A Generalized Accelerated Failure Time Model to Predict Restoration Time from Power Outages

Major disasters such as wildfire, tornado, hurricane, tropical storm, and flooding cause disruptions in infrastructure systems such as power and water supply, wastewater management, telecommunication, and transportation facilities. Disruptions in electricity infrastructure have negative impacts on sectors throughout a region, including education, medical services,financial services, and recreation. In this study, we introduced a novel approach to investigate the factors that can be associated with longer restoration time of power service after a hurricane. Considering restoration time as the dependent variable and using a comprehensive set of county-level data, we estimated a generalized accelerated failure time(GAFT) model that accounts for spatial dependence among observations for time to event data. The model fit improved by 12% after considering the effects of spatial correlation in time to event data. Using the GAFT model and Hurricane Irma's impact on Florida as a case study, we examined:(1) differences in electric power outages and restoration rates among different types of power companies—investor-owned power companies, rural and municipal cooperatives;(2) the relationship between the duration of power outage and power system variables;and(3) the relationship between the duration of power outage and socioeconomic attributes. The findings of this study indicate that counties with a higher percentage of customers served by investor-owned electric companies and lower median household income faced power outage for a longer time. This study identified the key factors to predict restoration time of hurricane-induced power outages, allowing disaster management agencies to adopt strategies required for restoration process.

A Subsection Shared Restoration Method for Long-Haul WDM Networks

A novel restoration scheme, Parted Path Shared Restoration (PPSR), was proposed. The major idea of PPSR is the strategy of ‘parted disposal’. PPSR keeps the advantage of Path Based Shared Restoration (PBSR) in utilization of capacity. In addition, the restoration time of PPSR is much less than that of PBSR. Furthermore, a satisfaction function was proposed to estimate the performance of PPSR. This function takes the utilization of capacity and restoration time into a harmonious and uniform frame. Through theoretical analysis and computer simulation, the performance of PPSR was demonstrated.

Spatio-temporal patterns of satellite-derived grassland vegetation phenology from 1998 to 2012 in Inner Mongolia, China

Spatio-temporal variations of vegetation phenology, e.g. start of green-up season（SOS） and end of vegetation season（EOS）, serve as important indicators of ecosystems. Routinely processed products from remotely sensed imagery, such as the normalized difference vegetation index（NDVI）, can be used to map such variations. A remote sensing approach to tracing vegetation phenology was demonstrated here in application to the Inner Mongolia grassland, China. SOS and EOS mapping at regional and vegetation type（meadow steppe, typical steppe, desert steppe and steppe desert） levels using SPOT-VGT NDVI series allows new insights into the grassland ecosystem. The spatial and temporal variability of SOS and EOS during 1998–2012 was highlighted and presented, as were SOS and EOS responses to the monthly climatic fluctuations. Results indicated that SOS and EOS did not exhibit consistent shifts at either regional or vegetation type level; the one exception was the steppe desert, the least productive vegetation cover, which exhibited a progressive earlier SOS and later EOS. Monthly average temperature and precipitation in preseason（February, March and April） imposed most remarkable and negative effects on SOS（except for the non-significant impact of precipitation on that of the meadow steppe）, while the climate impact on EOS was found to vary considerably between the vegetation types. Results showed that the spatio-temporal variability of the vegetation phenology of the meadow steppe, typical steppe and desert steppe could be reflected by the monthly thermal and hydrological factors but the progressive earlier SOS and later EOS of the highly degraded steppe desert might be accounted for by non-climate factors only, suggesting that the vegetation growing period in the highly degraded areas of the grassland could be extended possibly by human interventions.