The impact of latent heating on the location and strength of the tropical easterly jet     

Samrat Rao  Jayaraman Srinivasan 《Meteorology and Atmospheric Physics》2016,128(2):247-261

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Combining landslide susceptibility maps obtained from frequency ratio,logistic regression,and artificial neural network models using ASTER images and GIS     

Jaewon Choi  Hyun-Joo Oh  Hong-Jin Lee  Changwook Lee  Saro Lee 《Engineering Geology》2012

Landslide-related factors were extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images, and integrated techniques were developed, applied, and verified for the analysis of landslide susceptibility in Boun, Korea, using a geographic information system (GIS). Digital elevation model (DEM), lineament, normalized difference vegetation index (NDVI), and land-cover factors were extracted from the ASTER images for analysis. Slope, aspect, and curvature were calculated from a DEM topographic database. Using the constructed spatial database, the relationships between the detected landslide locations and six related factors were identified and quantified using frequency ratio (FR), logistic regression (LR), and artificial neural network (ANN) models. These relationships were used as factor ratings in an overlay analysis to create landslide susceptibility indices and maps. Three landslide susceptibility maps were then combined and applied as new input factors in the FR, LR, and ANN models to make improved susceptibility maps. All of the susceptibility maps were verified by comparison with known landslide locations not used for training the models. The combined landslide susceptibility maps created using three landslide-related input factors showed improved accuracy (87.00% in FR, 88.21% in LR, and 86.51% in ANN models) compared to the individual landslide susceptibility maps (84.34% in FR, 85.40% in LR, and 74.29% in ANN models) generated using the six factors from the ASTER images.  相似文献   

Study of Ozone and NO2 over Gadanki – a rural site in South India     

K. Renuka  Harish Gadhavi  A. Jayaraman  Shyam Lal  M. Naja  S. V. Bhaskara Rao 《Journal of Atmospheric Chemistry》2014,71(2):95-112

We have studied long-term changes in tropospheric NO₂ over South India using ground-based observations, and GOME and OMI satellite data. We have found that unlike urban regions, the region between Eastern and Western Ghat mountain ranges experiences statistically significant decreasing trend. There are few ground-based observatories to verify satellite based trends for rural regions. However, using a past study and recent measurements we show a statistically significant decrease in NO_X and O₃ mixing ratio over a rural location (Gadanki; 13.48° N, 79.18° E) in South India. In the ground-based records of surface NO_X, the concentration during 2010–11 is found to be lower by 0.9 ppbv which is nearly 60 % of the values observed during 1994–95. Small but statistically significant decrease in noon-time peak ozone concentration is also observed. Noon-time peak ozone concentration has decreased from 34?±?13 ppbv during 1993–96 to 30?±?15 ppbv during 2010–11. NO_X mixing ratios are very low over Gadanki. In spite of low NO_X values (0.5 to 2 ppbv during 2010–11), ozone mixing ratios are not significantly low compared to many cities with high NO_X. The monthly mean ozone mixing ratio varies from 9 ppbv to 37 ppbv with high values during Spring and low values during late Summer. Using a box-model, we show that presence of VOCs is also very important in addition to NO_X in determining ozone levels in rural environment and to explain its seasonal cycle.  相似文献   

Landslide susceptibility mapping on Panaon Island,Philippines using a geographic information system   总被引：6，自引：3，他引：3  

Hyun-Joo Oh  Saro Lee 《Environmental Earth Sciences》2011,62(5):935-951

For landslide susceptibility mapping, this study applied, verified and compared the Bayesian probability model, the weights-of-evidence to Panaon Island, Philippines, using a geographic information system. Landslide locations were identified in the study area from the interpretation of aerial photographs and field surveys, and a spatial database was extracted from SRTM (Shuttle Radar Topographic Mission) DEM (Digital Elevation Model) imagery, aerial photograph, topographic map, and geological map. The factors that influence landslide occurrence, such as slope, aspect, curvature, topographic wetness index and stream power index of topography, were calculated from SRTM imagery. Distance from drainage was extracted from topographic database. Lithology and distance from fault were extracted and calculated from geological database. Terrain mapping unit was classified from aerial photographs. The spatial association between the factors and the landslides was calculated as the contrast values, W ⁺ and W ⁻ using the weights-of-evidence model. Tests of conditional independence were performed for the selection of the factors, allowing the large number of combinations of factors to be analyzed. For each factor rating, the contrast values, W ⁺ and W ⁻ were overlaid for landslide susceptibility mapping. The results of the analysis showed that contrast rating (78.60%) for each factor’s multiclass had better accuracy of 5.90% than combinations of factor assigned to binary class with W ⁺ and W ⁻ (72.70%).  相似文献   

A GIS-based logistic regression model in rock-fall susceptibility mapping along a mountainous road: Salavat Abad case study, Kurdistan, Iran   总被引：1，自引：0，他引：1  

Ataollah Shirzadi  Lee Saro  Oh Hyun Joo  Kamran Chapi 《Natural Hazards》2012,64(2):1639-1656

This study describes the application of logistic regression to rock-fall susceptibility mapping along 11?km of a mountainous road on the Salavat Abad saddle, in southwest Kurdistan, Iran. To determine the factors influencing rock-falls, data layers of slope degree, slope aspect, slope curvature, elevation, distance to road, distance to fault, lithology, and land use were analyzed by logistic regression analysis. The results are shown as rock-fall susceptibility maps. A spatial database, which included 68 sites (34 rock-fall point cells with value of 1 and 34 no rock-fall point cells with value of 0) was developed and analyzed using a Geographic Information System, GIS. The results are shown as four classes of rock-fall susceptibility. In this study, distance to fault, lithology, slope curvature, slope degree, and distance to road were found to be the most important factors affecting rock-fall. It was concluded that about 76?% of the study area can be classified as having moderate and high susceptibility classes. Rock-fall point cells were used to verify results of the rock-fall susceptibility map using success curve rate and the area under the curve. The verification results showed that the area under the curve for rock-fall susceptibility map is 77.57?%. The results from this study demonstrated that the use of a logistic regression model within a GIS framework is useful and suitable for rock-fall susceptibility mapping. The rock-fall susceptibility map can be used to reduce susceptibility associated with rock-fall.  相似文献   

Evidence from IRAS for a very young, partially formed dust band     

Ashley J. Espy  Stanley F. Dermott  Sumita Jayaraman 《Planetary and Space Science》2009,57(2):235-242

The relative proportions of asteroidal and cometary materials in the zodiacal cloud is an ongoing debate. The determination of the asteroidal component is constrained through the study of the Solar System dust bands (the fine-structure component superimposed on the broad background cloud), since they have been confidently linked to specific, young, asteroid families in the main belt. The disruptions that produce these families also result in the injection of dust into the cloud and thus hold the key to determining at least a minimum value for the asteroidal contribution to the zodiacal cloud. There are currently known to be at least three dust band pairs, one at approximately 9.35° associated with the Veritas family and two central band pairs near the ecliptic, one of which is associated with the Karin subcluster of the Koronis family. Through careful co-adding of almost all the pole-to-pole intensity scans in the mid-infrared wavebands of the Infrared Astronomical Satellite (IRAS) data set, we find strong evidence for a partial Solar System dust band, that is, a very young dust band in the process of formation, at approximately 17° latitude. We think this is a confirmation of the M/N partial band pair first suggested by Sykes [1988. IRAS observations of extended zodiacal structures. Astrophys. J. 334, L55-L58]. The new dust band appears at some but not all ecliptic longitudes, as expected for a young, partially formed dust band. We present preliminary modeling of the new, partial dust band which allows us to put constraints on the age of the disruption event, the inclination and node of the parent body at the time of disruption, and the quantity of dust injected into the zodiacal cloud.  相似文献   

Validation of an artificial neural network model for landslide susceptibility mapping   总被引：6，自引：3，他引：3  

Jaewon Choi  Hyun-Joo Oh  Joong-Sun Won  Saro Lee 《Environmental Earth Sciences》2010,60(3):473-483

The aim of this study was to validate an artificial neural network model at Youngin, Janghung, and Boeun, Korea, using the geographic information system (GIS). The factors that influence landslide occurrence, such as the slope, aspect, curvature, and geomorphology of topography, the type, material, drainage, and effective thickness of soil, the type, diameter, age, and density of forest, distance from lineament, and land cover were either calculated or extracted from the spatial database and Landsat TM satellite images. Landslide susceptibility was analyzed using the landslide occurrence factors provided by the artificial neural network model. The landslide susceptibility analysis results were validated and cross-validated using the landslide locations as study areas. For this purpose, weights for each study area were calculated by the artificial neural network model. Among the nine cases, the best accuracy (81.36%) was obtained in the case of the Boeun-based Janghung weight, whereas the Janghung-based Youngin weight showed the worst accuracy (71.72%).  相似文献   

Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia   总被引：15，自引：0，他引：15  

Saro Lee  Biswajeet Pradhan 《Journal of Earth System Science》2006,115(6):661-672

This paper deals with landslide hazards and risk analysis of Penang Island, Malaysia using Geographic Information System (GIS) and remote sensing data. Landslide locations in the study area were identified from interpretations of aerial photographs and field surveys. Topographical/geological data and satellite images were collected and processed using GIS and image processing tools. There are ten landslide inducing parameters which are considered for landslide hazard analysis. These parameters are topographic slope, aspect, curvature and distance from drainage, all derived from the topographic database; geology and distance from lineament, derived from the geologic database; landuse from Landsat satellite images; soil from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value from SPOT satellite images. Landslide susceptibility was analyzed using landslide-occurrence factors employing the probability-frequency ratio model. The results of the analysis were verified using the landslide location data and compared with the probabilistic model. The accuracy observed was 80.03%. The qualitative landslide hazard analysis was carried out using the frequency ratio model through the map overlay analysis in GIS environment. The accuracy of hazard map was 86.41%. Further, risk analysis was done by studying the landslide hazard map and damageable objects at risk. This information could be used to estimate the risk to population, property and existing infrastructure like transportation network.  相似文献   

Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models   总被引：28，自引：9，他引：28  

Saro Lee  Biswajeet Pradhan 《Landslides》2007,4(1):33-41

The aim of this study is to evaluate the landslide hazards at Selangor area, Malaysia, using Geographic Information System (GIS) and Remote Sensing. Landslide locations of the study area were identified from aerial photograph interpretation and field survey. Topographical maps, geological data, and satellite images were collected, processed, and constructed into a spatial database in a GIS platform. The factors chosen that influence landslide occurrence were: slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, land cover, vegetation index, and precipitation distribution. Landslide hazardous areas were analyzed and mapped using the landslide-occurrence factors by frequency ratio and logistic regression models. The results of the analysis were verified using the landslide location data and compared with probability model. The comparison results showed that the frequency ratio model (accuracy is 93.04%) is better in prediction than logistic regression (accuracy is 90.34%) model.  相似文献   

Comparison of landslide susceptibility maps generated through multiple logistic regression for three test areas in Korea     

Saro Lee 《地球表面变化过程与地形》2007,32(14):2133-2148

The aim of this study was to apply, verify and compare a multiple logistic regression model for landslide susceptibility analysis in three Korean study areas using a geographic information system (GIS). Landslide locations were identified by interpreting aerial photographs, satellite images and a field survey. Maps of the topography, soil type, forest cover, lineaments and land cover were constructed from the spatial data sets. The 14 factors that influence landslide occurrence were extracted from the database and the logistic regression coefficient of each factor was computed. Landslide susceptibility maps were drawn for these three areas using logistic regression coefficients derived not only from the data for that area but also using those for each of the other two areas (nine maps in all) as a cross‐check of method validity. For verification, the results of the analyses were compared with actual landslide locations. Among the nine cases, the Janghung exercise using the logistic formula and the coefficient for Janghung had the greatest accuracy (88·44%), whereas Janghung results, when considered by the logistic formula and the coefficient for Boeun, had the least accuracy (74·16%). Copyright © 2007 John Wiley & Sons, Ltd.  相似文献