Karakteristik indeks vegetasi pada berbagai penggunaan lahan di hulu sub DAS Cikapundung melalui interpretasi citra satelit Landsat 8

Solihin, Muhammad Amir; Putri, Noviani; Setiawan, Andi; Siliwangi, Daud; Arifin, M Zainul

doi:10.24198/kultivasi.v19i3.28625

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…The research area saw cloud cover in 2015, which may have affected the NDVI value due to the white spectrum released. As a result, the NDVI value in the cloud would have been lower in 2015, approaching 0 or -1 [32]. Because it does not exhibit reflections or actual emissions from objects acquired by satellite images, the area covered by clouds in this study is not included in the examined area [31].…”

Section: Vegetation Density Changementioning

confidence: 99%

The effect of vegetation index on the land surface temperature in South Badung Regency, Bali Province

Dimyati,

Aginta,

Damayanti

2024

IOP Conf. Ser.: Earth Environ. Sci.

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The land surface temperature (LST) is a crucial component of the earth’s energy balance system. The temperature differences between the earth’s surface and the atmosphere are reflected in LST. Conversion of land, including vegetated land, may result in changes to LST. Using the vegetation index approach—NDVI and EVI—this study seeks to ascertain how variations in vegetation density impact LST. Using Landsat 7 ETM+ satellite imagery from 2003 and Landsat 8 OLI-TIRS from 2015 and 2020, this research combines remote sensing technologies and GIS to get vegetation density and LST values, which were then subjected to field verification and spatiotemporal analysis. According to the study’s findings, variations in vegetation density and soil surface temperature have an inverse or opposing relationship. The study’s findings suggest that variations in vegetation density and soil surface temperature have an opposing or inverse connection. In South Badung Regency, places with low vegetation density vary more in proximity to metropolitan areas, resulting in higher soil surface temperatures. These findings suggest that several additional factors, including population density and size, land use, urban planning, rainfall, and season, influence variations in land surface temperature in South Badung Regency.

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Section: Vegetation Density Changementioning

confidence: 99%

The effect of vegetation index on the land surface temperature in South Badung Regency, Bali Province

Dimyati,

Aginta,

Damayanti

2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…Hasil dari tingkat kerapatan dan perubahan vegetasi menggunakan NDVI menghasilkan 5 (lima) kelas, yaitu kelas non-vegetasi, kelas tingkat kehijauan sangat rendah, tingkat kehijauan rendah, tingkat kehijauan sedang, dan tingkat kehijauan tinggi (Hernawati dan Darmawan, 2018). Klasifikasi tingkat kehijauan (Tabel 2) dan kelas kerapatan tajuk (Tabel 3) menunjukkan Semakin besar nilai NDVI maka tingkat kehijauan vegetasi dan kerapatan vegetasi semakin tinggi (Solihin, et al, 2020).…”

Section: Analisis Kerapatanunclassified

Keanekaragaman Jenis dan Kerapatan Vegetasi Hutan Pantai di Selatan Pulau Sumbawa, Kecamatan Labangka, Kabupaten Sumbawa

Hidayati

Syafikri

Ramdhani

et al. 2023

jstl

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in Labangka Village in the South of Sumbawa Island is very important considering that this village is directly facing the Indian Ocean. In addition, the development of aquaculture in this village also requires knowledge of the vegetation that makes up the coastal forest so that appropriate management and monitoring activities can be planned. This study aims to identify the types of vegetation in coastal forest ecosystem in Labangka Village at four stations, namely in locations where super-intensive aquaculture will be built. The method used is the analysis of Importance Value Index and Normalized Differentiation Vegetation Index. The results of the study were as follows: Station 1 (27 species, dominated by Pongamia pinnata with an IVI of 185.64% for the tree level and IVI of 114.58% for the seedling level), Station 2 (9 species, dominated by P. pinnata INP of 214.16 % for the tree level and Leucaena leucocephala IVI 96.49% for the seedling level), Station 3 (18 species dominated by the pes-caprae formation type and shrubs, namely S. taccada, P. tectorius, and Heliotropium foertherianum), Station 4 (19 species dominated by shrubs namely S. taccada, Pandanus tectorius, and H. foertherianum and shrubs (L. camara and C. bonduc).The NDVI at observation stations ranged from -0.091 (sparse) to 0.543 (dense).

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“…Pemanfaatan data penginderaan jauh untuk pemetaan vegetasi pada beberapa penelitian sebelumnya, diawalis dengan mengunduh data satelit terlebih dahulu dan disimpan pada penyimpanan di komputer. Selanjutnya dilakukan pra pengolahan, pengolahan lanjutan dan analisis, seperti pada studi Hayu & Ridwana (2019); Hidayati et al, (2018); Solihin et al, (2020); Zaitunah & Sahara (2021). Pekerjaan ini tentunya akan menjadi tidak efisien jika melibatkan citra satelit dalam jumlah yang banyak, seperti pada studi ini, yaitu sebanyak 43 lapisan citra.…”

Section: Perubahan Tutupan Vegetasi DI Kabupaten Gorontalounclassified

Ekstraksi Perubahan Tutupan Vegetasi Di Kabupaten Gorontalo Menggunakan Google Earth Engine

Lahay

Koem

2021

Jambura Geosci. Rev.

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Monitoring changes in vegetation cover is important for the restoration of ecosystems in the Gorontalo Regency area. The utilization of remote sensing technology makes it possible to detect the dynamics of changes in vegetation cover spatially and temporally. The Terra MODIS satellite image collection in the study area is available in large numbers and sizes. Therefore, cloud computing-based spatial technology support is needed. Google Earth Engine (GEE) as a geospatial computing device is an alternative to cover this shortfall. The aim of this study is to explore the condition of vegetation cover spatially and temporally using the GEE platform. A total of 43 MODIS images in the study area, recording periods 2000 and 2020, were used to quickly and effectively generate vegetation cover maps. The process of downloading, processing, and analyzing data was automated through the GEE interface. The results of the mapping in 2000 and 2020 are shown by maps of vegetation cover in two classes, namely; vegetation and non-vegetation. The accuracy of the vegetation cover map shows good results, namely an overall accuracy of 0.81 for 2000 and 0.85 for 2020. The area of the non-vegetation class increased by 2815.29 ha, and the vegetation class decreased by 2767.31 ha. The map of spatial changes in vegetation cover in the study area is classified into three classes, namely revegetation, devegetation, and unchanged. Based on these results, the extraction of vegetation cover changes in the study area using the GEE platform can be carried out well.

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Karakteristik indeks vegetasi pada berbagai penggunaan lahan di hulu sub DAS Cikapundung melalui interpretasi citra satelit Landsat 8

Cited by 4 publications

References 11 publications

The effect of vegetation index on the land surface temperature in South Badung Regency, Bali Province

The effect of vegetation index on the land surface temperature in South Badung Regency, Bali Province

Keanekaragaman Jenis dan Kerapatan Vegetasi Hutan Pantai di Selatan Pulau Sumbawa, Kecamatan Labangka, Kabupaten Sumbawa

Ekstraksi Perubahan Tutupan Vegetasi Di Kabupaten Gorontalo Menggunakan Google Earth Engine

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