Using more than three million Landsat satellite images, this research developed the first global impervious surface area (GISA) dataset from 1972 to 2019. Based on 120,777 independent and random reference sites from 270 cities all over the world, the omission error, commission error, and F-score of GISA are 5.16%, 0.82%, and 0.954, respectively. Compared to the existing global datasets, the merits of GISA include: (1) It provided the global ISA maps before the year of 1985, and showed the longest time span (1972–2019) and the highest accuracy (in terms of a large number of randomly selected and third-party validation sample sets); (2) it presented a new global ISA mapping method including a semi-automatic global sample collection, a locally adaptive classification strategy, and a spatio-temporal post-processing procedure; and (3) it extracted ISA from the whole global land area (not from an urban mask) and hence reduced the underestimation. Moreover, on the basis of GISA, the long time series global urban expansion pattern (GUEP) has been calculated for the first time, and the pattern of continents and representative countries were analyzed. The two new datasets (GISA and GUEP) produced in this study can contribute to further understanding on the human’s utilization and reformation to nature during the past half century, and can be freely download from http://irsip.whu.edu.cn/resources/dataweb.php.
Many applied dispersion models require the knowledge of boundary-layer parameters such as sensible heat flux,QH, friction velocity,u*, and turbulent energy components, w and v. Formulas are suggested for calculating these parameters over a wide variety of types of ground surfaces, based on simple observations of wind speed near the ground and fractional cloud cover, and specification of constants such as roughness length, albedo, and soil moisture availability. Observations ofu*,QH, w, and v during field experiments in St. Louis and Indianapolis are used to test the formulas for urban sites. Relative errors of about ±20% in the predictions are seen to occur whenu*,QH, w, and v are large. However, when these quantities are small (e.g.,u* < 0.2 m/s), the errors in the predictions are as large as the mean value of the quantity itself.In addition, it is concluded from studies of available field data and theories that the magnitude of w is not well-known at elevations above about 100m during the late afternoon and night. Some simple parameterizations for w. are suggested that are consistent with the observed steady decrease in ground-level concentration in the afternoon and the sudden increase in concentration that can occur a few hours after sunset due to wind shears associated with a low-level jet, for continuous plumes emitted from moderate to tall stacks. 相似文献
Debris flows have caused serious loss of human lives and a lot of damage to properties in Taiwan over the past decades. Moreover, debris flows have brought massive mud causing water pollution in reservoirs and resulted in water shortage for daily life locally and affected agricultural irrigation and industrial usages seriously. A number of methods for prediction of debris flows have been studied. However, the successful prediction ratio of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for occurrence predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 178 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 93.82% demonstrates that the presented ANN model with seven significant factors can provide a stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems. 相似文献
Substantial damage to water supply systems, including water delivery pipelines, water treatment plants, reservoirs, and water
storage tanks, was reported after the 1999 Chi–Chi Taiwan Earthquake. This paper first summarizes the damage survey and then
presents the results of seismic fragility analysis for underground pipelines. Construction blueprints of the water delivery
pipelines and repair work orders of 11 townships and cities in the disastrous area were digitized into a Geographical Information
System (GIS) for analysis and assessment. With the aid of the GIS system, we found that PVC pipes made up 86% of water delivery
pipelines while steel, cast iron, ductile iron, PE and others took the rest. Therefore, this paper focuses on the fragility
analysis of PVC pipes. Three different methods were applied to derive the fragility relations between the PVC water pipes
having nominal diameters (approximately inner diameters) greater than or equal to 65 mm and earthquake intensity parameters
such as peak ground acceleration and peak ground velocity. The results were then examined with those of other countries. The
discrepancy between our results and the empirical equation used by HAZUS, an earthquake loss estimation software developed
by the Federal Emergency Management Agency was not significant. 相似文献
A shakemap system providing rapid estimates of strong ground shaking could be useful for emergency response providers in a
damaging earthquake. A hybrid procedure, which combines site-dependent ground motion prediction models and the limited observations
of the Real-Time Digital stream output system (RTD system operated by Central Weather Bureau, CWB), was set up to provide
a high-resolution shakemap in a near-real-time manner after damaging earthquakes in Taiwan. One of the main factors that affect
the result of ground motion prediction analysis is the existence of site effects. The purpose of this paper is to investigate
the local site effects and their influence in the ground shaking and then establish an early estimation procedure of potential
hazard for damaging earthquakes. Based on the attenuation law, the site effects of each TSMIP station are discussed in terms
of a bias function that is site and intensity-level dependent function. The standard deviation of the site-dependent ground
motion prediction model can be significantly reduced. The nonlinear behavior of ground soil is automatically taken into account
in the intensity-level dependent bias function. Both the PGA and the spectral acceleration are studied in this study. Based
on the RTD data, event correctors are calculated and applied to precisely estimate the shakemap of damaging earthquakes for
emergency response. 相似文献