The Lidar technology is widely used in various studies for mapping needs. In this study was to extract land cover using Lidar data by incorporating a support vector machine (SVM) approach. The study was located in the city of Lombok, Nusa Tenggara Barat. Image extraction was performed on single wavelength Lidar data to produce intensity and elevation (Digital Surface Model) features. Feature extraction of Lidar data was implemented by using a pixel-based approach. The extracted features used as an attribute for training data to generate the SVM prediction model. The prediction model to predict the types of land cover in the study area such as buildings, trees, roads, bare soil, and low vegetations. For accuracy assessment purposes, we used topographic map available in shapefile format as the reference map and estimated the accuracies of the resulted classifications. In this study, land cover classification used combination bands which improved the overall accuracy by approximately 20%. The use of the intensity data in this band combination was the reason for the increasing accuracy.

Lidar is a remote sensing technology that is developing and widely used today. This data has the advantage of having a very high spatial accuracy so that it is very supportive of mapping with detailed accuracy. There are various benefits of lidar data, one of which is for risk analysis of natural disasters. The purpose of this study is to use lidar data to analyze flood disasters in an area. The method uses information derived from the Lidar data, namely the Digital Surface Model (DSM) and the Digital Terrain Model (DTM), which results from ground and non-ground classification. From this data, topographical analysis is carried out, especially the river flow area and its influence on the surrounding area. The research location is the City of Mataram, Lombok, Indonesia. This location is a coastal area and the location through which the river flows into the sea. The results of the analysis of this study were compared with data on flood disasters that had occurred in that location as comparative data. The results showed that the analysis using Lidar data has excellent topographic accuracy as an approach in the analysis of flood disasters towards an area.

The purpose of this research is the use of a Digital Elevation Model (DEM) was used in conjunction with a Geographic Information System to compute morphometric factors influencing flooding vulnerability. These causal factors were subjected to a weighted overlay analysis in order to categorize areas based on their flooding vulnerability. The research location is in Sitiarjo Village Malang District East Java Indonesia. The flood disaster that most harmed the community in Sitiarjo village occurred in 1983, 2003, 2007, 2010, 2013 and 2017. Sitiarjo village is crossed by two major rivers, namely the Panguluran river and the Mbambang river which meet at the river in the southern part of the village.. The results showed that the flood vulnerability of sitiarjo village has a high level in the center of the village (flood plain and fluvial landforms). The greatest flood hazard is at the bottom of the confluence of the Pangluran and Mambang rivers in Rowo Terate Sub Village.