Identification of landslide spatial distribution and their types along the Riviere Frorse Drainage Basin triggered by the earthquake in Haiti on 12 January 2010

Jinling Zhao 1, 2, 3*, Chuang Liu 1, Tingting Lv 1 and Lijun Dai 1

As secondary effects, a series of landslides were triggered by the earthquake that occurred in Haiti on January 12, 2010. In this research, Riviere Frorse drainage basin was selected as the study area where the landslides were very concentrated and caused very serious damage. Due to the formation characteristics of a landslide, obvious changes of vegetation and texture characteristics between preand post-earthquake make it possible to identify the landslides in the high-resolution remotely sensed images. First, the Normalized Difference Vegetation Index (NDVI) images of pre- and post-earthquake were derived and the NDVI difference image was computed to identify the potential landslides. Then, multi-temporal images (pre- and post-earthquake, their resolution range from 0.41 m to 1.0 m) from Google Earth and the Digital Elevation Model (DEM) as well as its derivative slope were used to find out the landslides and mark the spatial sites. Finally, in order to identify and calculate the landslide acreage, the object-oriented classification method was mainly used by using the pre-earthquake World View-2 images on August, 2009 (whose spatial resolution is 0.46 m) and the post-earthquake GeoEye-1 (whose spatial resolution is 0.41 m) images on January 13, 2010. As a result, 165 landslides were interpreted and four types were specified: 98 new landslides (54,132 m2), 35 expanded landslides (40,315 m2), 24 no obviously changed landslides (186,962 m2) and 8 no completely recovered landslides (5,618 m2).

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Validation of Numerical Typhoon Model using Both Near-ground and Aerial Elevation Wind Measurements

Zhu Le Dong, Zhao Lin *, Ge Yao Jun and Cao Shu Yang

Strong typhoon Krosa (0715) was born on 2 Oct., 2007 on Pacific Ocean east of the Philippines and landed at about 15:30 on 7 in the boundary mountain region of Fujian Province in China. After landing, Krosa descended to tropical cyclone affecting the whole inland region of Shanghai and Zhejiang Province. The wind data of Typhoon Krosa were recorded timely and simultaneously at a near ground elevation of 10m at Houjia-Town Meteorologic Station on Chongming Island of Shanghai and at an aerial elevation of 436m above ground on the World Financial Center under construction. The recorded wind data were then analyzed to get the turbulence characteristics and utilized to calibrate the typhoon field parameters in Shanghai region, including large scale Holland parameter β and roughness length z0 nearby observation location. It was demonstrated that the turbulence intensity of typhoon was rather high even at an aerial elevation of 436m and the corresponding gust factor increased significantly after the landing of typhoon whilst that at 10m height was not affected evidently by the landing due to the dominant influence of the local terrain. It was also found based on the aerial observation data that different values of Holland parameter β should be employed for the radial distributions of air pressure before and after the typhoon landing to obtain a rational numerical simulation of typhoon wind field for both near ground and aerial elevations.

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The Vertical Structure of Thermal Anomaly before Inner Mongolia Ms5.9 Earthquake

Guangmeng Guo* and Jie Yang

Thermal anomaly had been widely reported in the last 20 years, all of these researches focused on the horizontal range of the thermal anomaly, while the vertical structure is seldom reported. In this paper we studied the Ms5.9 earthquake at Inner Mongolia on August 16, 2003 with NCEP temperature data. The result showed that the temperature increased about 9oC in the epicentral area just 4 days before this quake and the temperature at 1000hpa is very close to the epicenter, nearly 50 km. From 1000 hpa to 700 hpa, the thermal anomaly became far away from the epicenter, about 150 km at 700 hpa. It seemed that the anomaly was affected by winds and we considered that when this data was used to make prediction, the best choice was to choose the 1000 hpa temperature

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Dısaster and Emergency Management Activities by Geospatial Tools with specıal reference to Turkey

Erden Turan

Geospatial tools have a great potential in disaster and emergency management (DEM) cycles in terms of saving lives, limiting damage and reducing the costs of the event. Because of the chaotic nature of emergencies, emergency managers need geospatial data and tools that are collected and distributed in the form of useful products to manage disasters/ emergencies without the minimum amount of confusion. The term ‘geospatial’ includes interdependent resources such as maps, data sets, tools and procedures. Spatial data, Maps, Geographic Information Systems (GIS), Spatial Decision Support Systems (SDSS) and clearinghouses, geolibraries, archives, geoportals and geobrowsers, can be taken into consideration as types of geospatial tools in the DEM field. GIS are able to integrate information from different sources, of scales, accuracies and formats, into a single source and they can facilitate modeling, mapping and spatial decision support. GIS and SDSS can be powerful tools for the purpose of analysis because each phase in the DEM cycle is geographically and spatially related to one another. The aim of the paper is to improve DEM activities using geospatial tools.

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