Annual urban change information is important for an improved understanding of urban dynamics and continuous modeling of urban ecosystem processes. This study examined Landsat-derived Normalized Difference Vegetation Index (NDVI) time series for characterizing annual urban change. To
reduce impacts from cloud contamination and missing data, United States Geological Survey (USGS) Landsat Analysis Ready Data were processed to derive annual NDVI layers using a maximum value composite algorithm. National Land Cover Database land cover products from 2001 and 2011 were used
as references for generating a decadal urban change mask. Within the decadal urban change mask and using annual NDVI as input, we examined three time-series change detection methods to pinpoint specific year of urban change: (a) minimum-value method, (b) break-point detection, and (c) simple-threshold
identification. For accuracy assessment, we divided change pixels into urbanization and urban-intensification pixel groups, defined by initial land cover types. We used Google Earth's High-Resolution Imagery Archive as primary reference data for detailed accuracy assessment. Overall, the urbanization
pixel group has good change detection accuracies of above 82% for all three change detection algorithms. The break-point detection method resulted in the highest overall accuracy of 88%. Overall accuracies for urban intensification pixel group were in the range of 35%–76%, depending
on choice of change detection algorithm, length of input time-series, and further division of pixel subgroups.
Based on the background of the Suzhou Metro Line 3 crossing the Line 1 operating tunnel, the finite element software MIDAS/GTS was used to perform 3D model and simulate the construction of the shield tunnel. The influence of shield tunnel penetration before and after strengthening on operating tunnels is studied. The research results show that the maximum settlement of the operating tunnel caused by underpass construction without reinforcement is 11.64mm, which exceeds the control value of 10mm, and deformation control measures must be taken. After reinforcement, the maximum settlement of the soil around Line 3 is only 5.65mm, the reduction of settlement about 50%, and the settlement control effect is obvious, which shows that it is feasible to take deformation control measures for pre-reinforcement of the soil around the tunnel.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.