A simulation model for urban development in Bandar Lampung City, Lampung, Indonesia

Wulandari, Ririn Arminsih; Supriatna, Supriatna; Indra, Tito Latif

doi:10.1088/1755-1315/248/1/012090

Cited by 5 publications

(4 citation statements)

References 1 publication

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“…This can be attributed to the increased vegetated land cover and built-up area sparse patch in 2000 -2020 such as seasonal crop plantations, wetland seasonal crops, dry land seasonal crops, and residential buildings based on LPI and LSI values. The mountainous climate supports subsistence agriculture (a common socio-economic activity in the study area) and population growth encourages habitat modification and fragmentation [15,31].…”

Section: Resultsmentioning

confidence: 99%

“…The pixel size used to measure the landscape metrics in this study is a grid with a size of 30 x 30 meters. The landscape metrics calculation was carried out on land cover 2000, 2010, and 2020 and was extracted based analysis unit Van Zuidam's terrain unit classification [13][14][15] with FRAGSTATS 4.2 software. Landscape Indices chosen for several reasons: (1) comparison of landscape patterns with different times or different locations can be realized using landscape metrics [16];…”

Section: Landscape Metrics Calculationmentioning

confidence: 99%

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A spatial study of landscape patterns in landslide-prone areas at cikakak sub-district, west java

Aisyah

Supriatna²,

Rustanto³

2022

IOP Conf. Ser.: Earth Environ. Sci.

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Landslides have a record of deadliest impact in Indonesia during 2015 – 2017. Landslide may be caused by human activities which deteriorate the environment condition such as by reconstructing the landscapes that may reduce the ecological functions. Therefore, mapping the landslide-prone area is necessary as one of the efforts to mitigate the disaster that could be following. The methods used in this study are the landscape metrics with FRAGSTATS 4.2. and Index Storie. Landscape metrics is useful to map the landscape pattern while the Index Storie can be used to map the landslide-prone area, both Indexes then being used for further analysis to determine the relationship between landscape patterns and landslide-prone areas in the study area. Deforestation in the study area is indicated by the values of PD, LPI, and IJI, the Index Storie shows that areas of moderate landslide-prone areas dominate the study area and have specific characteristics that trigger the landslides. A combination of landscape metrics and Index Storie show that the relationship between landscape patterns and landslide-prone areas can be one of the priorities determining tools used for monitoring and planning land cover as an effort to mitigate landslides.

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Section: Resultsmentioning

confidence: 99%

Section: Landscape Metrics Calculationmentioning

confidence: 99%

A spatial study of landscape patterns in landslide-prone areas at cikakak sub-district, west java

Aisyah

Supriatna²,

Rustanto³

2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…The order of Collembola is found at every height of the study site except in open ground. The order is not found in open ground because its regeneration requires canopy shade [37,38]. The order Collembola includes the mesofauna because it measures about <4 mm.…”

Section: The Influence Of Altitude On the Abundance Of Soil Faunamentioning

confidence: 99%

The abundance of soil mesofauna and macrofauna at different altitudes in Mount Gede Pangrango National Park

Wasis,

Fatimah,

Winata

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Soil fauna is important in the breakdown of organic matter for soil fertility. Various environmental factors, including edaphic, climatic factors, and overlying vegetation, influence the abundance of soil fauna. This study aims to analyze the abundance of soil fauna at different altitudes and the influence of the environment on it. The research was conducted at three different altitudes, namely 1,550 m asl, 1,650 m asl, 1,750 m asl, and in open land (1,200 m asl). The LSD test results showed that the abundance of soil fauna significantly differed between the altitude of 1,650 m asl and open land. In comparison, the abundance of soil fauna at the 1,550 m asl and 1,750 m asl was not significantly different at the 95% confidence interval. The results of the correlation analysis show that the climatic factors of light intensity and air temperature are negatively correlated. In contrast, air humidity positively correlates with the abundance of soil fauna. Factors strongly correlated with abundance are litter wet weight and soil pH.

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“…Kebakaran hutan merupakan ancaman serius terhadap ekosistem dan masyarakat di seluruh dunia. Indonesia, sebagai salah satu negara dengan hutan tropis yang luas, juga menghadapi tantangan besar dalam mengelola dan mencegah kebakaran hutan (Wulandari et al, 2019). Salah satu daerah yang rentan terhadap kebakaran hutan adalah Pulau Buru, yang terletak di Provinsi Maluku.…”

Section: Pendahuluanunclassified

Pemetaan Kerentanan Kebakaran Hutan di Pulau Buru, Provinsi Maluku Berdasarkan Fire Hotspot

Abdul Muin,

Heinrich Rakuasa

2023

INSOLOGI: Jurnal Sains dan Teknologi

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Buru Island is one of the areas in Maluku Province where forest fires are common. The prolonged summer season, flammable vegetation and the practice of clearing agricultural land and settlements by burning can also trigger forest fires on Buru Island. This research uses fire hotspots in 2019-2023 obtained from the Fire Information for Resource Management System (FIRMS) and analyzed using the Kernel Density method in Arc GIS software. The results showed that in 2019 there were 224 fire hotspots spread across Buru Island, in 2020 there were 30 fire hotspots, in 2021 there were 31 fire hotspots, in 2022 there were 31 fire hotspots, in 2022 there were 32 fire hotspots and in 2023 there were 23 hotspots spread across Buru Island. The results also show that the level of forest fire vulnerability in the very low vulnerability class has an area of 543,868.30 ha or 63.76%, low vulnerability class of 201,449.44 ha (23.62%), vulnerability class of 83,344.31 (9.77%), and high vulnerability class of 24,327.01 ha or 2.85% of the total area of Buru Island. The results of the study are expected to help the local government in future forest fire disaster mitigation efforts.

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A simulation model for urban development in Bandar Lampung City, Lampung, Indonesia

Cited by 5 publications

References 1 publication

A spatial study of landscape patterns in landslide-prone areas at cikakak sub-district, west java

A spatial study of landscape patterns in landslide-prone areas at cikakak sub-district, west java

The abundance of soil mesofauna and macrofauna at different altitudes in Mount Gede Pangrango National Park

Pemetaan Kerentanan Kebakaran Hutan di Pulau Buru, Provinsi Maluku Berdasarkan Fire Hotspot

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