Computational fluid dynamics evaluation of the effect of different city designs on the wind environment of a downwind natural heritage site

Disturbance in wind regime and sand erosion deposition balance may lead to burial and eventual vanishing of a site.This study conducted 3D computational fluid dynamics(CFD)simulations to evaluate the effect of a proposed city design on the wind environment of the Crescent Spring,a downwind natural heritage site located in Dunhuang,Northwestern China.Satellite terrain data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)Digital Elevation Model(DEM)were used to construct the solid surface model.Steady-state Reynolds Averaged Navier-Stokes equations(RANS)with shear stress transport(SST)k-ωturbulence model were then applied to solve the flow field problems.Land-use changes were modeled implicitly by dividing the underlying surface into different areas and by applying corresponding aerodynamic roughness lengths.Simulations were performed by using cases with different city areas and building heights.Results show that the selected model could capture the surface roughness changes and could adjust wind profile over a large area.Wind profiles varied over the greenfield to the north and over the Gobi land to the east of the spring.Therefore,different wind speed reduction effects were observed from various city construction scenarios.The current city design would lead to about 2 m/s of wind speed reduction at the downwind city edge and about 1 m/s of wind speed reduction at the north of the spring at 35-m height.Reducing the city height in the north greenfield area could efficiently eliminate the negative effects of wind spee.By contrast,restricting the city area worked better in the eastern Gobi area compared with other parts of the study area.Wind speed reduction in areas near the spring could be limited to 0.1 m/s by combining these two abatement strategies.The CFD method could be applied to simulate the wind environment affected by other land-use changes over a large terrain.

Classification of full-polarization ALOS-PALSAR imagery using SVM in arid area of Dunhuang

Classification is an important process in interpretation of synthetic aperture radar （SAR） imagery. As an advanced instrument for remote sensing, the polarimetric SAR has been applied widely in many fields. The main aim of this paper is to explore the ability of the full-polarization SAR data in classification. The study area is a part of Dunhuang, Gansu Province, China. An L-band full-polarization image of Dunhuang which includes quad-polarization modes was acquired by the ALOS-PALSAR （Advanced Land Observing Satellite-the Phased Array type L-band Synthetic Aperture Radar）. Firstly, new characteristic information was extracted by the difference operation, ratio operation, and principal component transform based on the full-polarization （HH, HV or VH, VV） modes SAR data. Then the single-, dual-, full-polarization SAR data and new SAR characteristic information were used to analyze quantitatively the classification accuracy based on the Support Vector Machines （SVM）. The results show that classification overall accuracy of single-polarization SAR data is poor, and the highest is 56.53% of VV polarization. The classification overall accuracy of dual-polarization SAR is much better than single-polarization, the highest is 74.77% ofHV ＆ VV polarization data. The classification overall accuracy of full-polarization SAR is 80.21%, adding the difference characteristic information, ratio characteristic information and the first principal component （PC1） respectively, the overall accuracy increased by 3.09%, 3.38%, 4.14% respectively. When the full-polarization SAR data in combination with the all characteristic information, the classification overall accuracy reached to 91.01%. The full-polarization SAR data in combination with the band math characteristic information or the PC1 can greatly improve classification accuracy.

Methods for calculating glacier area and length in a mountainous area based on remote-sensing data and a digital elevation model

In a mountainous region, the glacier area and length extracted form the satellite imagery data is the projected area and length of the land surface, which can’t be representative of the reality; there are always some errors. In this paper, the methods of calculating glacier area and length calculation were put forward based on satellite imagery data and a digital elevation model (DEM). The pure pixels and the mixed pixels were extracted based on the linear spectral un-mixing approach, the slop of the pixels was calculated based on the DEM, then the area calculation method was presented. The projection length was obtained from the satellite imagery data, and the elevation differences was calculated from the DEM. The length calculation method was presented based on the Pythagorean theorem. For a glacier in the study area of western Qilian Mountain, northwestern China, the projected area and length were 140.93 km2 and 30.82 km, respectively. This compares with the results calculated by the methods in this paper, which were 155.16 km2 and 32.11 km respectively, a relative error of the projected area and length extracted from the LandSat Thematic Mapper (TM) image directly reach to -9.2 percent and -4.0 percent, respectively. The calculation method is more in accord with the practicality and can provide reference for some other object’s area and length monitoring in a mountainous region.

A method to obtain soil-moisture estimates over bare agricultural fields in arid areas by using multi-angle RADARSAT-2 data

Soil moisture is an important parameter for agriculture, meteorological, and hydrological studies. This paper focuses on soil-moisture estimation methodology based on the multi-angle high-and low-incidence-angle mode RADARSAT-2 data obtained over bare agricultural fields in an arid area. Backscattering of the high-and low-incidence angles is simulated by using AIEM(advanced integral equation model), with the surface-roughness estimation model built based on the simulated data. Combining the surface-roughness estimation model with the backscattering model of the low-incidence-angle mode, a soil-moisture estimation method is put forward. First, the natural logarithm(ln) of soil moisture was obtained and then the soil moisture calculated. Soil moisture of the study area in Dunhuang, Gansu Province, was obtained based on this method; a good agreement was observed between the estimated and measured soil moisture. The coefficient of determination was 0.85, and the estimation precision reached 4.02% in root mean square error(RMSE). The results illustrate the high potential of the approach developed and RADARSAT-2 data to monitor soil moisture.

Glacier extraction based on ASAR,DEM and texture feature of ASAR using SVM in the Western Qilian Mountains,Northwest China

This paper is focused on the method for extracting glacier area based on ENVISAT ASAR Wide Swath Modes （WSM） data and digital elevation model （DEM） data, using support vector machines （SVM） classification method. The digitized result of the glaci- er coverage area in the western Qilian Mountains was extracted based on Enhanced LandSat Thematic Mapper （ETM＋） imagery, which was used to validate the precision of glacier extraction result. Because of similar backscattering of glacier, shadow and wa- ter, precision of the glacier coverage area extracted from single-polarization WSM data using SVM was only 35.4%. Then, texture features were extracted by the grey level co-occurrence matrix （GLCM）, with extracted glacier coverage area based on WSM data and texture feature information. Compared with the result extracted from WSM data, the precision improved 13.2%. However, the glacier was still seriously confused with shadow and water. Finally, DEM data was introduced to extract the glacier coverage area. Water and glacier can be differentiated because their distribution area has different elevations; shadow can be removed from the classification result based on simulated shadow imagery created by DEM data and SAR imaging parameters; finally, the glacier coverage area was extracted and the precision reached to 90.2%. Thus, it can be demonstrated that the glacier can be accurately semi-automatically extracted from SAR with this method. The method is suitable not only for ENVISAT ASAR WSM imagery, but also for other satellite SAR imagery, especially for SAR imagery covering mountainous areas.