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All Journal Journal of Information Systems and Informatics Jurnal Riset Multidisiplin dan Inovasi Teknologi
Umar, Mohamad Fahrul Himalaya
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Social Sciences

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Land Cover Classification Using Sentinel 2A Image in Kolaka Subdistrict, Kolaka Regency, Southeast Sulawesi Suni, Muhammad Adam; Fitra, Ramad Arya; Umar, Mohamad Fahrul Himalaya
Jurnal Riset Multidisiplin dan Inovasi Teknologi Том 1 № 02 (2023): Jurnal Riset Multidisiplin dan Inovasi Teknologi
Publisher : PT. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/jimat.v1i02.267

Abstract

Land cover in Kolaka District continues to change. Mapping and identifying land cover types using the Maximum Likelihood method is more accurate than other methods. This research aims to analyze the capabilities of Sentinel 2A Imagery and the Maximum Likelihood classification method for mapping and identifying land cover types in Kolaka District. This research was carried out from July to September 2023 and was carried out in 4 stages, namely the first stage of image pre-processing by carrying out the layer stacking process. The second stage is image analysis and classification. The third stage is carrying out a Ground Check, and the fourth stage is validation and accuracy testing. The value of the accuracy test results with Overall Accuracy (OA) is 88.75% which is in the good category. The results of the land cover classification obtained 8 land cover classes, namely secondary dry land forest covering an area of 3974.20 Ha or 31.84%, plantation land cover covering an area of 3,886.87 Ha or 31.14%, dense bushes covering an area of 1,641.42 Ha or 13.15%, mixed dry land agricultural land cover covering an area of 1,415.62 Ha or 11.34%, residential land cover of 744.26 or 5.96%, paddy field cover of 613.53 Ha or 4.92%, open land cover of 148.66 Ha or 1.19% and water body land cover of 56.22 Ha or 0.45% of the total area of Kolaka District.
Spatial Analysis of Changes in Normalization Differences Vegetation Index in Protected Forest Areas of South Lore District, Poso Regency Suni, Muhammad Adam; Basoka, Muhammad Darmawan; Rafiq, Muhammad; Umar, Mohamad Fahrul Himalaya; Muis, Hasriani; Baharuddin, Rhamdhani Fitrah; Agusman, Agusman
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.577

Abstract

Detection of changes in vegetation density generally uses the vegetation index parameter. The value of the vegetation index can provide information on the proportion of vegetation cover, live plant index, plant biomass, cooling capacity, and estimation of carbon dioxide absorption. This study aims to analyze changes in the level of vegetation density using Sentinel 2-A imagery in the protected forest area of South Lore District. This study used the method of calculating the Normalized Difference Vegetation Index (NDVI) to identify changes in density over 5 years. The results of the NDVI analysis are the largest in the range of -0.92960 to 0.871725. The vegetation density class in the Protected Forest Area of South Lore District in 2017 is in the dense class with an area of 15,322.24 Ha or around 47.66%, while the smallest in the non-vegetation class, which is 103.11 Ha or 0.32%, while the largest vegetation density class is in the Protected Forest Area of South Lore District in 2022, namely in the medium/quite dense class with an area of 19,948.18 Ha or 62.01% while the smallest in the non-vegetation class of 219.17 Ha or 0.68%. The largest increase in area was in the moderate/quite dense class of 4,892.33 Ha or 15.20% while the largest decrease in area was in the dense class with an area of 6,651.16 Ha or 20.67% of the total area of the Protected Forest Area of South Lore District.
Co-Authors Agusman, Agusman Baharuddin, Rhamdhani Fitrah Basoka, Muhammad Darmawan Fitra, Ramad Arya Hasriani Muis Muhammad Adam Suni Muhammad Rafiq