Ippei Harada

Urban air pollution monitoring using differential optical absorption spectroscopy (DOAS) and wind lidar

The technique of differential optical absorption spectroscopy (DOAS) is applied to monitor concentrations of nitrogen dioxide (NO2) and aerosol, the major pollutants in the urban atmosphere. Two DOAS paths with optical distances of a few kilometers have been set up in the Chiba city area. The spectra of visible radiation emitted from xenon flashlights installed on tall constructions are analyzed in comparison with the laboratory spectrum of NO2. The intensity stability of the light sources enables the retrieval of aerosol extinction along the paths. It is found that the temporal behavior of both pollutants is similar to those observed at nearby ground sampling stations, though the effect of difference in the observation height often appears. Wind Doppler lidar measurement has also been undertaken from an observation site near an industrial complex along the Tokyo Bay, suggesting the influence of wind direction on the pollutant concentrations observed in the region.

Multi-Scale Effect on Landscape Pattern Analysis Using Satellite Data with a Range of Spatial Resolutions

Multi-Scale Effect on Landscape Pattern Analysis Using Satellite Data with a Range of Spatial Resolutions In recent years, identifying the relationship between pattern and scale has emerged as a central issue in ecology and geography. Scale has been defined by grain or resolution but bias in results will occur if the scale is wrongly selected relevant to the landscape evaluation. In this research, satellite data of varying resolution, QuickBird (2.5m), ALOS/AVNIR-2 (10m), Terra/ASTER (15m) and Landsat/ETM+ (30m), were employed to analyze the scale effects of grain size. The research was implemented at Azeta, a typical rural landscape located in Sakura City, central Japan. Land-cover classifications were first implemented using the Maximum Likelihood Method on satellite data of varying resolution. Based on the results of these classifications, a number of landscape metrics imbedded in the FRAGSTATS were extracted for landscape pattern analysis. The results indicate that most landscape patterns show some degree of consistency and scaling relations such as power-law among the various satellite resolutions. The applicability of these various satellite data resolutions for landscape analysis in the target area was also evaluated.

A determination of the earthquake disaster area by object-based analysis using a single satellite image

The final goal of this study is to create data to support emergency efforts in a disaster affected area by locating damaged buildings shortly after the disaster. In this study, prioritizing the practicality of the method for emergency purposes, we designed a method only to use a single satellite image of an affected area, eliminating the use of complex algorithms and auxiliary data. The uniqueness of our method lies in the application of an object-based region segmentation to images and the use of features of objects obtained from texture, hierarchical and other information in order to extract damaged buildings. Out of 26 features resulting from the analysis of objects, we found one feature and three combinations of two different features that are effective in extracting damaged buildings, such as Rectangular fit, Homogeneity, Number of sub-objects/Area, and Length of longest of edge/Area.

The extraction of methane sources over the global area using satellite data

In this study, we determined the concentration of global methane (CH4) emission using SCIAMACHY data. We analyzed land and sea area to investigate the nine-year changes of CH4 concentration from 2003 to 2011. Where we subtracted the CH4 concentration in land and sea during 9 years. As a result, we found that the growth rate of global CH4 concentration is 3-5ppb/year in land. It was cleared that a big amount of CH4 emission concentration was found not only in paddy fields in the Northern Hemisphere but also in broadleaf evergreen areas in the Southern Hemisphere (Central Africa and South America).