Pemanfaatan Citra Landsat 8 untuk Identifikasi Sebaran Vegetasi di Kecamatan Pangandaran

Ridwan Saidi; Nisvi Nur’adqiah; Yusifa Muzri; Lu’lu’ Izzatul Fawziah; Reza Pahlawan; Dede Sugandi; Riki Ridwana

doi:10.20527/jpg.v7i1.7607

Pemanfaatan Citra Landsat 8 untuk Identifikasi Sebaran Vegetasi di Kecamatan Pangandaran

Ridwan Saidi, Nisvi Nur’adqiah, Yusifa Muzri, Lu’lu’ Izzatul Fawziah, Reza Pahlawan, Dede Sugandi, Riki Ridwana

Abstract

This study aims to determine: (1) the density of vegetation in Pangandaran district. (2)the result of comparison of vegetation density from digital image interpretation using the NDVI transformation with the results of validation. This research was done in pangandaran regency, which is located at coordinates 108º 41 - 1090 East Longitude and 07o 41-07 07 50 South Latitude has an area of up to 61 km². This research was conducted in several stages, namely: (1) the preparation of tools and data, (2) digital data processing, (3) field data collection, and (4) data analysis. Thanks to the density of vegetation can be done quickly by way of digital image interpretation using NDVI (Normalized Difference Vegetation Index) transformation. The purpose of this research is to know the land arrangement in Pangandaran District and for vegetation index of residential area in Pangandaran District. The object of this research is residential area in Pangandaran District. The data used are Landsat Image 8 year 2018. The software used is ENVI 5.1 and ArcGIS 10.3 software. The method used is the classification of land use and the calculation of NDVI in ENVI which then classified based on the range of NDVI index values. The results showed that the density of vegetation in Pangandaran District was dominating classified and as quite dense but it needed a lot of updating of its digital image and data so that the accuracy rate increased between imagery and field data. Vegetation in Pangandaran Subdistrict is mostly dominated by teak, waru, coconut, Chinese petai, goat, santigi, and ketapang. Based on the results of the interpretation accuracy test, obtained an accuracy value for the entire sample of 57% so that the results of image interpretation and field checks regarding vegetation density cannot be accepted because the expected level of interpretation accuracy is 85%, while the accuracy test results get a value of 57%. To get a complete picture of the availability of green open space in Pangandaram Regency, fast and relatively more accurate analysis of high spatial resolution is needed. The satellite imagery used in this study is Landsat 8 Imagery which has never been used in previous studies. Analysis of these images uses a vegetation index / NDVI that can directly distinguish plants from non-plants. The results of this image analysis also produce digital data that can be processed quantitatively for further research purposes.

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DOI: http://dx.doi.org/10.20527/jpg.v7i1.7607