Forest fires are contributing significantly to the acceleration of deforestation. Monitoring and mapping these fires are crucial, and remote sensing technology has proven effective for this purpose. This research employs remote sensing methods to evaluate the severity of a forest fire in Kampung Balai Besar, Dungun. The incident, covering a 23-hectare area, occurred on 15 June 2021. Initial data processing utilized Sentinel-2 satellite images from 14 June 2021 (pre-fire) and 19 June 2021 (post-fire). The extent and severity of the fire were assessed using the Normalized Burn Ratio (NBR) index derived from satellite images. Different levels of burn severity were classified based on the extracted NBR, and classes of the calculated index value were generated accordingly. The severity level and intensity of the burn were analyzed using the Difference Normalized Burn Ratio (dNBR) index. This spectral index aided in assessing the severity of the forest fire in Kampung Balai Besar. The findings revealed that 13.9% of the area experienced low severity burns, 47.2% had moderate to high severity burns, and 38.9% exhibited high severity burns. In summary, areas with moderate to high and high severity burns showed more significant damage, while unburned areas displayed higher vegetation productivity. The study successfully identified the burned area in Kampung Balai Besar, providing valuable information for early decision-making and effective forest management planning.

Road access is crucial in any location since it promotes more comfortable transportation for people. However, the seasonal monsoon can cause water to overflow and affect to local transportation accessibility. Thus, the aim of this research was to provide analternative route map for safe travel from Kota Marudu to Kota Kinabalu, Sabah during the floods using a geospatial approach. The flood vulnerability map was produced based on selected local criteria which are the slope, rainfall, land cover/land use (LULC), distance from river and river density, while network analysis used for the path analysis. The dominants factors were the LULC and the distance from river which have the equal rank from Analytic Hierarchy Process (AHP) evaluation. The vulnerability map showedthere were two alternative route available during the flood in the study area. When compared, one of it could be used as an applicableroute during the flood. Since the flood extent was only based on estimation, thus the flood only could be predicted and sometimes will cause unexpected disaster. New road should be proposed which it should be a good idea to establish road at the higher part of the district. With this alternative route map, user may be informed to choose a safer route when the rainy season arrived as cautious during the season.

The integration of Light Detection and Ranging (LiDAR) technology into consumer electronics like smartphones has created new opportunities for the use of three-dimensional (3D) modelling, especially in the domains of infrastructure inspection and civil engineering. This paper presents the accuracy of a 3D bridge model generated using a smartphone LiDAR application in comparison with conventional surveying methods. In this study, LiDAR data were captured using an iPhone 13 Pro and processed to generate 3D models. The accuracy of the generated model was then validated against reference data obtained from a tacheometry survey, which served as a ground truth for Root Mean Square Error (RMSE) determination based upon coordinates, distance measurements and volumetric comparison. The results indicate that smartphone LiDAR achieves coordinate RMSE values within the decimeter to submeter range for both Ground Control Points (GCPs) and bridge edge features. The RMSE values obtained for the GCPs were 0.324, 0.274 and 0.298 m, respectively. Distance analysis revealed moderate differences of 0.278, 0.668 and 0.455 m, respectively, while the volumetric comparison showed a relatively small overall difference of 0.679 m3 between the two methods. These values validate that the smartphone LiDAR is suitable for preliminary bridge documentation, 3D visualization and rapid geometric assessment. Nevertheless, it cannot serve as a replacement for high precision surveying methods required for detailed structural inspection. Overall, the findings demonstrate the potential of smartphone LiDAR as a cost-effective complementary device for bridge modelling applications in the fields of geomatics and civil engineering.