Numerical Experiment of Combined Infrared and Ultraviolet Radiation Remote Sensing to Determine the Profile and Total Content of Atmospheric Ozone

A new remote sensing method is described to determine the vertical distribution and total content of atmospheric ozone. The method combines surface infrared, satellite infrared and ultraviolet channels. The width of the infrared channels is 0.01 cm-1, less than Lorentz half-width at the earth's surface, rather than the present width, because these channels can obtain information about variations in the ozone profile below the profile main-peak. The numerical experiments show that the method has a satisfactory precision in determining total ozone content, just about I percent error, and vertical distribution from the earth to 65 km space. In addition, some semi-analysis functions lor calculating backscattered ultraviolet and a relaxation equation are described in this paper.

Progress and development on multi-parameters remote sensing application in earthquake monitoring in China

In this paper, the progress and development on remote sensing technology applied in earthquake monitoring research are summarized, such as differential interference synthetic aperture radar （D-InSAR）, infrared remote sensing, and seismo-ionospheric detecting. Many new monitoring data in this domain have been used, and new data processing methods have been developed to obtain high-precision images about crustal deformation, outgoing longwave radiation （OLR）, surface latent heat flux （SLHF）, and ionospheric parameters. The development in monitoring technology and data processing technique largely enriches earthquake research information and provides new tools for earthquake stereoscope monitoring system, especially on the space part. Finally, new developing trend in this area was introduced, and some key problems in future work were pointed out.

Formation cause of thermal infrared high temperature belt along Honghe fault and its relation to earthquakes

Aiming at two Dayao earthquakes with magnitude more than 6 occurred in 2003 in Yunnan Province, we analyzed and interpreted the NOAA satellite thermal infrared images of 1999, 2003 and 2004 in Chuandian region, and also calculated the annual variation of brightness temperature of the hot belt along Honghe fault to explore the formation cause of the high temperature belt and its relation to the earthquakes. The results show that the high temperature belt along Honghe fault is caused by geographic environment factors, such as water system and terrain. But the annual average brightness temperature of the belt in earthquake year of 2003 is clearly higher than that in no earthquake years of 1999 and 2004, this maybe indicates that the thermal activities of Honghe fault increase in earthquake years, and can cause the annual variation anomaly of brightness temperature. We can detect and monitor this thermal activities of Honghe fault before earthquake by analyzing and comparing the relative changes of thermal infrared brightness temperature of the hot belt in different years.

PMODTRAN:a parallel implementation based on MODTRAN for massive remote sensing data processing

MODerate resolution atmospheric TRANsmission(MODTRAN)is a commercial remote sensing(RS)software package that has been widely used to simulate radiative transfer of electromagnetic radiation through the Earth’s atmosphere and the radiation observed by a remote sensor.However,when very large RS datasets must be processed in simulation applications at a global scale,it is extremely time-consuming to operate MODTRAN on a modern workstation.Under this circumstance,the use of parallel cluster computing to speed up the process becomes vital to this time-consuming task.This paper presents PMODTRAN,an implementation of a parallel task-scheduling algorithm based on MODTRAN.PMODTRAN was able to reduce the processing time of the test cases used here from over 4.4 months on a workstation to less than a week on a local computer cluster.In addition,PMODTRAN can distribute tasks with different levels of granularity and has some extra features,such as dynamic load balancing and parameter checking.

Performance of the Large Field of View Airborne Infrared Scanner and its application potential in land surface temperature retrieval

The Large Field of View Airborne Infrared Scanner is a newly developed multi-spectral instrument that collects images from the near-infrared to long-wave infrared channels.Its data can be used for land surface temperature(LST)retrieval and environmental monitoring.Before data application,quality assessment is an essential procedure for a new instrument.In this paper,based on the data collected by the scanner near the Yellow River in Henan Province,the geometric and radiometric qualities of the images are first evaluated.The absolute geolocation accuracy of the ten bands of the scanner is approximately 5.1 m.The ground sampling distance is found to be varied with the whisk angles of the scanner and the spatial resolution of the images.The band-to-band registration accuracy between band one and the other nine bands is approximately 0.25 m.The length and angle deformations of the ten bands are approximately 0.67%and 0.3°,respectively.The signal-to-noise ratio(SNR)and relative radiometric calibration accuracy of bands 4,9,and 10 are relatively better than those of the other bands.Secondly,the radiative transfer equation(RTE)method is used to retrieve the LST from the data of the scanner.Measurements of in situ samples are collected to evaluate the retrieved LST.Neglecting the samples with unreasonable retrieved LST,the bias and RMSE between in situ LST measured by CE312 radiometer and retrieved LST are−0.22 K and 0.94 K,and the bias and RMSE are 0.27 K and 1.59 K for the InfReC R500-D thermal imager,respectively.Overall,the images of the Large Field of View Airborne Infrared Scanner yield a relatively satisfactory accuracy for both LST retrieval and geometric and radiometric qualities.

The ADV/ASV AATSR aerosol retrieval algorithm:current status and presentation of a full-mission AOD dataset

An advanced along-track scanning radiometer(AATSR)global multi-year aerosol retrieval algorithm is described.Over land,the AATSR dual-view(ADV)algorithm utilizes the measured top of the atmosphere(TOA)reflectance in both the nadir and forward views to decouple the contributions of the atmosphere and the surface to retrieve aerosol properties.Over ocean,the AATSR single-view(ASV)algorithm minimizes the discrepancy between the measured and modelled TOA reflectances in one of the views to retrieve the aerosol information using an ocean reflectance model.Necessary steps to process global,multiyear aerosol information are presented.These include cloud screening,the averaging of measured reflectance,and post-processing.Limitations of the algorithms are also discussed.The main product of the aerosol retrieval is the aerosol optical depth(AOD)at visible/near-infrared wavelengths.The retrieved AOD is validated using data from the surface-based AERONET and maritime aerosol network(MAN)sun photometer networks as references.The validation shows good agreement with the reference(r=0.85,RMSE=0.09 over land;r=0.83,RMSE=0.09 at coasts and r=0.96,RMSE=0.06 over open ocean).The results of the aerosol retrievals are presented for the full AATSR mission years 2002–2012 with seasonally averaged time series for selected regions.

Demonstration of uncertainty resulting from MODerate resolution Imaging Spectroradiometer-like geometries:an albedo case study

This research examines uncertainty in MODerate resolution Imaging Spectroradiometer(MODIS)observations,and demonstrates the direct influence of geometric distortions resulting from the standard practice of geolocating swath observations.MODIS observations vary dependent on the ground sample distance,which varies dependent on the view zenith angle that changes with every orbit.MODIS Level 2G(L2G)land products are generated by applying a geolocation algorithm that resamples the variable observation geometries to a consistent grid of fixed pixel size and location,a process which itself introduces variability associated with the changing observational footprint.For this study,broadband albedo was simulated for five validation sites,representing five distinct land cover types,exhibiting quantifiable variability,with additional seasonal variability exhibited in some sites.All site simulations exhibit compounded uncertainty attributable to the geometric distortion sufficient to influence climate models(i.e.ranges from 0.01 to 0.045 albedo).These results indicate there is a minimum level of uncertainty associated with the variable geometry that should be factored into L2Gbased products,particularly for nominal 250 m band data.Aggregating the data to coarser resolutions and smoothing the data through average resampling can mitigate the uncertainty.

Global operational land imager Landsat-8 reflectance-based active fire detection algorithm

A global operational land imager(GOLI)Landsat-8 daytime active fire detection algorithm is presented.It utilizes established contextual active fire detection approaches but takes advantage of the significant increase in fire reflectance in Landsat-8 band 7(2.20μm)relative to band 4(0.66μm).The detection thresholds are fixed and based on a statistical examination of 39 million non-burning Landsat-8 pixels.Multi-temporal tests based on band 7 reflectance and relative changes in normalized difference vegetation index in the previous six months are used to reduce commissions errors.The probabilities of active fire detection for the GOLI and two recent Landsat-8 active fire detection algorithms are simulated to provide insights into their performance with respect to the fire size and temperature.The algorithms are applied to 11 Landsat-8 images that encompass a range of burning conditions and environments.Commission and omission errors are assessed by visual interpretation of detected active fire locations and by examination of the Landsat-8 images and higher spatial resolution Google Earth imagery.The GOLI algorithm has lower omission and comparable commission errors than the recent Landsat-8 active fire detection algorithms.The GOLI algorithm has demonstrable potential for global application and is suitable for implementation with other Landsat-like reflective wavelength sensors.