Lop Nur, as the center of China and Eurasia, has a special position in geoscience research. The objective of this paper is to give a comprehensive and reasonable explanation of how the unique Lop Nur Ear feature formed. Because of the severe natural environment, the extensive area, and the difficult field work conditions, remote sensing data are highly suitable for the study of the Lop Nur lake basin. Three types of multisource remote sensing data are applied in this study. Combined with field investigations and laboratory measurements, the causes of the “Ear” feature are explored from different points of view. The results indicate that surface roughness is the most direct cause, while the salinity and depth of the subsurface dry medium layer are the root causes, and topography is an important environmental factor for the formation of the Lop Nur Ear feature. The results of this study help to solve a geological mystery and also provide a new insight into climate change and the demise of ancient civilizations.
The application of synthetic aperture radar (SAR) in urban areas is far from resolved with an increased spatial resolution, so building extraction from SAR images remains a difficult task. According to SAR imaging principles, the outline of a building is usually incomplete in a single-aspect SAR image, and microwave interactions between adjacent targets further complicate this phenomenon in urban areas. Thus, in this study, dual-aspect high-resolution SAR images obtained, respectively from ascending and descending orbits are introduced to extract the building footprints in urban areas, and a method for building footprint extraction based on the fusion of dual-aspect SAR images is proposed. First these dual-aspect SAR images are co-registered, and then the preliminary positions of each potential building are determined using Markov random field models and Hough transform. Next the test images are partitioned into several subimages that contain only one building target. Then the edge of a building is extracted within the subimage of each aspect using a region-growing method and gradient algorithm, and then detection results obtained from each aspect are fused to produce the ultimate outline of the buildings based on Dempster-Shafer evidence theory. Experiments using TerraSAR-X images demonstrate that this method can extract the complete footprint of buildings in urban areas and can also improve the accuracy when estimating the dimensions of buildings.
In this paper, a simulation method is introduced to generate synthetic aperture radar (SAR) image based on ray tracing
algorithm. 3D models of buildings, which are triangulated and described with vectors, are introduced into the simulator
and then the simulated images can be generated under different viewing configuration. The simulation consists of three
steps -modeling of the scene, tracing and generation of high resolution SAR images. 3D models of man-made objects are
illuminated by a virtual antenna whose signal is simplified by rays sent to the objects and back to the sensor. Then the
intensity map of rays is gridded into the SAR images. In the end, two buildings, one with a plane roof and the other with
a gable roof, are imported into the simulator under different viewing configuration. The effects of layover, shadow and
double bounce are simulated correctly in geometrically. So the simulator can be used for some interpret complex SAR
images which are composed of buildings.
This article analyses nowadays in common use of football robots in China, intended to improve the football robots'
hardware platform system's capability, and designed a football robot which based on DSP core controller, and combined
Fuzzy-PID control algorithm. The experiment showed, because of the advantages of DSP, such as quickly operation,
various of interfaces, low power dissipation etc. It has great improvement on the football robot's performance of
movement, controlling precision, real-time performance.
Urban forest is of great interest to a variety of scientific and urban planning applications. This paper presents a strategy for monitoring urban forest using Landsat TM/ETM+ (Thematic Mapper / Enhanced Thematic Mapper Plus) imagery time series and calculating its ecological benefits. And the strategy is applied to the temporal analysis of the zone inside the 4th Ring Road in Beijing. The analysis consists of two key steps in: the first is to extract urban forest from Landsat images; the second is to calculate the ecological benefits of urban forest. The extraction of urban forest from Landsat imagery is accomplished implementing classification models, which are based on empirical relationships between forest coverage and the spectrum on Landsat imagery, and are generated using regression tree techniques. Quickbird images and field investigations are applied to generate classification models and to assess their accuracies. Subsequently, the ecological benefits calculation about urban forest is carried out introducing CITYgreen model. This paper mainly concerns carbon storage and the function in air pollution reduction. In the following part, the results of the analysis are presented, as well as the figures that illustrate their variations. At the end, the advantages and disadvantages of this strategy are discussed.
The tropical and subtropical regions are characterized by their extraordinary resource environment, weather and climate. So the spaceborne synthetic aperture radar (SAR) with all day and all weather imaging capability has particular function to detect these regions. The available spaceborne radar systems take into consideration observing the tropical and subtropical regions, however, until recently, there has not been the professional radar satellite for observing these regions. This paper proposed the concept of TSARSAT (Tropical SAR Satellite), and analyzed its technological characteristics. The radar satellite will play an important role in rice growth monitoring and yield estimation, tropical rain forest monitoring, disaster monitoring and warning, ocean detection, coast belt surveying and topography mapping.