Spectral reflectance and principal component analysis on the distribution of clove vegetation using Landsat 8

International Journal of Physical Sciences and Engineering

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Title Spectral reflectance and principal component analysis on the distribution of clove vegetation using Landsat 8
Creator Yuliara, I Made
Ratini, Ni Nyoman
Windarjoto, Windarjoto
Suandayani, Ni Komang Tri
Subject clove distribution
Landsat 8
normalized difference vegetation index (NDVI)
principal component analysis (PCA)
spectral reflectance
Description This paper discusses the distribution of clove vegetation in Buleleng Regency, Bali using a vegetation index extracted from Landsat 8 imagery based on spectral reflectance and Principal Component Analysis (PCA). Data analysis used the Normalized Difference Vegetation Index (NDVI) transformation and PCA band transformation. Adjustment of the position of clove vegetation in the image is determined by the measurement results of the clove coordinate sample in the field. The results showed that the accuracy of the area of ?? clove vegetation distribution as measured as a percentage comparison to the area data of the Forestry and Plantation Service, Buleleng Regency, Bali in 2014, was 97.066% for the spectral reflectance-based vegetation index (NDVIref) and 97.072% for those based on PCA ( NDVIpca). The distribution class category with the dominant area identified into heavy class (NDVIref) of 7841.25 ha and moderate class (NDVIpca) of 7591.77 ha. There is a difference in the two determinant coefficient values ?? (R2), which is 0.2407% and at 5% significance, the variants of the B4 and B5 spectral reflectance image variable data variants, as well as the C1 and C2 component image variables simultaneously, can affect the NDVI vegetation index.
Publisher Universidad Tecnica de Manabi
Date 2020-12-31
Type info:eu-repo/semantics/article
Format application/pdf
Identifier https://sciencescholar.us/journal/index.php/ijpse/article/view/611
Source International journal of physical sciences and engineering; Vol. 4 No. 3: December 2020; 27-37
Language eng
Relation https://sciencescholar.us/journal/index.php/ijpse/article/view/611/554
Rights Copyright (c) 2020 International journal of physical sciences and engineering

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