Solar-induced chlorophyll fluorescence (SIF) is regarded as a proxy for photosynthesis in terrestrial vegetation. Tower-based long-term observations of SIF are very important for gaining further insight into the ecosystem-specific seasonal dynamics of photosynthetic activity, including gross primary production (GPP). Here, we present the design and operation of the tower-based automated SIF measurement (SIFSpec) system. This system was developed with the aim of obtaining synchronous SIF observations and flux measurements across different terrestrial ecosystems, as well as to validate the increasing number of satellite SIF products using in situ measurements. Details of the system components, instrument installation, calibration, data collection, and processing are introduced. Atmospheric correction is also included in the data processing chain, which is important, but usually ignored for tower-based SIF measurements. Continuous measurements made across two growing cycles over maize at a Daman (DM) flux site (in Gansu province, China) demonstrate the reliable performance of SIF as an indicator for tracking the diurnal variations in photosynthetically active radiation (PAR) and seasonal variations in GPP. For the O2–A band in particular, a high correlation coefficient value of 0.81 is found between the SIF and seasonal variations of GPP. It is thus concluded that, in coordination with continuous eddy covariance (EC) flux measurements, automated and continuous SIF observations can provide a reliable approach for understanding the photosynthetic activity of the terrestrial ecosystem, and are also able to bridge the link between ground-based optical measurements and airborne or satellite remote sensing data.

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