KEYWORDS: Roads, Geographic information systems, Visualization, Signal attenuation, Data modeling, Visual analytics, Absorption, Data processing, Spatial analysis, Analytical research
Before building a new road, we need to predict the traffic noise generated by vehicles. Traditional traffic noise prediction methods are based on certain locations and they are not only time-consuming, high cost, but also cannot be visualized. Geographical Information System (GIS) can not only solve the problem of manual data processing, but also can get noise values at any point. The paper selected a road segment from Wenxi to Heyang. According to the geographical overview of the study area and the comparison between several models, we combine the JTG B03-2006 model and the HJ2.4-2009 model to predict the traffic noise depending on the circumstances. Finally, we interpolate the noise values at each prediction point and then generate contours of noise. By overlaying the village data on the noise contour layer, we can get the thematic maps. The use of GIS for road traffic noise prediction greatly facilitates the decision-makers because of GIS spatial analysis function and visualization capabilities. We can clearly see the districts where noise are excessive, and thus it becomes convenient to optimize the road line and take noise reduction measures such as installing sound barriers and relocating villages and so on.
In this contribution, we present a simple method based on Albedo-VI (vegetation index) triangular space to determine the Priestley-Taylor parameter for estimating evaporative fraction (EF) and evapotranspiration (ET) in arid and semi-arid regions. We apply this method to MODIS and observation data acquired during the Heihe river basin field experiment from July 1 to September 30, 2008. Results show that the decreasing trend of the estimated EF from MODIS data is consistent with that of precipitation during the period of day 183 to 274, 2008. The bias of estimated daily ET deviating from the corresponding ground-measured ET is −8.66 W/m2 and the root-mean-square error is 21.55 W/m2, indicating the Albedo-VI triangular method has a potential in ET estimation as a simple satellite-based method independent of surface ancillary data.
This paper presented a method for precisely computing the ground 2D size of any pixel in a satellite image received by a
push-broom linear array sensor, and further calculating the planar distance between any two pixels in the image. The
algorithm is deduced from the imaging principle of linear array sensors, with consideration of the arc of the earth's
surface, the height of ground, and the light refraction caused by the air. The author used the method to measure the
ground planar distance between two pixels in a Worldview-1 image, compared with the site measurement, the errors
were less than the size of pixel. As the computation is based on the instant position and orientation of the sensor, the
method is useful for local small area measuring and real time measuring.
Based on the image characteristics of Tianshan Mountains, using multi-temporal multi-band NOAA/AVHRR, MODIS
images, combined with high resolution CBERS-1/2 and ETM images, a model for estimating the area of snow cover and
the depth of snow cover at different places was proposed. The snow cover variation characteristics including the
distribution of snow cover, the depth of snow cover and the drawing method for snow cover were focused. Based on the
model, the snow cover of the area along Tianshan Highway from
1996-2006 was studied.
In this paper, a simple surface dryness index (Vegetation Condition Albedo Drought Index, VCADI) based on the spectral patterns of surface moisture in two dimensional spectral space of vegetation index versus broadband albedo is suggested. VCADI derived from multi-sources remote sensing data including the Thematic Mapper (TM), the Enhanced Thematic Mapper Plus (ETM+) and the MODerate Resolution Imaging Spectroradiometer (MODIS) images are significantly related to field measured soil moisture over different eco-systems. Spatio-temporal patterns of VCADI are further analyzed using time series of MODIS data over Ningxia Huizu Autonomous Region of China. Results indicate that VCADI variations are accordant with regional rainfall dynamics and the index has a potential in drought estimation as a simple satellite derived method completely independent of surface ancillary data.
Many types of feature extracting of RS image are analyzed, and the work procedure of pattern recognizing in RS images of seismic disaster is proposed. The aerial RS image of Tangshan Great Earthquake is processed, and the digital features of various typical seismic disaster on the RS image is calculated.
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