Investigation and modeling of physical development of urban areas and its effects on light pollution using night light data

BAGHERİ, Samaneh; Karimzadeh, Sadra; Feizizadeh, Bakhtiar

doi:10.26833/ijeg.976495

Cited by 9 publications

(4 citation statements)

References 20 publications

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“…Nighttime lights can monitor the development of urban areas and provide an important perspective which reflects the level of urbanization [37]. As land subsidence also exhibits a strong response to urban construction [38], a static load to some extent, VIIRS nighttime light data can be integrated to simulate the occurrence of land subsidence.…”

Section: Nighttime Light Datamentioning

confidence: 99%

Study on Land Subsidence Simulation Based on a Back-Propagation Neural Network Combined with the Sparrow Search Algorithm

Zhu

Lin

et al. 2023

Remote Sensing

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Rapid simulation of land subsidence can provide an effective means of facilitating its management and control. This paper innovatively introduced a back-propagation (BP) neural network subsidence simulation model which was optimized by the sparrow search algorithm (SSA), hereinafter referred to as the SSA-BP model, to simulate land subsidence in Tongzhou District, Beijing. First, based on the time series interferometric synthetic aperture radar (InSAR) monitoring, different technologies such as spatial analysis, Google Earth Engine (GEE), and machine learning were utilized together with a variety of multi-source spatial data, including groundwater level, compressible layer thickness, Visible Infrared Imager Radiometer Suite (VIIRS) nighttime light images, and the OpenStreetMap (OSM) road distribution. Furthermore, we determined the optimal grid scale for land subsidence research and worked out a multifactor-driven SSA-BP land subsidence simulation model for which sensitivity analysis was performed with great care. Main conclusions: (1) From November 2010 to January 2020, the average annual surface displacement rate in Beijing’s subcentre, Tongzhou, ranged from −133.9 to +3.9 mm/year. (2) Our SSA-BP land subsidence simulation model allows for a relatively high overall accuracy. The average root mean square error (RMSE) is 5.00 mm/year, the average mean absolute error (MAE) is 3.80 mm/year, and the average coefficient of determination (R2) is 0.83. (3) Sensitivity analysis shows that the SSA-BP model driven by multiple factors has a far better simulation performance than the model driven by any single weighting factor, and displays the highest sensitivity to the groundwater level factor among all the weighting factors. In terms of subdividing the study area, our SSA-BP land subsidence model runs with multifunctional zones displayed a higher accuracy than that without. This paper made use of a machine learning model to simulate land subsidence in Beijing’s Tongzhou District and explored the sensitivity of different factors to land subsidence, which is helpful for its scientific prevention.

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Section: Nighttime Light Datamentioning

confidence: 99%

Study on Land Subsidence Simulation Based on a Back-Propagation Neural Network Combined with the Sparrow Search Algorithm

Zhu

Lin

et al. 2023

Remote Sensing

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“…The settlement size data were collected from the Bangladesh Bureau of Statistics. As OpenStreetMap (OSM) is widely available and provides free geographic data on the world's road network, railway network, and airports [50], it was used in this investigation. The downscaling technique was used for raster data to provide homogeneity at different scales, whereas standard spatial resolution was used for data conversion from vector to raster.…”

Section: Data Collectionmentioning

confidence: 99%

Mapping Ecotourism Potential in Bangladesh: The Integration of an Analytical Hierarchy Algorithm and Geospatial Data

Abtahee,

Islam,

Haque

et al. 2023

Sustainability

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The significance of ecotourism has been increasing due to its potential for biodiversity preservation, economic advancement, and the promotion of sustainability awareness. In this research, geospatial analysis and the Analytical Hierarchy Process (AHP) was employed to identify feasible ecotourism sites in Bangladesh. The study applied Geographical Information System–Remote Sensing (GIS-RS) parameters and weighted overlay techniques for selected ecotourism characteristics, such as natural attractiveness, topographic features, accessibility, proximity to facilities, and community characteristics. The study found that a significant proportion (around 44%) of Bangladesh’s land exhibits high potential for ecotourism. Cox’s Bazar, Chittagong, and Rangamati are particularly favorable ecotourism locations. However, some difficulties emerge in regions that are not easily reachable, such as mangrove forests, and in densely inhabited localities like Dhaka. The research also identified the ecological costs linked with ecotourism, such as the exhaustion of resources, the fragmentation of habitats, contamination, and the disruption of wildlife. The primary recommendations to address the adverse effects include educating the local populace, enforcing regulatory measures, implementing efficient waste management systems, enforcing a stringent code of conduct, providing economic incentives to the local communities, and addressing the issue of food security. The cartographically delineated potential zones have the potential to function as a navigational instrument for global travelers and facilitate the decision-making process of policymakers in the realm of sustainable land resource management in Bangladesh. This study enhances the understanding of the potential of ecotourism and offers valuable insights for advancing responsible and sustainable tourism practices within the nation.

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“…By utilizing land and light pollution at different times, we can identify city growth. This research was conducted from 2012 to 2020, which shows that the growth conditions of Taheran City and Tabriz City are experiencing increasingly declining urban growth [7]. NPP-VIIRS can be used to provide a quantitative picture as a source of economic census data on the image of China.…”

Section: Introductionmentioning

confidence: 99%

VIIRS Night-Time Light Image in the Spatial Structure Identification of Banyuwangi Regency

Listyawati,

Prasetiyo,

Nurtjahjaningtyas

2024

IOP Conf. Ser.: Earth Environ. Sci.

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A spatial structure is a hierarchical arrangement of settlement centers and a network system of infrastructure and facilities that support the community’s socio-economic activities. Spatial structure is important because the city’s rapid growth requires regional service center planning. In general, the method for determining the spatial structure uses the Centrality Index (IS) with a variable number of facilities, infrastructure, and people to obtain a hierarchical arrangement of regional service centers. However, this method is often constrained by data limitations, so in this study remote sensing technology was used through night light imagery in identifying potential centers. This study used the Visible and Infrared Imaging Radiometer Suite (VIIRS) sensor, one of the sensors carried by the Suomi-NPP (National Polar-orbiting Operational Environmental Satellite System Preparatory Project) satellite. Identification is done by overlaying the night light image with the existing spatial structure to produce potential centers. Based on the analysis results, eight classifications are based on the light emission interval class, where the higher the class, the higher the light emission value, which indicates the potential for a new center. The Pesanggaran sub-district is in class eight, the Tegaldimo sub-district is in class six, and the Banyuwangi sub-district is in class one.

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Investigation and modeling of physical development of urban areas and its effects on light pollution using night light data

Cited by 9 publications

References 20 publications

Study on Land Subsidence Simulation Based on a Back-Propagation Neural Network Combined with the Sparrow Search Algorithm

Study on Land Subsidence Simulation Based on a Back-Propagation Neural Network Combined with the Sparrow Search Algorithm

Mapping Ecotourism Potential in Bangladesh: The Integration of an Analytical Hierarchy Algorithm and Geospatial Data

VIIRS Night-Time Light Image in the Spatial Structure Identification of Banyuwangi Regency

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