Spatial modelling of land use/cover change (LUCC) in South Tangerang City, Banten

Saifullah, Khalid; Barus, Baba; Rustiadi, Ernan

doi:10.1088/1755-1315/54/1/012018

Cited by 8 publications

(7 citation statements)

References 12 publications

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“…The first stations is located in Serpong as part of South Tangerang City (-6°21'46.8"S, 106°40'12"E). South Tangerang City is an example of urban expansion phenomenon in peri-urban region [12]. South Tangerang City is one of the rapid urban expansions of residential areas.…”

Section: The Study Areamentioning

confidence: 99%

Investigating the relationship between variation of greenhouse gases concentrations and humidex

Marufatin

Kusnoputranto

Kardono³

2018

E3S Web Conf.

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The increasing greenhouse gases (GHGs) in the atmosphere contribute to increasing average temperature earth’s surface. This research investigated relationship between variation of GHGs and human thermal comfort based on humidity index (humidex). This study applied humidex, an indices to assess the thermal comfort. The analysis was done by examining the observational data from two different monitoring stations in Serpong and Bogor. The result showed that the average CO2 concentration per month ranged between 422 and 453 ppm in Serpong, whereas in Bogor the average CO2 concentration per month was 413-426 ppm. The average CH4 concentration per month variation in Serpong was 2.05-2.65 ppm. While in Bogor, the average CH4 concentration per month variation ranged between 1.92 and 2.08 ppm. The difference of GHGs concentration in each location might be influenced by meteorological parameters and environmental characteristics. The comfort level according to humidex in Serpong was 30.5-41.5 whereas in Bogor was 29.4-38.5. The correlation between GHGs concentration and air temperature in urban areas in both stations showed a significant and strong but negative relationship. The relationship between GHGs concentration and humidex was indirectly indicated by the relationship of GHGs concentration on air temperature as indicator of humidex.

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Section: The Study Areamentioning

confidence: 99%

Investigating the relationship between variation of greenhouse gases concentrations and humidex

Marufatin

Kusnoputranto

Kardono³

2018

E3S Web Conf.

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“…The percentage of area differences in land-use classes was less than 8%. Considering this level of agreement, the model was found eligible to predict the changes for 2032, 2062 and 2092 (Saifullah et al 2017).…”

Section: Land Change Modelermentioning

confidence: 93%

Potential influence of climate and land-use changes on green water security in a semi-arid catchment

Abbasi

Amirabadizadeh

Afshar

et al. 2021

Journal of Water and Climate Change

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Temporal and spatial changes of green water (GW) security due to climate and land-use/land-cover (LULC) changes can be used to make the best decision for sustainable GW management. In this study, simultaneous effects of climate and LULC changes on water resources in Kashafrood Basin were evaluated by Soil and Water Assessment Tool (SWAT). Land change modeler was set up to monitor LULC, assess changes and make predictions. The MIROC-ESM model derived from Coupled Model Intercomparison Project Phase 5 under two representative concentration pathway (RCP) emission scenarios RCP2.6 and RCP8.5 was applied to evaluate the effects of climate change. Two indices of GW-Scarcity and GW-Vulnerability, representing GW-Security, were quantified using the GW-Footprint concept in Kashafrood Basin. The results show that the annual average of blue water was predicted to increase by 142–350%, and GW storage and the annual averages of GW flow were predicted to decrease by 12–65 and 8–20%, respectively, depending on emission scenarios and time. The GW-Security estimates in the entire basin suggest a better condition in the future by indicating 24–45 and 16–52% decreases in GW-Scarcity and GW-Vulnerability, respectively, depending on emission scenarios and time.

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“…Beginning with the least influential variable in the model's accuracy and skill, the next least influential variable is added, and additional variables sequentially added until only one variable, the most influential remains. This process informs the model development as it identifies those variables that did not significantly improve the overall accuracy of the model and can be permanently excluded [30,31]. The above sensitivity tests provide valuable information that the MLP use to generate the most parsimonious model.…”

Section: Model Development and Projectionsmentioning

confidence: 98%

New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss

Hewson

Crema

González‐Roglich

et al. 2019

Land

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Despite global recognition of the social, economic and ecological impacts of deforestation, the world is losing forests at an alarming rate. Global and regional efforts by policymakers and donors to reduce deforestation need science-driven information on where forest loss is happening, and where it may happen in the future. We used spatially-explicit globally-consistent variables and global historical tree cover and loss to analyze how global- and regional-scale variables contributed to historical tree cover loss and to model future risks of tree cover loss, based on a business-as-usual scenario. Our results show that (1) some biomes have higher risk of tree cover loss than others; (2) variables related to tree cover loss at the global scale differ from those at the regional scale; and (3) variables related to tree cover loss vary by continent. By mapping both tree cover loss risk and potential future tree cover loss, we aim to provide decision makers and donors with multiple outputs to improve targeting of forest conservation investments. By making the outputs readily accessible, we anticipate they will be used in other modeling analyses, conservation planning exercises, and prioritization activities aimed at conserving forests to meet national and global climate mitigation targets and biodiversity goals.

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Spatial modelling of land use/cover change (LUCC) in South Tangerang City, Banten

Cited by 8 publications

References 12 publications

Investigating the relationship between variation of greenhouse gases concentrations and humidex

Investigating the relationship between variation of greenhouse gases concentrations and humidex

Potential influence of climate and land-use changes on green water security in a semi-arid catchment

New 1 km Resolution Datasets of Global and Regional Risks of Tree Cover Loss

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