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ACHARYA TRI DEV,양인태,이동하 한국측량학회 2018 한국측량학회지 Vol.36 No.1
DEM (Digital Elevation Model) is a useful dataset which represents the earth surface. Beside many applications, production and frequent update of DEM is a costly task. Recently global satellite based DEMs are available which has huge potential for application. To check the accuracy, this study compares two global DEMs: AW3D30 (Advanced Land Observing Satellite World 3D 30m) and SRTM30 (Shuttle Radar Topography Mission Global 30m) with reference resampled LiDAR DEM 30m in a test area around Chuncheon, Korea. The comparison analysis was based on statistics of each DEM, their difference, profiles, slope, basin and stream orders. As a result, it is found that SRTM30 and AW3D30 were much similar but inconsistent in the test area compared to the LiDAR30 DEM. In addition, SRTM30 shows less difference with LiDAR30 compared to the AW3D30 DEM. But, DEMs should be very carefully examined for area which has temporal or season changes. For basin and stream analysis, global DEMs can be used only for regional scale analysis not local large scales.
Landslide Susceptibility Mapping using Relative Frequency and Predictor Rate along Araniko Highway
Tri Dev Acharya,이동하 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.2
Roads are important infrastructure that brings economic development in a nation by connecting different places. But, in Nepal, many roads are very vulnerable to landslides due to various reasons. Araniko Highway is one of the most landslide affected major road in Nepal lacking study in past. In this study, landslide susceptibility mapping along Dolalghat - Kodari section in Araniko Highway, Nepal, was done by integrating Relative Frequency (RF) and Predictor Rate (PR). PR was applied to the RF to quantify the prediction ability of the conditioning factors while producing Landslide Susceptibility Index (LSI). First, landslide inventory map of 314 landslides was prepared. Then, the database was divided into 70/30 ratio for the training and validating the model. After analysing thirteen landslide conditioning factors, susceptibility map produced using LSI was categorized into five classes. Finally, overall performance of the resulting map was assessed using the receiver operating characteristic curve technique. The success rate and prediction rate curve showed that the area under the curve for RF was 0.606 and 0.581 respectively. The result of this study showed a successful mapping of landslide susceptibility by integrating RF and PR.
Acharya, Tri Dev,Yang, In Tae,Lee, Dong Ha MYU K.K. 2018 Sensors and materials Vol.30 No.8
<P>With over four decades spent collecting spaceborne moderate-resolution imagery, Landsat represents the longest remote sensing mission in the world, and has had various applications. Land cover mapping is its heritage for research around the world. Landsat 8 continues the legacy of previous Landsat systems, with a new Operational Land Imager (OLI) sensor that has high spectral resolution and improved signal-to-noise ratio for better characterization of land cover. With improved quality, data size also increases. Hence, with limited research in adjusting data size, it is necessary to explore robust land cover classification techniques that produce accurate maps with more or fewer inputs. The Optimum Index Factor (OIF) is a statistic value that can be used to select the optimum combination of three bands in a satellite image that has the highest amount of information. In this study, we explore the land cover classification of OLI imagery based on OIF. Two test sites were selected around the hilly regions of Korea for OLI original composite, first-rank OIF composite, and OLI original with sum derivative of top-three OIF ranked composites. These three composites were classified with the well-known Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) classifiers. The results were then analyzed and compared on the basis of producer accuracy, user accuracy, overall accuracy, and kappa coefficient. The result shows that the first-ranked OIF with a three-band composite shows a similar classification accuracy in SVM and slightly less in SAM, while the ten-band composite with OLI original bands and the sum derivative of the top-three OIF rank shows the same result or a small improvement in SVM classification. OIF-derivative composites can be useful in classification problems depending on whether the minimum amount of data for a similar result or more data to achieve higher accuracy is preferred.</P>
Acharya, Tri Dev,Yang, In Tae,Lee, Dong Ha 대한공간정보학회 2016 대한공간정보학회지 Vol.24 No.2
Landslide is one of the natural hazards, triggered by rainfall or earthquake and it leads to damage and loss of properties and lives especially in hilly and mountainous regions. Inventory maps of the area is of much importance in order to understand the landslide phenomena in detail , conduct further studies on landslide, prepare susceptibility map and minimize risk.. Inventory maps of landslides can be constructed by several methods, using multiple images through visual interpretation, using algorithms in multi-spectral or SAR images or verification from field investigation. The possible methods were explored for Sindhupalchowk district of Nepal, which was struck by massive earthquake on 2015 and landslide inventory was prepared. The inventory was analyzed for its frequency over elevation, slope aspect and dominant soil classes and also the information value for their occurrence probability.