Atsuko Nonomura

Impact of land use and land cover changes on the ambient temperature in a middle scale city, Takamatsu, in Southwest Japan.

There is a lack of information on urban heat island impact on the thermal environment due to low populated urban sprawl, although densely populated urban sprawl impact has been identified by several researchers. The Takamatsu area has recently developed in a low populated urban sprawl style without any increase in population. This paper examined the impact of a low populated urban sprawl on the thermal environment through an analysis of the last 30 years data set and investigated the contribution of vegetation fraction and population density to the temperature trend. As a consequence, it was shown that one of the most significant causative factors of temperature increase is an expansion of non-vegetated area even without population growth. This result implied that vegetated zones should be maintained in urban areas in order to realize sustainable urbanization.

A replication of landslide hazard mapping at catchment scale

Landslide hazard assessment is a primary tool to understand the basic characteristics of slopes that are prone to landslides, especially during extreme rainfall. In this study, weights-of-evidence modelling a bivariate statistical method, and a logistic regression model, a multivariate statistical method, were used for landslide hazard mapping in two catchments of the Siwaliks in the Nepal Himalaya. Two typical catchments, Charnath and Jalad of the Siwaliks in easternNepal, were selected for the landslide hazard mapping. Both modelling approaches were applied by considering 10 intrinsic factors and one extrinsic factor. Mainly digital elevation model-based causative factors and field data were used to prepare data layers of landslide causative factors. In many approaches formodelling of landslide hazard in GIS, the model validation process is always dependent, and landslide data, which are used to calculate a landslide hazard index (LHI), are applied for verification. However, in this study, the LHI was calculated in one catchment (Jalad) and the same index for a different class of causative factors was applied for another catchment (Charnath), and the LHI wasverified. The verification results were very promising, with an independent prediction rate of about 75%. This validates weights-of-evidence and logistic regression models for landslide hazard assessment in the Siwaliks Range of Nepal.

Estimation Method of Amount of Tsunami Disaster Wastes during the 2011 off the Pacific Coast of Tohoku Earthquake

A huge amount of disaster wastes was accumulated along coastline areas of the Tohoku region by tsunami dur ing the 2011 off the Pacific coast of Tohoku Earthquake. Th e total amount of tsunami disaster wastes was estimated to be 26.7 million tons. This corresponds to 50 % of the total amount of the waste of Japan in 2009. Tohoku Earthquake caused widespread serious damage. Since the coastal area o f Tohoku region shapes a saw-toothed coastline, it is difficult to prepare large places for filling these disaster wastes. And a road for carrying to these treatment facilities i s not enough in Tohoku coast line area, most port facilit ies were damaged seriously. This means the dispose of disast er wastes is in extremely difficult in Tohoku region. Since a tsunami height in Shikoku region during nex t Tokai Earthquake or Nankai one will be larger than the Tohoku Earthquake, it can be anticipated that an am ount of disaster wastes in Shikoku is also very large. It i s very important to estimate an amount of tsunami disaster wastes for quick recover and revival of damaged areas. This paper describes a method of wastes amount estimation based on the officially announced data a nalyzed in GIS platform.

Wildfire damage evaluation by merging remote sensing with a fire area simulation model in Naoshima, Kagawa, Japan

Not only wildfire damage, but the failure of post-fire forest restoration is also one of the major threats for the conservation of forest ecosystems. Therefore, it is required to estimate wildfire damaged potential and recovery capacity to orientate the management of a post-fire community. The aim of our research is to estimate the resistibility against wildfire and the post-fire regeneration capacity by merging field observation data with Terra/ASTER Level1B satellite data and a fire area simulation model (FARSITE). As a result, the resistibility against wildfire and the post-fire regeneration capacity were high in the high prior-fire normalized differential vegetation index (NDVI) areas, where the trees had been thriving. Also, after the fire, the well developed surface soil (the A horizon) provided a good environment for resprouting from unburned stumps and the rhizome. It is suggested that the thriving forests have a strong resistance against wildfire and have large regeneration capacity.

A method for regionally mapping gravitationally deformed and loosened slopes using helicopter-borne electromagnetic resistivity data

Earthquake-induced deep-seated landslides are prone to occur at gravitationally deformed and loosened slopes. These slopes need to be identified for landslide susceptibility mapping and landslide risk assessment. Surface morphology is an effective factor for finding the slopes, but is not effective for estimating the degree and the area of loosening. Subsurface geophysical investigations are quite useful for determining subsurface geological structures in regions where loosening has occurred. In this study, a method was developed for regionally mapping gravitationally deformed and loosened slopes as earthquake-induced deep-seated landslide susceptible zones by differentiating from sound bedrocks in flexural toppled slopes. Using the helicopter-borne electromagnetic resistivity data, “average ruggedness of resistivity” was proposed as an index parameter for differentiating the loosened zones. The estimated loosened zones were compared with observed geomorphological features during field survey, and it is shown that “average ruggedness of resistivity” is a useful parameter for regional mapping of earthquake-induced deep-seated landslide susceptible slopes.

Hazard Mapping of Earthquake-Induced Deep-Seated Catastrophic Landslides Along the Median Tectonic Line in Shikoku by Using LiDAR DEM and Airborne Resistivity Data

Shikoku Island has been threatened by great earthquakes occurred along the Nankai Trough and the Median Tectonic Line. Estimated magnitude of the largest earthquake along the Nankai Trough is estimated 9.0. Estimated magnitude of the Median Tectonic Line Earthquakes in northeastern part of Shikoku is 8.0 or more. The great earthquakes might trigger deep-seated landsides and the huge amount of landslide debris might paralyze transportation and isolate villages in mountainous areas. In order to mitigate the damage, estimating the hazard and preparation is necessary. In this study, index of susceptibility for earthquake-induced deep-seated catastrophic landslides is proposed geologically and geomorphologically.

Susceptibility of slopes to earthquake-induced landslides: a new index derived from helicopter-borne electromagnetic resistivity and digital elevation data sets

In mountainous areas of Asia, huge earthquakes have triggered numerous landslides in recent decades. Estimating the susceptibility of slopes to landslide and the volume of potential landslide debris helps in planning for disaster risk management. We developed a new index to measure the susceptibility of slopes to earthquake-induced landslides by using helicopter-borne electromagnetic resistivity (HEM) survey data to quantify the looseness of bedrock and a digital elevation model to quantify the amplification of seismic waves by topography. In our study area around the Kanagi landslide (triggered by the 1707 Hoei earthquake), our new index showed that landslide susceptibility was low within the area of past landslides, but was higher in areas outside the scar of past landslides. Our results indicate that most of the loosened rock masses have been removed by past landslides, and the areas beyond the main landslide scar, where loosened bedrock remains, are now most susceptible to future earthquake-induced landslides. Our results indicate that this index may be effective in areas susceptible to landslides due to toppling failure and rock avalanches in loosened bedrock slopes.