Compared to traditional multi-spectral information, nighttime light data has more intuitive features and is more sensitive to feedback on human-acquired trends such as urban sprawl and industrial development. Therefore, this paper uses Shanghai as the study area and combines the 30m resolution land use raster data with the monthly NPP-VIIRS data to determine the threshold value using the spatial comparison method of higher resolution image data. The threshold dichotomy was used to extract the urban built-up areas from the nighttime light images, and the error was only 0.85 when compared with the statistical data.
KEYWORDS: Bridges, Point clouds, Data modeling, Safety, Data acquisition, 3D scanning, Feature extraction, Deformation, Laser applications, Error analysis
Bridge engineering construction is a kind of engineering construction with high risk. Only by building scientific and reasonable safety assessment and monitoring measures can the construction safety be improved and the risk be controlled. Based on the construction of a large cantilever steel truss traffic bridge project, this paper introduces the application of three-dimensional laser scanning technology in the monitoring of bridge transverse construction from the aspects of measuring point layout, monitoring scheme, scanning measurement and data analysis and processing. This paper introduces the bridge construction safety monitoring technology, as well as the content and steps of construction safety monitoring, and summarizes the measures of bridge construction safety assessment monitoring.
Remote sensing technology can quickly identify hydro thermal alteration related to mineralization and provide help for prospecting through efficient and accurate analysis. In this study, the Zhaoping fault zone is taken as the research area, Landsat8 OLI remote sensing images with good imaging quality are used as the data source, and ENVI software is used to perform pruning, radiometric calibration, atmospheric correction, and preprocessing of removing interference information including water and vegetation from remote sensing images in 2015 and 2020 respectively. The mineralized alteration information of this area is extracted by CROSTA method, and the extracted thematic information is analyzed and verified. In addition, by comparing the extraction maps of mineralization information in 2015 and 2020, it is found that the situation of over exploitation of mineral resources still exists. The results are in good agreement with the known ore points in the study area, indicating that the extraction of metal mineralization information through remote sensing images is of great significance to the study and rational utilization of mineral resources.
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