Penggunaan Metode Unsupervised (ISO Data) untuk Mengkaji Kerapatan Vegetasi di Kecamatan Pangandaran

Rahmawan, Agung Dwi; Pawestri, Dini Adha; Fakhriyah, Rafifah Adinda; Pasha, Habibie Daud Syafaat; Ferryandy, Muhamad; Sugandi, Dede; Ridwana, Riki; Somantri, Lili

doi:10.23887/jjpg.v8i1.22752

Cited by 6 publications

(6 citation statements)

References 6 publications

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“…These conditions indicate mangrove forests located on the outskirts and directly adjacent to the sea tend to be in natural condition. The reduced area in the very sparse-density, sparse-density, mediumdensity, and dense-density classes is not only due to damage, but the change in the area occurs due to the transfer of the previously mentioned mangrove density to very dense in density (Fahreza et al, 2022).…”

Section: Table 3 Area Of Thementioning

confidence: 88%

Analysis of Changes in Mangrove Land Cover in West Langsa District, Langsa

Junianto

Sugianto

Basri

2023

jppipa, pendidikan ipa, fisika, biologi, kimia

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This study aims to analyze changes in land cover and mangrove crown density in Langsa Barat District for the period 2000-2020. The method used in this study is the maximum likelihood classification (MLC) to determine changes in mangrove land cover while determining mangrove density using the NDVI equation. Based on the results of the analysis of changes in mangrove land cover there was an increase and decrease in area. In 2000 the area of mangrove land was 1,039.17 ha, then increased in area in 2005 amounted to 1.325,59 ha (27.56%). In 2010, the mangrove area decreased by 1.145,22 ha (15.75%). In 2015, the mangrove area increased to 1,357.10 ha (18.50%), and finally, in 2020 there was an increase in the mangrove area to 2.027.05 ha (49.37%). While the analysis of mangrove crown density using NDVI value from 2000 to 2020, the highest crown density value was in 2020 with the category of the dense crown density of 1,509.40 ha (74.46%), while the medium crown density value was recorded in 2020 namely 517.49 ha (25.53%). Meanwhile, the lowest sparse category canopy density value was recorded in 2020 with an area of 0.17 ha (0.01%).

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Section: Table 3 Area Of Thementioning

confidence: 88%

Analysis of Changes in Mangrove Land Cover in West Langsa District, Langsa

Junianto

Sugianto

Basri

2023

jppipa, pendidikan ipa, fisika, biologi, kimia

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“…The use of random starts is to reduce bias in the acquisition of sampling data. Bruguiera parviflora B = 0,168 (D) 2,42 Clough and Scott (1989) 3…”

Section: Develop the Best Biomass Model From Several Vegetation Indic...mentioning

confidence: 99%

“…Those are generally located in Sumatra, Kalimantan, and Papua. However, in reality, over time, the forest area in Indonesia has experienced degradation, causing an increasing problem of forest destruction [2].…”

Section: Introductionmentioning

confidence: 99%

The above-ground biomass model of mangrove forest in Panai Hilir, Indonesia

Samsuri,

Pasaribu,

Zaitunah

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Mangrove forest is one of the forests with high biomass storage in the tropics besides mainland forests. The mangrove ecosystem has an ecological function as a carbon reducer through a sequestration process (C-sequestration). One technique that can be used to calculate biomass is the use of remote sensing technology using satellite imagery and the application of transformation of the vegetation index. This study aims to obtain the best biomass equation model from several vegetation indices, analyze the estimated biomass value from Landsat 8 imagery in 2022, and map the distribution of the estimated distribution of average above-ground biomass of mangrove forest in Panai Hilir using Landsat 7 imagery and Landsat 8 in 2002 and 2022. This study used a systematic sampling method with a random start with 70 plots. Biomass calculations are carried out using allometric equations. Modeling uses the dependent variable (biomass) and the independent variable (vegetation index). The vegetation indices used are NDVI, GNDVI, and TDVI. The results of this study showed that the chosen equation model was the GNDVI (Green Normalized Difference Vegetation Index) linear equation model y = 11, 479x – 2,5569 with r2 of 0,404. The average distribution of above-ground biomass of mangrove vegetation at research sites 2002 was 109,66 tons/ha, with the highest biomass distribution being 200,48 tons/ha. The average above-ground biomass content of mangrove vegetation at the research location in 2022 is 98,28 tons/ha, with the highest biomass distribution of 213,10 tons/ha. In calculations using the selected model and index, in 2022, a total estimated average biomass was obtained of 405,52 tons/ha.

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“…Then the atmospheric correction is carried out to change the digital number value to the reflectance value. Atmospheric correction is used to clarify the appearance of objects in the image due to inappropriate reflectance values due to atmospheric influences, absorption, and scattering [13]. The method used is the Dark Object Subtraction (DOS) method.…”

Section: Data Sourcementioning

confidence: 99%

Shallow sea waters habitat mapping in 2018 and 2022 using Sentinel-2 Imagery with OBIA Method at Kelapa Dua Island, Seribu Island, Jakarta Province, Indonesia

Panjaitan,

Hamidah

2023

IOP Conf. Ser.: Earth Environ. Sci.

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Shallow sea habitat has a very important role as a place to live and shelter for various types of organisms. Mapping this area needs to be done regularly considering the many benefits it has and the tendency for this area to change, one of them is by using remote sensing technology with the object-based image analysis (OBIA) method. OBIA classification includes the process of image segmentation and classification of all segmentation results. In the segmentation process using scale 100 at level 1 and scale 10 at level 2. Furthermore, at the classification process, 6 (six) habitat classes are obtained, namely sand, coral, macroalgae, sea grass, rubble and dead coral algae. The overall accuracy value in 2018 showed a value of 70%, and in 2022, it showed a value of 70.77%. The kappa coefficient value is 0.617 in the 2018 image acquisition and 0.612 in the 2022 image acquisition. The analysis carried out showed that there was a change in each habitat with the habitat that experienced the greatest changes are sand and dead coral algae class.

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Penggunaan Metode Unsupervised (ISO Data) untuk Mengkaji Kerapatan Vegetasi di Kecamatan Pangandaran

Cited by 6 publications

References 6 publications

Analysis of Changes in Mangrove Land Cover in West Langsa District, Langsa

Analysis of Changes in Mangrove Land Cover in West Langsa District, Langsa

The above-ground biomass model of mangrove forest in Panai Hilir, Indonesia

Shallow sea waters habitat mapping in 2018 and 2022 using Sentinel-2 Imagery with OBIA Method at Kelapa Dua Island, Seribu Island, Jakarta Province, Indonesia

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