Search

[ABSTRACT]Land subsidence is an environmental geological phenomenon that causes slow lowering of ground surface elevation. With this slow deformation in land comes great risks to buildings and infrastructures resulting in significant economic losses and in worst case scenarios loss of human life as well. Therefore, it is important to assess risk beforehand for proper risk management. The objective of this research is to assess risk in the areas affected by land subsidence in Kathmandu Valley, Nepal using Geographic Information System (GIS) processing. A land subsidence map of Kathmandu valley (from 2007 to 2010) has been generated using Differential synthetic aperture radar interferometry (D-InSAR) technique. Geophysical data, that includes the subsidence volume, land subsidence velocity and groundwater exploitation intensity of the affected area will be utilized to estimate the future land subsidence. Social data, that includes population density, gross domestic product/km2 and construction land proportion will be utilized to estimate the vulnerability. Finally, the estimated land subsidence and estimated vulnerability will be combined together to obtain a land subsidence risk map. Different cases with and without governmental prevention and reduction policy or action will also be employed to compare the differences. This result is expected to be useful for the government and interested stakeholders for better understanding of the prevailing situation and the changes that can be brought through interventions. The generated result will also be helpful for disaster prevention policy-making

[ABSTRACT]Soil moisture plays a very important role in earth's water cycle. In East Asia,there are so many different areas like desert,semiarid ,steppe and so on. Study on these leads to understand more about climate and land surface change in the future. Mircrowave remote sensing is a effective method to measure soil moisture in large areas. AMSR-E(Advanced Microwave Scanning Radiometer for EOS) is a sensor which provides timely,long-term,quality informations on land hydrology. In this study, we use AMSR-E(Koike Ver.5.31 )soil moisture dataset and APHRODITE 's Water Resources (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation)dataset, validate the AMSR-E(Koike Ver.5.31) soil moisture dataset, and analyse the temporal-spatial variations of soil moisture in arid regions of East Asia. This study shows two areas of China, XinJiang and Inner Mongolia as a example. We make soil moisture maximum value image of month and soil moisture minimum value image of month. And we find the difference by the two values subtraction. As a result, soil moisture maximum value of month minus soil moisture minium value of month is very large in arid region,and soil moisture memory is small. Soil moisture memory ,in essence the fact that soil can"remember "a wet or dry anomaly long after the condition responsible for the anomaly are forgotten by the atmosphere(Randal D.Koster 2001).AMSR-E(Koike Ver.5.31) can capture the characteristics of soil moisture in arid regions very well .In the temporal ,among four seasons, summer can show the better correlation between soil moisture and precipitation. In winter possiblly because there is snow on the ground and the reason will be clarified in the next research. In the spatial,the correlation between soil moisture and precipitation is lower in west inner mongolia than east part.( west part is dry than east part in inner mongolia). According to APHRODITE's feature, near APHRODITE observation point the correlation between soil moisture and precipitation is higher,far from the APHRODITE observation point the correlation between soil moisture and precipitation is lower.No doubt soil moisture is also be affected by many factors,like vegetation, surface temperature and so on. Their relationship will be analyzed in the next step.

[ABSTRACT]In the context of the Project 4, a partial results・ on area studies and advanced databases were presented in this paper. As a connection to Project 1, results of global surface changes detection were explained first to find the local surface changes. Several important outcomes were selected and gave brief explanation. To find and organize the achievements of area studies, spatial database should be developed. Final part of the paper reported the example of databases on spatial information.

[ABSTRACT]The Project 1 of the CEReS research project aims to understand the present situation and changes of global surface environment. This project is an integrated project of several sub-projects. This paper describes a framework of the Project 1 and its achievements which include Re-calibration of NOAA/AVHRR over Land, Production of global MOD IS data of 2003, Global land cover, Global percent tree cover and Behavior of a surface temperature/vegetation index (TVX) matrix derived from 10-day composite AVHRR images over monsoon Asia.

[ABSTRACT]Bortala River, originated from the Alatao Mountain in Xinjiang China, is supplied mainly by the melting snow. The annual melting snow is about 45% of the total annual run-off. The annual monthly maximum run-off usually occurs in June, run-off in April to June consists 60% of the total in snow-melt seasons. Temperature of the river basin has started to heat up since late 80s in last century, and the annual mean temperature raised from 5 .5 that is in 60s to 7.9 in 2000s, annual precipitation has been in the tendency of rising too, esp-ecially got its peak in springs. Along with the climatic warming, there has been an enormous change in the hydrological process of the river, it mainly includes that the monthly maximum run-off in June has -shifted to May, the total monthly run-off has increased about 15%, and the percentage of monthly melting snow in April to June in total run-off has raised from 60% to 70%. In the change tendency of long standing, raising of the temperature mainly occurs in winter, increasing of the precipitation in winter is also distinct, the hydrological process is mainly obvious decreasing of the run-off in summer and obvious increasing of the run-off in spring. Analysis by the image data of the same time shows that the hydrological process caused by climatic warming has already effected the land use/cover changes around the lake Ebnur that situated in the lower reaches of the river.

[ABSTRACT]Primary function of Center for Environmental Remote Sensing (CEReS) is to provide satellite dataset such as GMS, MTSAT-IR, and NOAA/AVHRR for research community. We started data archive system (DAS) re-construction since 2005. New DAS based on PC servers and RAID storages with Free Operi Source Software (FOSS). Such configuration changes allow us to easy-expansion of DAS and random data access via 1intemet, thus downloaded files by users have been increased since 2005. In addition, activities of Virtual Laboratory (VL) for diagnosing the climate system accelerate the volume of archived satellite data since 2007. Our primary task in VL is collection and utilizations of geostationary meteorological satellites, thus we re-process raw full-disk data into grided format (after geometric correction) and open through the internet. Such data processing is not only contributed to VL also related communities. We will play an important role as one of data active archive center (DAAC) in Asia for satellite and related dataset.

[ABSTRACT]Indo-Japanese lidar system established over a tropical station, Gadanki (13.5 N,79.2 E), India is in operation since 1998.Using this system regular observations of upper troposphere clouds, and aerosols at stratospheric heights were made. The Moderate Resolution Imaging Spectroradiometer (MODIS) measurements on the Terra spacecraft are also used for remote sensing of high altitude clouds aerosols from space. Data collected using the polarization lidar during the period 1998-2004 are selected for systematic investigation and presentation. Several tropical cirrus cloud structures have been identified with low to moderate ice content. Occasionally thin sub visible clouds in the vicinity of tropical tropopause have been identified. Lidar observations clearly show occurrence of cirrus clouds over this station with varying thickness. The interseasonal variation of cirrus occurrence frequencies shows much of the occurrences during the monsoon season. The aerosol measurements in the upper troposphere and lower stratosphere show low aerosol content with vertical distribution upto 35km altitude. Scattering ratio (SR) and aerosol extinction are found to exhibit seasonal and interannual variations in upper troposphere (UT) and lower stratosphere(LS).SR in UT in 2001 and 2004 during winter is lower than that of summer, while LS winter profiles are found to have higher SR values apparently experience a shift in altitude corresponding to the seasonal change in tropapause indicating a relation between the two. The correlation observations made using MODIS satellite are compared with lidar data for systematic statistical study.