Landslide impact is potentially hazardous to an urban environment. Landslides occur at certain slope levels over time and require practical slope analysis to assess the nature of the slope where a landslide is likely to occur. Thus, acquiring very high-resolution remote sensing data plays a significant role in determining the slope surface. For this study, 12 landslide conditioning parameters with 10 × 10 cell sizes that have never been previously collectively applied were created. These factors were created directly from the LiDAR (Light Detection and Ranging) DEM (digital elevation model)using their layer toolboxes, which include slope, aspect, elevation, curvature, and hill shade. Stream power index (SPI), topographic wetness index (TWI), and terrain roughness index (TRI) were created from spatial layers such as slope, flow direction, and flow accumulation. Shapefiles of distances to roads, lakes, trees, and build-up were digitized as land use/cover from the LiDAR image and produced using the Euclidean distance method in ArcGIS. The parameters were selected based on expert knowledge, previous landslide literature, and the study area characteristics. Moreover, multicriteria decision-making analysis, which includes the analytic hierarchy process (AHP) and fuzzy logic approaches not previously utilized with a LiDAR DEM, was used in this study to predict the possibility of a landslide. The receiver operating characteristics (ROC) were used for the validation of results. The area under the curve (AUC) values obtained from the ROC method for the AHP and fuzzy were 0.859 and 0.802, respectively. The final susceptibility results will be helpful to urban developers in Malaysia and for sustainable landslide hazard mitigation.

Oil palm has become one of the largest plantation industries in Malaysia, but the constraints in terms of manpower and time to monitor the development of this industry have caused many losses in terms of time and expense of oil palm plantation management. The introduction to the use of drone technology will help oil palm industry operators increase the effectiveness in the management of oil palm cultivation and production. In addition, knowledge gaps on drone technology were identified, and suggestions for further improvement could be implemented. Therefore, this study reviews the application and potential of drone technology in oil palm plantation, and the limitation and potential of the methods will be discussed.

A landslide is a significant environmental hazard that results in an enormous loss of lives and properties. Studies have revealed that rainfall, soil characteristics, and human errors, such as deforestation, are the leading causes of landslides, reducing soil water infiltration and increasing the water runoff of a slope. This paper introduces vegetation establishment as a low-cost, practical measure for slope reinforcement through the ground cover and the root of the vegetation. This study reveals the level of complexity of the terrain with regards to the evaluation of high and low stability areas and has produced a landslide susceptibility map. For this purpose, 12 conditioning factors, namely slope, aspect, elevation, curvature, hill shade, stream power index (SPI), topographic wetness index (TWI), terrain roughness index (TRI), distances to roads, distance to lakes, distance to trees, and build-up, were used through the analytic hierarchy process (AHP) model to produce landslide susceptibility map. Receiver operating characteristics (ROC) was used for validation of the results. The area under the curve (AUC) values obtained from the ROC method for the AHP model was 0.865. Four seed samples, namely ryegrass, rye corn, signal grass, and couch, were hydroseeded to determine the vegetation root and ground cover’s effectiveness on stabilization and reinforcement on a high-risk susceptible 65° slope between August and December 2020. The observed monthly vegetation root of couch grass gave the most acceptable result. With a spreading and creeping vegetation ground cover characteristic, ryegrass showed the most acceptable monthly result for vegetation ground cover effectiveness. The findings suggest that the selection of couch species over other species is justified based on landslide control benefits.