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Proceedings Paper

Mapping tree height in agroforestry system using Landsat 8 data
Author(s): Yudi Setiawan; Lilik B. Prasetyo; Sahid Hudjimartsu; Wim Ikbal; Desi Suyamto
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Paper Abstract

Agroforestry is a land use management-system represents unique vegetation characteristics among tree vegetation types. Tree height is a vegetation variable used to characterize vertical structure, including mixed vegetation structure in agroforestry. Estimation of tree heights with multispectral imagery is a relatively new application and is dependent on integrating synoptic coverage optical data with samples of height data, often from LiDAR-derived reference data. In this study, multispectral Landsat 8 data, Unmanned Aerial Vehicle (UAV)-based LiDAR height data and a log-linear regression model were used to estimate tree height for agroforestry land use in western part of Java Island, Indonesia. We generated a Canopy Height Model (CHM) directly from height-normalized LiDAR points and used as reference data in modeling the key height variable in the multispectral bands of Landsat 8. The analysis showed that red band was the best band to estimate tree height in agroforestry land use, followed by swir band. The log-linear regression algorithm of red band accurately reproduced the LiDAR-derived height training data using Landsat 8 data with overestimate 1.46 m in estimating tree height < 5 m and underestimate 7.79 m for tree height > 20 m.

Paper Details

Date Published: 6 August 2018
PDF: 7 pages
Proc. SPIE 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 107730P (6 August 2018); doi: 10.1117/12.2326014
Show Author Affiliations
Yudi Setiawan, Bogor Agricultural Univ. (Indonesia)
Lilik B. Prasetyo, Bogor Agricultural Univ. (Indonesia)
Sahid Hudjimartsu, Bogor Agricultural Univ. (Indonesia)
Wim Ikbal, Bogor Agricultural Univ. (Indonesia)
Desi Suyamto, Bogor Agricultural Univ. (Indonesia)


Published in SPIE Proceedings Vol. 10773:
Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018)
Kyriacos Themistocleous; Giorgos Papadavid; Silas Michaelides; Vincent Ambrosia; Diofantos G. Hadjimitsis, Editor(s)

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