Landslide Geoanalytics Using LiDAR-derived Digital Elevation Models

Landslides are natural hazards that contribute to tremendous economic loss and result in fatalities if there is no well-prepared mitigation and planning. Assessing landslide hazard and optimizing quality to improve susceptibility maps with various contributing factors remain a challenge when working with various geospatial datasets. Also, the system of updating landslide inventories which identify geometry, deformation, and type of landslide with semi-automated computing processes in the Geographic Information System (GIS) can be flawed. This study explores landslide geoanalytics approaches combined with empirical approach and powerful analytics in the Zagros and Alborz Mountains of Iran. Light Detection And Ranging (LiDAR)-derived Digital Elevation Models (DEMs), Unmanned Aerial Vehicle (UAV) images, and Google Earth images are combined with the existing inventory dataset. GIS thematic data in conjunction with field observations are utilized along with geoanalytics approaches to accomplish the results. The purpose of this study is to explore the challenges and techniques of landslide investigations. The study is carried out by studying stream length-gradient (SL) index analysis in order to identify tectonic signatures. A correlation between the stream length-gradient index and the graded Dez River profile with slopes and landslides is investigated. By building on the previous study a quantitative approach for evaluating both spatial and temporal factors contributing to landslides for susceptibility mapping utilizing LiDAR-derived DEMs and the Probability Frequency Ratio (PFR) model is expanded. Furthermore, the purpose of this study is to create an algorithm and a software package in MATLAB for semi-automated geometric analysis to measure and determine the length, width, area, and volume of material displacement and flow direction, as well as the type of landslide. A classification method and taxonomy of landslides are explored in this study. LiDAR-derived DEMs and UAV images help to characterize landslide hazards, revise and update the inventory dataset, and validate the susceptibility model, geometric analysis, and landslide deformation. This study makes the following accomplishments and contributions: 1) Operational use of LiDAR-derived DEMs for landslide hazard assessment is estimated, which is a realistic ambition if we can continue to build on recent achievements; 2) While a steeper gradient could potentially be a signature for landslide identification, this study identifies the geospatial locations of high-gradient indices with potential to landslides; 3) An updated inventory dataset is achieved, this study indicates an improved landslide susceptibility map by implementing the PFR model compared to the existing data and previous studies in the same region. This study shows that the most effective factor is the lithology with 13.7% positive influence; and 4) This study builds a software package in MATLAB that can a) determine the type of landslide, b) calculate the area of a landslide polygon, c) determine and measure the length and width of a landslide, d) calculate the volume of material displacement and determine mass movement (i.e. deformation), and e) identify the flow direction of a landslide material movement. In addition to the contributions listed above, a class taxonomy of landslides is introduced in this study. The relative operating characteristic (ROC) curve method in conjunction with field observations and the inventory dataset are used to validate the accuracy of the PFR model. The validation of the result for susceptibility mapping accuracy is 92.59%. Further, the relative error method is applied to validate the performance of relative percentage of error of the selected landslides computing in the proposed software package. The relative percentage of error of the area, length, width, and volume is 0.16%, 1.67%, 0.30%, and 5.50% respectively, compared to ArcGIS. Marzan Abad and Chalus from Mazandaran Province of Iran and Madaling from Guizhou Province of China are used for validating the proposed algorithm

Crystallinity, Magnetic and Electrical Properties of Bi doped LaVO3

We report the results of crystal structure, magnetization and resistivity measurements of Bi doped LaVO3. X-ray diffraction (XRD) shows that if doping Bi in the La site is less than ten percent, the crystal structure of La1-xBixVO3 remains unchanged and its symmetry is orthorhombic. However, for higher Bi doping (>10%) composite compounds are found where the XRD patterns are characterized by two phases: LaVO3+V2O3. Energy-dispersive analysis of the x-ray spectroscopy (EDAX) results are used to find a proper atomic percentage of all samples. The temperature dependence of the mass magnetization of pure and single phase doped samples have transition temperatures from paramagnetic to antiferromagnetic region at TN=140 K. This measurement for bi-phasic samples indicates two transition temperatures, at TN=140 K (LaVO3) and TN=170 K (V2O3). The temperature dependence of resistivity reveals semiconducting behavior for all samples. Activation energy values for pure and doped samples are extracted by fitting resistivity versus temperature data in the framework of thermal activation process

Sulfur Dioxide Preserves Superoxide Dismutase and Catalase Activities in Acute Kidney Injury

Background: Acute kidney injury (AKI) is a major clinical problem in situations such as shock, sepsis, and kidney transplantation, and also occurs as a side effect of some drugs. Gentamicin (GM) is an effective antibiotic against severe gram-negative infections. However, it can produce AKI in humans. Reactive oxygen species (ROS) have been proposed as the causative factor for the renal side effects of GM. This study was performed to investigate the protective role of sulfur dioxide (SO2) against GM-induced acute kidney injury in rats.Methods: Male Wistar rats were randomly assigned to one of the following groups: 1, sham group; 2, GM group (100 mg/kg i.p. for 7 days); and 3, GM+SO2 group (5 μg/kg i.p. for 7 days). On day 8, renal tissues were collected for oxidative stress assessment. To compare the groups, superoxide dismutase (SOD) and catalase (CAT) in renal tissue were measured.Results: GM caused significant acute kidney injury as demonstrated by the increase in BUN and creatinine levels in plasma. The decrease in renal tissue SOD and CAT levels revealed that oxidative stress occurred in the kidney. In the GM+SO2 group, SO2 prevented GM-induced reduction in SOD and CAT levels to some extent.Conclusions: These findings suggest that SO2 partly protects the kidneys from GM-induced nephrotoxicity by its antioxidant effect

Landslide hazard and risk analyses at a landslide prone catchment area using statistical based geospatial model.

This paper presents the application of remote sensing techniques, digital image analysis and Geographic Information System tools to delineate the degree of landslide hazard and risk areas in the Balik Pulau area in Penang Island, Malaysia. Its causes were analysed through various thematic attribute data layers for the study area. Firstly, landslide locations were identified in the study area from the interpretation of aerial photographs, satellite imageries, field surveys, reports and previous landslide inventories. Topographic, geologic, soil and satellite images were collected and processed using Geographic Information System and image processing tools. There are 12 landslide-inducing parameters considered for the landslide hazard analyses. These parameters are: topographic slope, topographic aspect, plan curvature, distance to drainage and distance to roads, all derived from the topographic database; geology and distance to faults, derived from the geological database; landuse/landcover, derived from Landsat satellite images; soil, derived from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value, derived from SPOT satellite images. In addition, hazard analyses were performed using landslide-occurrence factors with the aid of a statistically based frequency ratio model. Further, landslide risk analysis was carried out using hazard map and socio-economic factors using a geospatial model. This landslide risk map could be used to estimate the risk to population, property and existing infrastructure like transportation networks. Finally, to check the accuracy of the success-rate prediction, the hazard map was validated using the area under curve method. The prediction accuracy of the hazard map was 89%. Based on these results the authors conclude that frequency ratio models can be used to mitigate hazards related to landslides and can aid in land-use planning

Coupling of DEM and remote-sensing-based approaches for semi-automated detection of regional geostructural features in Zagros mountain, Iran.

In recent years, remote-sensing data have increasingly been used for the interpretation of objects and mapping in various applications of engineering geology. Digital elevation model (DEM) is very useful for detection, delineation, and interpretation of geological and structural features. The use of image elements for interpretation is a common method to extract structural features. In this paper, linear features were extracted from the Landsat ETM satellite image and then DEM was used to enhance those objects using digital-image-processing filtering techniques. The extraction procedures of the linear objects are performed in a semi-automated way. Photographic elements and geotechnical elements are used as main keys to extract the information from the satellite image data. This paper emphasizes on the application of DEM and usage of various filtering techniques with different convolution kernel size applied on the DEM. Additionally, this paper discusses about the usefulness of DEM and satellite digital data for extraction of structural features in SW of Zagros mountain, Iran

Challenges of solid waste management in Malaysia

Malaysia is faced with challenges with respect to the solid waste management sector because of the increase of population and tourism, economic growth for sustainable development and inadequate waste legislation enforcement, infrastructure and public attitude among residents. This paper gives an approach of the solid waste management in Malaysia with the aim of presenting the state of waste management practices and problems with regards to environmental, economic and other ramifications