Suchergebnisse

For the establishment of precise disaster prevention measures in response to the Nankai megathrust earthquakes predicted to occur in the future, it is necessary to conduct numerous earthquake simulations and evaluate the vulnerability of the urban environment quantitatively. This vulnerability is evaluated on the basis of factors such as the extent of damage from earthquakes, as well as the attributes of residents, urban infrastructure, and systems in the environment. In this study, we propose a sparse modeling (SpM)-based technique for the evaluation of potential damage to urban environments due to Nankai megathrust earthquakes in Japan. As explanatory variables, any variables related to urban environments in Kochi Prefecture are considered. The results show that, unlike the so-called "complex disaster" events, the number of critical variables that characterize damage states when external disaster forces data (e.g. estimated seismic motion and tsunami height) and urban environment data are available is low, regardless of the magnitude of damage. In other words, urban system variables selected for damage states may be extracted as variables indicating vulnerability to earthquake damage. In addition, we evaluated the characteristics of different cities by visualizing the SpM results on a radar chart. The proposed technique is useful for gaining a deeper understanding of the influence of urban environment variables on earthquake damages. Furthermore, it is expected that measures for improving urban system resilience will be explored based on the proposed technique.

This research develops an agent-based land-use model for shifting cultivation, where the spatial distribution of crop cultivation is dynamically determined by the relationship between demand and supply of crops. We apply and evaluate the model using statistical and geographic data from Luangprabang Province, Laos, where rice and other crops are cultivated in various forms, including shifting cultivation. Our model explicitly incorporates socioeconomic dimensions of shifting cultivation in which villages are assigned the role of decision makers. We evaluate the model by comparing the simulation results with the existing statistical data and remote sensing images from the 1990s. Our model provides reasonably satisfactory estimates of aggregate area and volume of each crop type at the provincial level. We also evaluate the model across differing spatial resolutions for shifting cultivation areas. We find that the model has limited explanatory power at higher spatial resolutions of 0.5 km to 2.5 km grid cells, but can account for the spatial patterns fairly well at more aggregate levels with the resolutions of 5 km to 10 km.