Linyan Bai

Correlation for gas–liquid equilibrium prediction in Fischer–Tropsch synthesis

A correlation for the prediction of the solubilities of gaseous solutes in heavy waxes in Fischer–Tropsch synthesis was developed on the basis of cubic equation of state. The correlation can be used for the systems with a wide range of solutes, including CO, H2, CO2, CH4, C2H4 and C2H6, and heavy wax solvents from C20 to C61, and requires critical temperature and critical pressure together with molecular weight instead of the acentric factor of the corresponding pure compound as input information. By using a single binary interaction factor, it is sufficient for this correlation to represent a binary system over a wide range of temperatures and pressures. For 406 experimental data points of 29 binary systems from literature, the correlation can provide good approximations with an overall average absolute deviation less than 6%, which can meet the demands of the engineering design of Fischer–Tropsch process.

Epidemic risk analysis after the Wenchuan Earthquake using remote sensing

On 12 May 2008, Wenchuan Earthquake, magnitude 8.0, destroyed thousands of buildings, and resulted in thousands of people being buried in the collapsed buildings. In order to investigate the potential epidemic disease risk after earthquake, a Backward Propagation Neural Network (BPNN) was constructed to assess the potential epidemic risks by applying remote sensing technology to obtain Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) values, as well as by using a geographic information system (GIS) to gain ambient epidemic-related spatial factors over the earthquake region. In this study, a relationship was established between the change in environmental factors after earthquake and potential epidemic risks, which was found to be statistically significant. The result might be explained for three change perspectives, namely environmental risks, medical risks and psychological risks. The corresponding strategies for preparedness in case of epidemic disease were given.

Workload and task management of Grid-enabled quantitative aerosol retrieval from remotely sensed data

As the quality and accuracy of remote sensing instruments improve, the ability to quickly process remotely sensed data is in increasing demand. Quantitative retrieval of aerosol properties from remotely sensed data is a data-intensive scientific application, where the complexities of processing, modeling and analyzing large volumes of remotely sensed data sets have significantly increased computation and data demands. While Grid computing has been a prominent technique to tackle computational issues, little work has been done on making Grid computing adapted to remote sensing applications. In this paper, we intended to demonstrate the usage of Grid computing for quantitative remote sensing retrieval applications. A workload estimation and task partition algorithm was developed, and it executes a generic remote sensing algorithm in parallel over partitioned datasets, which is embedded in a middleware framework for remote sensing retrieval named the Remote Sensing Information Service Grid Node (RSIN). A case study shows that significant improvement of system performance can be achieved with this implementation. It also gives a perspective on the potential of applying Grid computing practices to remote sensing problems.

Simultaneous determination of aerosol optical thickness and surface reflectance using ASTER visible to near-infrared data over land

An innovative method for the determination of aerosol optical thickness (AOT) and surface reflectance for operational use of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) visible to near-infrared data is presented. This method is designed to obtain the atmospheric parameters needed in the correction of the image. This method is based on a simplified radiative transfer equation describing the relation between the ground surface reflectance, AOT and top-of-atmosphere reflectance. By exploiting the ASTER dual-angle view capabilities in band 3N (Nadir) and band 3B (Backwards), surface reflectance and AOT can be retrieved synchronously. Thus, it solves the problem of separating atmospheric radiance from the transmitted radiance of the surface to some extent. After applying this new atmospheric correction method to three areas of ASTER images, Beijing urban city, the Heihe River Basin and Hong Kong of China, ASTER surface reflectance products (AST07) were obtained. AOT values from in situ measurements of CIMEL Electronique 318 Sun Photometers or AERONET (AErosol RObotic NETwork) and surface reflectance in situ measured using an Analytical Spectral Device (ASD) Field Spec spectral radiometer are used for validation. AOT derived from the new method is consistent with in situ station measurements from CIMEL Electronique 318 Sun Photometer and level 2.0 data from AERONET, with correlation coefficient (R 2) of 0.98 and root mean square error of 0.05, whereas Multi-angle Imaging Spectroradiometer AOT products underestimate AERONET AOT and Moderate-Resolution Imaging Spectroradiometer AOT products overestimate AERONET AOT in these regions. More encouraging is the comparison between the corrected surface reflectance, AST07 and ASD measurements. Root mean square error of AST07 and retrieved surface reflectance are as follows: band 1 (556 nm) = 0.04 and 0.05; band 2 (661 nm) = 0.036 and 0.035; band 3 (807 nm) = 0.056 and 0.038, which suggests that compared with AST07 in bands 2 and 3, retrieved surface reflectance has better agreement with measured reflectance from ASD.

Aerosol optical depth retrieval over land using MODIS data and its application in monitoring air quality

Atmospheric remote sensing offers us a view to estimate air quality in describing the aerosol distribution either for a local or global coverage because aerosol parameters, such as aerosol optical depth (AOD) are significant indicators of the air quality. However, AOD retrieval over land still remains a difficult task because the measured signal is a composite of reflectance of sunlight by the variable surface covers and back scattering by the semitransparent aerosol layer. In this paper, an approach using bi-angle with Moderate Resolution Imaging Spectroradiometer (MODIS) data was presented. The derived AOD is compared to AERONET observations in the Asia area and a retrieval error within 16% is found. Moreover, a biomass burning episode in North China between June 7, 2007 was presented, it is demonstrated that AOD increased up to 2.0 during the burning phase and then returned to normal values (0.2–0.5), which fully in line with the observation result.

A new context-based procedure for the detection and removal of cloud shadow from moderate-and-high resolution satellite data over land

This paper has focused on a new automated detection and removal of cloud shadows of remotely sensed data to service quantitative interval of atmospheric parameters, using the FengYun-3 (FY-3), moderate spatial resolution and HuanJing-1 (HJ-1), high spatial resolution satellite data. Taking into account interaction between neighboring pixels in remote sensing images, this research aims at the special context relationships that are used to detect cloud shadows and then being carried out on related pixel match and cloud shadow removal. The tests show that the algorithm of detection and removal of cloud shadow is very simple and valid with the high discrimination accuracy and low leaking discrimination rate and so on, as well as yet associated with scale and scaling effect.

Synthetic retrieval of aerosol optical depth and surface reflectance using Terra and Aqua platforms in semi-arid regions

Aerosol quantitative retrieval from remote sensing over land surface is still a challenging task, especially for bright land areas such as desert, urban, coast, arid and semi-arid regions. A new aerosol optical depth (AOD) and surface reflectance remote sensing retrieval model is developed by exploiting a kernel-driven BRDF (Bidirectional Reflectance Distribution Function) model and the SYNTAM (Synergy of TERRA and AQUA MODIS) model, which considered the surface BRDF effect while retrieving AOD. After applying this new model to Terra and Aqua MODIS data in the Heihe River Basin of China, AOD and surface reflectance of this region are retrieved. Results show that the multiple correlation coefficient (R2) between retrieved AOD from MODIS and in situ measurements of CIMEL CE318 Sun-photometers is 0.92 at 0.55/zm. Using ASD Field Spec spectral radiometer measurements to validate retrieved surface reflectance, the RMSE values for band 1~3 are lower than 0.06.

Grid Enabled Simultaneous Retrieval of Aerosol and Ground Surface Reflectance from Integration of AERONET and Satellite Data

In this paper, a method using multi-resource remotely sensed data and ground base data for quantitative determination of aerosol optical properties was demonstrated. The model exploits the synergy of TERRA and AQUA MODerate resolution Imaging Spectrometer (MODIS) data, to simultaneously retrieve both Aerosol Optical Thickness (AOT) and surface reflectance. The ground station data routinely coming from AERosol Robotic NETwork (AERONET) of ground-based sun- and sky-scanning radiometers were assimilated as variables describing model initial states. To meet the increased computational needs caused by the complex and computational intensity, the algorithm was migrated to run as parallel processing on a Grid platform. Experimental results were presented with a realistic application, using data collected by MODIS over China mainland. The results show that Grid-enabled model allowed on-demand large volume of ground-based data assimilation with parameters, and achieved improvement both in retrieval accuracy and computing performance.

Nationwide aerosol optical thickness retrieval application using grid computing platform

Aerosol optical thickness retrieval (AOT) from remotely sensed data over land is still a difficult task because the solar light reflected by the Earth-atmospheric system mainly comes from the ground surface. A novel aerosol remote sensing model SYNTAM by exploiting the synergy of TERRA and AQUA MODIS data could be used to accomplish part of the task of aerosol retrieval over land, especially over higher reflective surface. This paper addressed the issue how the SYNTAM method is applied to the national wide MODIS data for retrieval of aerosol optical thickness over China. The retrieval process is time consuming and the EMS (enhanced memory systems) memory required is very high. To solve the problem, we adapted the SYTAM model to the Grid computing environment. First retrieval process is laid out. The process is decomposed into small steps in pipeline. Decomposing strategy does not consider the difference computability among the computing elements. A coordinator is in charge of load balance. And then the detailed data query, data pre-processing, job monitoring and post-processing are discussed. We have developed one middleware by which the retrieval algorithm can be parallel processed. Preliminary experiment of aerosol retrieval of nationwide range was conducted. The experimental results indicated the computational process had been accelerated in an effective way. Using Grid computing platform, wide range and real-time aerosol information can be retrieved.

Regional quantitative retrieval of aerosol optical depth by exploiting the synergy of VISSR and MODIS data

Atmospheric aerosol particles influence the Earths radiation balance directly by scattering of infrared energy and indirectly by modifying the properties of clouds through microphysical processes. For the sake of effectively monitoring it, many atmospheric aerosol observation networks are set up and provide associated informational services in the wide world. However, the aerosol optical depth show large spatial and temporal variations because of the variety of production (e.g., car exhaust, power plants, forest fires, evaporation from petroleum products, agriculture, natural living plants, dust storms, breaking ocean waves, volcanoes), transport and removal processes and the prevailing meteorological conditions. In this paper an algorithm is developed which retrieves the diurnal change of AOT by using MODIS and FY-2D satellite visible channel data. This research is helpful for understanding the forming mechanism, influence and controlling approach of atmospheric aerosol and necessary for establishing corresponding operational predicting system of haze weather, which will provide the stable scientific support for predicting haze weather and setting up the controlling standard and synthesis prevention countermeasure.