scholarly journals A Comparison and Review of Surface Detection Methods Using MBL, MABEL, and ICESat-2 Photon-Counting Laser Altimetry Data

Author(s):  
Huan Xie ◽  
Qi Xu ◽  
Dan Ye ◽  
Jianghao Jia ◽  
Yuan Sun ◽  
...  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ibtissame Khaoua ◽  
Guillaume Graciani ◽  
Andrey Kim ◽  
François Amblard

AbstractFor a wide range of purposes, one faces the challenge to detect light from extremely faint and spatially extended sources. In such cases, detector noises dominate over the photon noise of the source, and quantum detectors in photon counting mode are generally the best option. Here, we combine a statistical model with an in-depth analysis of detector noises and calibration experiments, and we show that visible light can be detected with an electron-multiplying charge-coupled devices (EM-CCD) with a signal-to-noise ratio (SNR) of 3 for fluxes less than $$30\,{\text{photon}}\,{\text{s}}^{ - 1} \,{\text{cm}}^{ - 2}$$ 30 photon s - 1 cm - 2 . For green photons, this corresponds to 12 aW $${\text{cm}}^{ - 2}$$ cm - 2 ≈ $$9{ } \times 10^{ - 11}$$ 9 × 10 - 11 lux, i.e. 15 orders of magnitude less than typical daylight. The strong nonlinearity of the SNR with the sampling time leads to a dynamic range of detection of 4 orders of magnitude. To detect possibly varying light fluxes, we operate in conditions of maximal detectivity $${\mathcal{D}}$$ D rather than maximal SNR. Given the quantum efficiency $$QE\left( \lambda \right)$$ Q E λ of the detector, we find $${ \mathcal{D}} = 0.015\,{\text{photon}}^{ - 1} \,{\text{s}}^{1/2} \,{\text{cm}}$$ D = 0.015 photon - 1 s 1 / 2 cm , and a non-negligible sensitivity to blackbody radiation for T > 50 °C. This work should help design highly sensitive luminescence detection methods and develop experiments to explore dynamic phenomena involving ultra-weak luminescence in biology, chemistry, and material sciences.


2021 ◽  
Vol 13 (16) ◽  
pp. 3062
Author(s):  
Guo Zhang ◽  
Boyang Jiang ◽  
Taoyang Wang ◽  
Yuanxin Ye ◽  
Xin Li

To ensure the accuracy of large-scale optical stereo image bundle block adjustment, it is necessary to provide well-distributed ground control points (GCPs) with high accuracy. However, it is difficult to acquire control points through field measurements outside the country. Considering the high planimetric accuracy of spaceborne synthetic aperture radar (SAR) images and the high elevation accuracy of satellite-based laser altimetry data, this paper proposes an adjustment method that combines both as control sources, which can be independent from GCPs. Firstly, the SAR digital orthophoto map (DOM)-based planar control points (PCPs) acquisition is realized by multimodal matching, then the laser altimetry data are filtered to obtain laser altimetry points (LAPs), and finally the optical stereo images’ combined adjustment is conducted. The experimental results of Ziyuan-3 (ZY-3) images prove that this method can achieve an accuracy of 7 m in plane and 3 m in elevation after adjustment without relying on GCPs, which lays the technical foundation for a global-scale satellite image process.


Author(s):  
G. Li ◽  
X. Tang ◽  
X. Gao ◽  
J. P. Huang ◽  
J. Chen ◽  
...  

After GLAS (Geo-science Laser Altimeter System) loaded on the ICESat (Ice Cloud and land Elevation Satellite), satellite laser altimeter attracts more and more attention. ZY3-02 equipped with the Chinese first satellite laser altimeter has been successfully launched on 30<sup>th</sup> May, 2016. The geometric calibration is an important step for the laser data processing and application. The method to calculate the laser pointing angle error based on existed reference terrain data is proposed in this paper. The public version terrain data, such as 90m-SRTM and 30m-AW3D30, can be used to estimate the pointing angle of laser altimeter. The GLAS data with simulated pointing error and actual ZY3-02 laser altimetry data is experimented to validate the algorithm. The conclusion will be useful for the future domestic satellite laser altimeter.


2016 ◽  
Author(s):  
Kelly M. Brunt ◽  
Robert L. Hawley ◽  
Eric R. Lutz ◽  
Michael Studinger ◽  
John G. Sonntag ◽  
...  

2016 ◽  
Vol 31 (153) ◽  
pp. 88-107 ◽  
Author(s):  
Guoyuan Li ◽  
Xinming Tang ◽  
Xiaoming Gao ◽  
Huabin Wang ◽  
Yu Wang

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