Photon-counting distributed free-space spectroscopy

Spectroscopy is a well-established nonintrusive tool that has played an important role in identifying and quantifying substances,from quantum descriptions to chemical and biomedical diagnostics.Challenges exist in accurate spectrum analysis in free space,which hinders us from understanding the composition of multiple gases and the chemical processes in the atmosphere.A photon-counting distributed free-space spectroscopy is proposed and demonstrated using lidar technique,incorporating a comb-referenced frequency-scanning laser and a superconducting nanowire single-photon detector.It is suitable for remote spectrum analysis with a range resolution over a wide band.As an example,a continuous field experiment is carried out over 72 h to obtain the spectra of carbon dioxide(CO_(2))and semi-heavy water(HDO,isotopic water vapor)in 6 km,with a range resolution of 60 m and a time resolution of 10 min.Compared to the methods that obtain only column-integrated spectra over kilometer-scale,the range resolution is improved by 2-3 orders of magnitude in this work.The CO_(2)and HDO concentrations are retrieved from the spectra acquired with uncertainties as low as±1.2%and±14.3%,respectively.This method holds much promise for increasing knowledge of atmospheric environment and chemistry researches,especially in terms of the evolution of complex molecular spectra in open areas.

Confidence Measure of the Shallow-Water Bathymetry Map Obtained through the Fusion of Lidar and Multiband Image Data

With the advancement of Lidar technology,bottom depth(H)of optically shallow waters(OSW)can be measured accurately with an airborne or space-borne Lidar system(H_(Lidar) hereafter),but this data product consists of a line format,rather than the desired charts or maps,particularly when the Lidar system is on a satellite.Meanwhile,radiometric measurements from multiband imagers can also be used to infer H(H_(imager) hereafter)of OSW with variable accuracy,though a map of bottom depth can be obtained.It is logical and advantageous to use the two data sources from collocated measurements to generate a more accurate bathymetry map of OSW,where usually image-specific empirical algorithms are developed and applied.Here,after an overview of both the empirical and semianalytical algorithms for the estimation of H from multiband imagers,we emphasize that the uncertainty of H_(imager) varies spatially,although it is straightforward to draw regressions between H_(Lidar) and radiometric data for the generation of H_(imager).Further,we present a prototype system to map the confidence of H_(imager) pixel-wise,which has been lacking until today in the practices of passive remote sensing of bathymetry.We advocate the generation of a confidence measure in parallel with H_(imager),which is important and urgent for broad user communities.