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All Journal Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat International remote sensing application journal

Dian Adhetya Arief

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Author-ID : 5915639

Astronomy Computer Science & IT Earth & Planetary Sciences Education Environmental Science Health Professions Medicine & Pharmacology Public Health

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UTILIZING LANDSAT 8 IMAGERY FOR MAPPING OF BURNED AREAS USING THE NORMALIZE DIFFERENCE VEGETATION INDEX (NDVI) AND NORMALIZE BURN RATIO (NBR) METHODS Rizka Fadil; Dian Adhetya Arief; Sri Kandi Putri
International Remote Sensing Applied Journal Vol 1 No 2 (2020): international remote sensing application journal (December Edition)
Publisher : Remote Sensing Technology Study Program

This study aims (1) to map changes in the area of forest land in the western part of Bengkalis Regency in 2016 and 2021, (2) to determine the distribution of the area of forest burned in the western part of Bengkalis Regency, (3) to determine the severity of forest fires in the District of Bengkalis West Bengkalis.This study used the NDVI (Normalized Difference Vegetation Index) method by Huete et. Al by compositing band 5 (NIR) and band 4 (Red) on Landsat 8 imagery which was processed using ArcGIS software before and after a forest fire. As well as the NBR (Normalized Burn Ratio) and dNBR (Difference Normalized Burn Ratio) methods by Eidenshink et al by compositing band 5 (NIR) and band 7 (SWIR) on Landsat 8 images processed using QGIS software. For sampling using random sampling method and accuracy test using overall accuracy, user's accuracy, producer's accuracy, and kappa analysis. The results of this study are (1) the area of forest land in Bengkalis Regency continues to decrease every year, in 2016 the area of forest land903,920 ha and 2021 the total forest area is463,441 ha. (2)The area of forest land burned due to forest fires in Bengkalis Regency, which burned the least was 267.43 ha, while it was 1468.93 ha and the most extensive was 2186.53 ha.(3) Based on one forest fire distribution map, it is divided into 7 fire severity classes, namely high post-fire regrowth, low post-fire regrowth, no burning, low, medium-high and very high and the most dominant forest fire level is low-high.

MAPPING ESTIMATION OF SHALLOW WATER DEPTH USING BATHYMETRIC EMPIRICAL MODELING ECHOSOUNDER DATA AND SENTINEL-2 SATELLITE IMAGE DATA (CASE STUDY: SHALLOW WATERS OF BAYUR BAY, PADANG CITY) Altha Nurzafira Melin; Dian Adhetya Arief
International Remote Sensing Applied Journal Vol 2 No 2 (2021): international remote sensing application journal (Dec Edition 2021)
Publisher : Remote Sensing Technology Study Program

This study aims to see the depth of the shallow waters of Teluk Bayur, Padang City, West Sumatra Province using Sentinel 2 imagery through the processing of Geographic Information Systems and Remote Sensing. Satellite imagery is intended to obtain in-depth information at an affordable cost and to examine differences in the use of the algorithms used. This study uses Sentinel 2 satellite data. The algorithm used in this research is Bathymetric Empirical Modeling which is applied to Sentinel-2 digital satellite imagery, it will go through several analytical processes, starting from the extraction of water bodies where this process separates between water bodies and non-water bodies. waters, after that the process of correcting the reflection of the water surface or Sunglint. The results of this study are empirical maps of the shallow waters of Teluk Bayur which get a maximum depth of 125 m using band 1 and band 2, while the maximum depth that is more accurate is 128 m using band 2 and band 3 where the maximum depth of 128 m is also the depth of data acquisition results echosounder PT. PELINDO II Teluk Bayur Branch.

Co-Authors Altha Nurzafira Melin Dedy Fitriawan Mustika Seprianita Risky Ramadhani Rizka Fadil Sri Kandi Putri Syarah Jelita

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