This research is being conducted in Australia to automatically extract forest structure. Point clouds hold a vast amount of information on vegetation, habitat characteristics, fuel loads, timber volumes, and other forest characteristics. However, it is challenging to turn this data into usable information.

This research aimed to develop a technique to automatically classify point clouds into different forest components: near-surface vegetation, mid-storey scrubs, tree stems, and tree canopy. After classification, useful information on these different vegetation strata can be extracted, making it easier to interpret vegetation information hidden in the point clouds.

– See more at: http://blog.lidarnews.com/coloring-the-points#sthash.DheH5ggI.dpuf

Credits to: NURZARIYATUL SYAHIRAH BINTI MASROL (1SGHG)

Credits to: NORHIKMAH BINTI ABDUL RAZAK (1 SGHG)

Credits to: MOHAMAD HANIF BIN ABDULLAH (1 SGHG)

Add all overlapped photos in AGIsoft

Generate dense point clouds, surface and texture

Credits to: Zuliana binti Che Pi (1 SGHG)

Proposal defense en zamri

Simulations of Flooding Due to ‘Agaton’ and ‘Seniang’ in Cabadbaran River

Preliminary and unvalidated 2D simulations of the January 2014 Typhoon Agaton and December 2014 Typhoon Seniang flood events in Cabadbaran River, Agusan del Norte, Philippines. The purpose of these simulations is to provide preliminary visualizations of the differences in the magnitude and extent of flooding during the two typhoons.

The simulation was generated using the Environmental Fluid Dynamics Code or EFDC, with inflow hydrographs computed using HEC HMS and tidal data as boundary conditions. The 2D model utilized LiDAR-derived DTM provided by UP DREAM/Phil-LiDAR Data Preprocessing Team of UP Diliman. The river bed topography/bathymetry of Cabadbaran River is not yet integrated into the DTM used during the simulation. The model simulations will be updated once river bed topography/bathymetry of Cabadbaran River is available.

Video at: Video 1 Video 2

Adapted from: https://carsulidar1.wordpress.com

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Surveying golf course

Lidar Survey from UAV:

– 70 points per square meter
– <10 cm accuracy

more at: http://yellowscan.lavionjaune.com/2015/04/02/surveying-golf-course/