Comparison Of Model Accuracy In Tree Canopy Density Estimation Using Single Band, Vegetation Indices And Forest Canopy Density (FCD) Based On Landsat-8 Imagery (Case Study: Peat Swamp Forest In Riau Province)

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Identification of a tree canopy density information may use remote sensing data such as
Landsat-8 imagery. Remote sensing technology such as digital image processing methods could be used
to estimate the tree canopy density. The purpose of this research was to compare the results of accuracy of each method for estimating the tree canopy density and determine the best method for mapping the
tree canopy density at the site of research. The methods used in the estimation of the tree canopy density
are Single band (green, red, and near-infrared band), vegetation indices (NDVI, SAVI, and MSARVI), and
Forest Canopy Density (FCD) model. The test results showed that the accuracy of each method: green
73.66%, red 75.63%, near-infrared 75.26%, NDVI 79.42%, SAVI 82.01%, MSARVI 82.65%, and FCD
model 81.27%. Comparison of the accuracy results from the seventh methods indicated that MSARVI is
the best method to estimate tree canopy density based on Landsat-8 at the site of research. Estimation
tree canopy density with MSARVI method showed that the canopy density at the site of research
predominantly 60-70% which spread evenly.
Informasi Detil
Judul Seri -
No. Panggil -
Penerbit LAPAN : Jakarta.,
Deskripsi Fisik Hlm. 81-92
Bahasa English
ISBN/ISSN 2549-516X
Klasifikasi NONE
Edisi International Journal of Remote Sensing and Earth
Subyek FCD
Tree canopy density
single band
vegetation indices
Pernyataan Tanggungjawab
-
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