Urban tree analysis using unmanned aerial vehicle (uav) images and object-based classification (case study: University of indonesia campus)

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Abstract

This paper aims to analyze the urban trees located in University of Indonesia campus using UAV image and Object-based Image Analysis (OBIA). Herein, DJI Phantom 4 Pro was flown at 90 meter height to take image above the study area with spatial resolution of 2.4 cm/pixel. The image from UAV then processed using Agisoft Photoscan and underwent geometric correction. The image containing red, green and blue (RGB) bands then segmented with multi-resolution algorithm. Four Vegetation Indices (VIs) namely Normalized Green-red Difference Index (NGRDI), Visible Atmospherically Resistant Index (VARI), Visible-band Difference Vegetation Index (VDVI) and Red-Green Ratio Index (RGRI) were used to develop rule sets for land use land cover (LULC) classification. Vegetation class was separated from LULC image to be further analysed with ArcGIS using information from ground truth observation. Final product is urban tree map containing tree names and LULC classes.

Original languageEnglish
Article number012105
JournalIOP Conference Series: Earth and Environmental Science
Volume683
Issue number1
DOIs
Publication statusPublished - 17 Mar 2021
Event3rd International Geography Seminar 2019, IGEOS 2019 - Solo, Indonesia
Duration: 31 Aug 2019 → …

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