Spatial Model of Canopy Density in Mangrove Forest of Percut Sei Tuan

Nurdin Sulistiyono, Khairil Amri, Pindi Patana, Achmad Siddik Thoha

2019

Abstract

Information about canopy density is needed in many ways, for example, in estimating forest degradation and forest quality. Utilization of vegetation index values on satellite imagery can be used to predict canopy density distribution. This study aims to predict canopy density distribution in mangrove forests. The methodology used is using regression analysis by connecting Normalized Difference Vegetation Index (NDVI) value with canopy density values in the field. The NDVI value is derived from Landsat 8 satellite images, while the canopy density percentage is obtained by using a camera. The spatial distribution of canopy density is obtained through spatial modeling using Geographic Information System (GIS). The results showed that the NDVI value of the linear regression model could be used to predict the density distribution of mangrove forest canopy with r square value of 59.0% and sig value <0.005.

Paper Citation

in Harvard Style

Sulistiyono N., Amri K., Patana P. and Thoha A. (2019). Spatial Model of Canopy Density in Mangrove Forest of Percut Sei Tuan.In Proceedings of the International Conference on Natural Resources and Technology - Volume 1: ICONART, ISBN 978-989-758-404-6, pages 42-45. DOI: 10.5220/0008388000420045

in Bibtex Style

@conference{iconart19,
author={Nurdin Sulistiyono and Khairil Amri and Pindi Patana and Achmad Siddik Thoha},
title={Spatial Model of Canopy Density in Mangrove Forest of Percut Sei Tuan},
booktitle={Proceedings of the International Conference on Natural Resources and Technology - Volume 1: ICONART,},
year={2019},
pages={42-45},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008388000420045},
isbn={978-989-758-404-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Natural Resources and Technology - Volume 1: ICONART,
TI - Spatial Model of Canopy Density in Mangrove Forest of Percut Sei Tuan
SN - 978-989-758-404-6
AU - Sulistiyono N.
AU - Amri K.
AU - Patana P.
AU - Thoha A.
PY - 2019
SP - 42
EP - 45
DO - 10.5220/0008388000420045