Pendekatan Indeks Vegetasi Untuk Mengevaluasi Kenyamanan Termal Menggunakan Data Satelit Landsat-Tm Di Kota Ambon

Abstract

The objectives of the research were to obtain correlation model between NDVI (Normalized Density Value Index) and Freshness Index, to examine the capability of Landsat-TM satellite to show opened green space in controlling the effect of heat island, to know the level of freshness in Ambon town, and to produce layout of opened green space of Ambon town in relation with the need of freshness of the communities. The result of the research showed that Landsat-TM satellite can be used to detect the green space area of the Ambon town. Based on the classification of NDVI through Landsat-TM satellite, the Ambon town has 899,9 hectares (3 %) of land without vegetation or scarcely vegetation, 1488,71 hectares (4 %) were low density of vegetation, 1495,34 hectares (4 %) were in middle density, and 32060, 58 hectares were in high density. NDVI had a positive correlation to the temperature and relative humidity which means that increasing of vegetation density decreased the temperature and increased the relative humidity of a certain area. Effect of the heat island to the Ambon town are identified 1267,93 hectares, and generally found in the central of town (District of Sirimau) and the new development area which followed the main road area.

Identification of The Geothermal Heat at Mount Iyang-Argopuro Based on a Data Image of Landsat 8 Satellite and a Data Gravity of GGMPlus Satellite

“…The vegetation density value in Figure 4 will be used as a reference in mapping geothermal manifestations in the Iyang-Argopuro Volcano Complex. According to Pietersz et. al.…”

“…al. (2018) areas that have a high greenish vegetation density class generally have a lower ground surface temperature than the surrounding area [25]. However, this does not always apply to areas that have geothermal potential.…”

Spatial Analysis of Changes in Normalization Differences Vegetation Index in Protected Forest Areas of South Lore District, Poso Regency

“…The NDVI method calculates the difference between the reflectance of light in the red spectrum (which is produced by chlorophyll in plants) and the near-infrared (which is produced by plant cells that reflect light). This method uses a simple formula that has previously been used by researchers, previous researchers [5], [7], [14], [15], [16], [17]. In determining the vegetation index, the following equation can be used: Sentinel 2A image data recorded in 2017 and 2022 obtained from the USGS were then analyzed using ArcGIS 10.8 software using a raster calculator using equation (1) to produce NDVI (Normalized Difference Vegetation Index) values.…”

Analisis Kerapatan Vegetasi Kota Ambon Menggunakan Data Citra Satelit Sentinel-2 dengan Metode MSARVI Berbasis Machine Learning pada Google Earth Engine

“…Perkembangan Kota Ambon yang semakin meningkat dapat berdampak pada kerapatan vegetasi di kota tersebut [1], [2]. Peningkatan jumlah penduduk dan pertumbuhan ekonomi dapat mendorong pengembangan infrastruktur dan pembangunan hunian yang membutuhkan lahan, sehingga dapat mengurangi luas area hijau dan mengurangi keberadaan vegetasi di kota .…”

“…Nilai kerapatan vegetasi di Kota Ambon pada tahun 2023 yaitu nilai terendah -0,481341 dan nilai tertinggi 0,978457. Kerapatan vegetasi tinggi dapat diartikan sebagai daerah yang memiliki banyak tumbuhan atau vegetasi yang rapat dan padat, sehingga area tersebut memiliki nilai indeks vegetasi yang tinggi [1]. Hasil analisis kerapatan vegetasi menggunakan metode Metode MSARVI (Modified Soil-Adjusted Vegetation Index) menunjukan bahwa daerah yang memiliki kerapatan vegetasi tinggi memiliki luas sebesar 32.856,03 ha atau 85%, daerah yang memiliki kerapatan vegetasi sedang memiliki luas sebesar 3.508,67 ha atau 9,11 % dan daerah yang memiliki kerapatan vegetasi rendah memiliki luas sebesar 2.169,64 ha atau 5,63 %.…”