Mega-earthquakes and extreme climate events accompanied by intrinsic fragile geology lead to numerous landslides along mountain highways in Taiwan, causing enormous life and economic losses. In this study, a system for rapid slope disaster information integration and assessment is proposed with the aim of providing information on landslide occurrence, failure mechanisms, and subsequent landslide-affected areas to the highway authority rapidly. The functionality of the proposed system is deployed into three units: (1) geohazard rapid report (GeoPORT I), (2) multidisciplinary geological survey report (GeoPORT II), and (3) site-specific landslide simulation report (GeoPORT III). After landslide occurrence, the seismology-based monitoring network rapidly provides the initial slope disaster information, including preliminary location, event magnitude, earthquake activity, and source dynamics, within an hour. Within 3 days of the landslide, a multidisciplinary geological survey is conducted to collect high-precision topographical, geological, and remote-sensing data to determine the possible failure mechanism. After integrating the aforementioned information, a full-scale three-dimensional landslide simulation based on the discrete element method is performed within 10 days to reveal the failure process and to identify the areas potentially affected by subsequent disasters through scenario modeling. Overall, the proposed system can promptly provide comprehensive and objective information to relevant authorities after the event occurrence for hazard assessment. The proposed system was validated using a landslide event in the Central Cross-Island Highway of Taiwan.
The urban heat island is considered as one of the most important climate change phenomena in urban areas, which can result in remarkable negative effects on flora, concentration of pollutants, air quality, energy and water consumption, human health, ecological and economic impacts, and even on global warming. The variation analysis of the surface urban heat island intensity (SUHII) is important for understanding the effect of urbanization and urban planning. The objective of this study was to present a new strategy based on the Shannon’s entropy and Pearson chi-square statistic to investigate the spatial and temporal variations of the SUHII. In this study, Landsat TM, ETM+, OLI and TIRS images, MODIS products, meteorological data, topographic and population maps of the Babol city, Iran, from 1985 to 2017, and air temperature data recorded by ground recorder devices in 2017 were used. First, Single-Channel algorithm was used to estimate land surface temperature (LST), and the maximum likelihood classifier was employed to classify Landsat images. Then, based on LST maps, surface urban heat island ratio index was employed to calculate the SUHII. Further, several statistical methods, such as the degree-of-freedom, degree-of-sprawl and degree-of-goodness, were used to analyse the SUHII variation along different geographic directions and in various time periods. Finally, correlation between various parameters such as air temperature, SUHII, population variation and degree-of-goodness index values were investigated. The results indicated that the SUHII value increased by 24% in Babol over different time periods. The correlation coefficient yielded 0.82 between the values of the difference between the mean air temperature of the urban and suburbs and the SUHII values for the geographic directions. Furthermore, the correlation coefficient between the population variation and the degree-of-goodness index values reached 0.8. The results suggested that the SUHII variation of Babol city had a high degree-of-freedom, high degree-of-sprawl and negative degree-of-goodness. 相似文献
P phase arrival picking of weak signals is still challenging in seismology. A wavelet denoising is proposed to enhance seismic P phase arrival picking, and the kurtosis picker is applied on the wavelet-denoised signal to identify P phase arrival. It has been called the WD-K picker. The WD-K picker, which is different from those traditional wavelet-based pickers on the basis of a single wavelet component or certain main wavelet components, takes full advantage of the reconstruction of main detail wavelet components and the approximate wavelet component. The proposed WD-K picker considers more wavelet components and presents a better P phase arrival feature. The WD-K picker has been evaluated on 500 micro-seismic signals recorded in the Chinese Yongshaba mine. The comparison between the WD-K pickings and manual pickings shows the good picking accuracy of the WD-K picker. Furthermore, the WD-K picking performance has been compared with the main detail wavelet component combining-based kurtosis (WDC-K) picker, the single wavelet component-based kurtosis (SW-K) picker, and certain main wavelet component-based maximum kurtosis (MMW-K) picker. The comparison has demonstrated that the WD-K picker has better picking accuracy than the other three-wavelet and kurtosis-based pickers, thus showing the enhanced ability of wavelet denoising. 相似文献
The aim of this work is to analyze the size-distribution and composition of nanoparticles in a water-extract of a podzol B horizon. AsFlowFFF coupled to ICP–MS and a UV/VIS detector was used for particle fractionation and simultaneous measurement of the composition of the nanoparticles. Detected nanoparticles were organic and mineral particles; the mineral particles were dominated by clay and Fe-(hydr)oxides. Both organic- and inorganic particles contributed to the mobility of Fe, Al, trace metals and P. For Zn, Pb and P respectively 73%, 92% and 72% of the colloidal concentrations were associated with clay minerals. The large contribution of clay particles to the mobility of trace metals and P can be partly explained by the high amount of dispersed clay due to drying, sieving and rewetting of the soil. Inorganic nanoparticles can contribute significantly to the mobility of metals and P in soils. 相似文献