MANGROVE EXTRACTION IN E.B. MAGALONA, NEGROS OCCIDENTAL USING LIDAR DATA

ABSTRACT: Mangroves have a lot of economic and ecological advantages which include but are not limited to coastal protection, habitat for wildlife, fisheries and forestry products. Determination of the extent and density of the mangrove patches in the coastal areas of the Philippines is therefore important especially in resource conservation, protection and management. This starts with a well-defined and accurate map. LiDAR (Light Detection and Ranging), a remote sensing technology that measures distance by illuminating a target with a laser and analyzing the reflected light, was used in the extraction of Mangroves in the coastal area of EB Magalona, Negros Occidental. Total coastal study area is 143 km. Derivatives that were used in the extraction include Digital Terrain Model (DTM), Digital Surface Model (DSM), Intensity, Number of Returns, and Canopy Height Model (CHM). The RGB bands of the Orthographic photographs taken at the same time with the LiDAR data was also used as one of the layers during the processing. Normalized Difference Vegetation Index (NDVI), Green-Red Vegetation Index (GRVI) and CHM using Canny Edge Layer was derived as well to produce an enhanced segmentation. Training and Validation points were collected through field validation and visual inspection. The points were then used to feed the Support Vector Machine (SVM) based on tall structures (CHM>1). Only four classes were used, namely, Built-up, Mangroves, Other Trees and Sugarcane. Buffering and contextual editing was incorporated to reclassify the extracted mangroves. However, this workflow only extracted mangroves that are at least one meter tall thereby excluding mangrove