On Integration of Geodetic Observation Results for Assessment of Land Subsidence Hazard Risk in Urban Areas of Indonesia

2015 ◽  
pp. 435-442 ◽  
Author(s):  
Hasanuddin Z. Abidin ◽  
Heri Andreas ◽  
Irwan Gumilar ◽  
Bambang D. Yuwono ◽  
Dodid Murdohardono ◽  
...  
Keyword(s):  
Land Subsidence ◽  
Urban Areas ◽  
Geodetic Observation ◽  
Hazard Risk ◽  
Observation Results

The experience of monitoring the land subsidence in urban areas by radar satellite interferometry on the example of St. Petersburg

2020 ◽  
Vol 64 (4) ◽  
pp. 399-408
Author(s):  
Shirshova V. ◽  
Keyword(s):  
Land Subsidence ◽  
Urban Areas ◽  
Radar Satellite

Разработана и опробована методика мониторинга на основе метода радиолокационной спутниковой интерферометрии с применением открытых данных радиолокационного спутника Sentinel-1. Обработка радиолокационных снимков была реализована на открытом программном обеспечении SNAP. В результате были получены 40 карт вертикальных смещений города Санкт-Петербург. На основе геоинформационного программного обеспечения QGIS был произведен анализ полученных карт смещений и визуализация результатов интерферометрической обработки.

scholarly journals Chronological reflection on monitoring urban areas subsidence due to groundwater extraction

2019 ◽  
Vol 85 ◽  
pp. 07015 ◽  
Author(s):  
Alina Radutu ◽  
Radu Constantin Gogu
Keyword(s):  
Land Subsidence ◽  
Urban Areas ◽  
Urban Expansion ◽  
Groundwater Withdrawal ◽  
Groundwater Extraction ◽  
Monitoring Methods ◽  
Vertical Displacements ◽  
Order Of Magnitude ◽  
History Of ◽  
Subsidence Monitoring

Land subsidence affects urban areas worldwide. Sometimes it could be driven by intensive groundwater withdrawal to assure different urban needs and functionalities. Some of these urban areas have a long history of subsidence that covers almost a century. The aim of this paper is to present the evolution of several urban areas affected by land subsidence, the methods used to monitor vertical displacements along the decades in relationship to the groundwater extraction associated to the urban expansion, and the mitigation techniques used for countering the effects of intensive groundwater withdrawal. Even the originally applied subsidence monitoring methods (such as geometric levelling) are still very sensitive, in terms of time consuming, covered area, and financial effort, these methods might be complemented by new methods based on Synthetic Aperture Radar Interferometry (InSAR). InSAR methods show also a significant progress during the last decades when considering the subsidence sensed order of magnitude.

Landslide hazard risk mapping based on Random Forest Classification in Ruijin, Jiangxi, China

2020 ◽  
Author(s):  
Zhou Xiaoting ◽  
Weicheng Wu ◽  
Ziyu Lin ◽  
Guiliang Zhang ◽  
Renxiang Chen ◽  
...  
Keyword(s):  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Road Traffic ◽  
Road Construction ◽  
Buffer Zone ◽  
Landslide Risk ◽  
Risk Area ◽  
Hazard Risk ◽  
Forest Classification

<p>Landslides are common geological hazards that not only affect the normal road traffic but also pose a great threat and damage to human lives and properties. This study aims to conduct such a hazard risk mapping using Random Forest Classification (RFC) approach taking Ruijin County in Jiangxi, China as an example. Multi-source data namely terrain (DEM, slope and aspect), precipitation, the normalized difference vegetation index (NDVI) representing vegetation condition and abundance, strata and their lithology, distance to roads, distance to rivers, distance to faults, thickness of weathering crust, soil type and texture, etc., were employed for this study. The non-numeric data such as geological strata, soil units, faults, were spatialized and assigned values in terms of their susceptibility to landslide. Similarly, linear features such as roads, rivers and faults were buffered with distances of 0-30, 30-60, 60-90 and 90-120 m and each buffer zone was assigned a susceptibility value of landslide, e.g., zones 0-30, 30-60, 60-90 and 90-120 of road buffers were assigned respectively 10, 7, 4, and 1, meaning that the closer to the road, the higher risk of landslide. In total, 16 hazard factor layers were derived and converted into raster. 156 landslide hazards that have truly taken places (points) and been verified in field were used to create a training set (TS, 70% of total landslides) and a validation set (VS, 30%) by buffering-based rasterization procedure. A number of polygons were defined in places where landslide is unlikely to occur, e.g., water bodies, zero-slope plain, and urban areas. These polygons were added to the TS as non-risk area. Then, RFC was conducted to model the probability of landslide risk using these 16 factor layers as predictors and TS for training. The obtained RF model was applied back to the 16 factor layers to predict the probability of landslide risk at each pixel in the whole county. The prediction map was checked against the VS and found that the Overall Accuracy and Kappa Coefficient are respectively 92.18% and 0.8432, and the landslide-prone areas are mainly distributed on two sides of the roads. The results reveal that extremely high-risk zones with a probability of more than 0.9 take up 76.70 km<sup>2</sup> in the county, and the distance to roads is the most important factor followed by precipitation among all factors causing landslides as road construction and housing development cut off slopes leading to instability of the weathered crust; and heavy rainfalls trigger the instability. Our study shows that the RFC prediction has high accuracy and in good consistency with field observation.</p>

scholarly journals Extensive Investigation of the Land Subsidence Impressions on Gedebage District, Bandung, Indonesia

2021 ◽  
Vol 873 (1) ◽  
pp. 012044
Author(s):  
I Gumilar ◽  
TP. Sidiq ◽  
I Meilano ◽  
B Bramanto ◽  
G Pambudi
Keyword(s):  
Land Subsidence ◽  
Urban Areas ◽  
Average Rate ◽  
Satellite System ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Infrastructure Development ◽  
Global Navigation Satellite ◽  
Almost All ◽  
The Impact

Abstract Gedebage district is presently experiencing rapid and mass infrastructure development and becoming one of the developed districts in Bandung, Indonesia. A football stadium, several luxury housing, the grand mosque of West Java province, and a business center have been built in this district. However, it is well known that the Gedebage district has turned into one of the Bandung districts that suffers from land subsidence phenomena. Since 2000, the Gedebage district has suffered land subsidence at an average rate of 10 cm per year and becoming one of the fastest sinking districts in Bandung. This fast land subsidence phenomenon is suspected of affecting the infrastructure in this district. Therefore, this work aims to capture the current subsidence rate in the Gedebage district using the geodetic approach of the combination of the Global Navigation Satellite System (GNSS) with Interferometric Synthetic Aperture Radar (InSAR) and investigate the impact of land subsidence on infrastructures in Gedebage district. We use GNSS campaign datasets from the years 2016 and 2019. Each GNSS campaign was performed at least 10-12 hours of observations. We also utilize a similar period of 2016 to 2019 for the InSAR datasets. Utilizing both GNSS and InSAR datasets, we can capture the subsidence with the rate reaching 4 -15 cm per year between 2016 and 2019, and it occurs uniformly in this district. The impact of land subsidence occurred in almost all urban areas in the Gedebage district. These impacts include cracks in buildings, bridges and roads, and also tilted buildings.

scholarly journals Validated 3D Spatial Stepwise Quantitative Hazard, Risk and Resilience Analysis and Management of Explosive Events in Urban Areas

2018 ◽  
Vol 4 (1) ◽  
pp. 93-129 ◽  
Author(s):  
Ivo Häring ◽  
Malte von Ramin ◽  
Alexander Stottmeister ◽  
Johannes Schäfer ◽  
Georg Vogelbacher ◽  
...  
Keyword(s):  
Urban Areas ◽  
Risk And Resilience ◽  
Hazard Risk ◽  
Explosive Events

scholarly journals Investigation of Groundwater Withdrawal and Recharge Affecting Underground Structures in the Shanghai Urban Area

2019 ◽  
Vol 11 (24) ◽  
pp. 7162 ◽  
Author(s):  
Yong-Xia Wu ◽  
Tian-Liang Yang ◽  
Pei-Chao Li ◽  
Jin-Xin Lin
Keyword(s):  
Land Subsidence ◽  
Urban Areas ◽  
Water Pressure ◽  
Underground Structure ◽  
Pressure Head ◽  
Groundwater Withdrawal ◽  
Underground Structures ◽  
Groundwater Head ◽  
Increased Risk ◽  
Confined Aquifers

In this paper, the hydrogeological features of Quaternary deposits in Shanghai as well as the characteristics of groundwater withdrawal and recharge in urban areas are investigated. One phreatic aquifer and five confined aquifers (AqI to AqV) are present in Shanghai, and these aquifers are separated by five aquitards. Groundwater withdrawal from confined aquifers has resulted in land subsidence in Shanghai. To control land subsidence, the groundwater withdrawal volume has been decreased, and the groundwater recharge volume has been increased since 1965. Correspondingly, the pressure head in confined aquifers has risen. The groundwater head increases in shallow aquifers may impact underground structures and lead to the following issues: i) an increased risk of water in-rushing hazards caused by confined water pressure during structural excavations and ii) an increased instability risk caused by groundwater buoyancy. Both excavation anti-uprush and underground structure anti-floating are discussed in this paper. Based on the risk possibilities, the anti-uprush of the excavation is divided into six regions, and the structural anti-floating is divided into five regions in urban areas. To avoid geohazards caused by the rise in groundwater head, real-time monitoring of the pressure head in AqII is recommended.

scholarly journals Spatially Varying Relationships between Land Subsidence and Urbanization: A Case Study in Wuhan, China

2022 ◽  
Vol 14 (2) ◽  
pp. 291
Author(s):  
Zhengyu Wang ◽  
Yaolin Liu ◽  
Yang Zhang ◽  
Yanfang Liu ◽  
Baoshun Wang ◽  
...  
Keyword(s):  
Spatial Pattern ◽  
Land Subsidence ◽  
Urban Areas ◽  
Spatial Scales ◽  
Moran’S I ◽  
Anthropogenic Factors ◽  
Spatial Correlations ◽  
Moran's I ◽  
Average Value ◽  
Gwr Model

Land subsidence has become an increasing global concern over the past few decades due to natural and anthropogenic factors. However, although several studies have examined factors affecting land subsidence in recent years, few have focused on the spatial heterogeneity of relationships between land subsidence and urbanization. In this paper, we adopted the small baseline subset-synthetic aperture radar interferometry (SBAS-InSAR) method using Sentinel-1 radar satellite images to map land subsidence from 2015 to 2018 and characterized its spatial pattern in Wuhan. The bivariate Moran’s I index was used to test and visualize the spatial correlations between land subsidence and urbanization. A geographically weighted regression (GWR) model was employed to explore the strengths and directions of impacts of urbanization on land subsidence. Our findings showed that land subsidence was obvious and unevenly distributed in the study area, the annual deformation rate varied from −42.85 mm/year to +29.98 mm/year, and its average value was −1.0 mm/year. A clear spatial pattern for land subsidence in Wuhan was mapped, and several apparent subsidence funnels were primarily located in central urban areas. All urbanization indicators were found to be significantly spatially correlated with land subsidence at different scales. In addition, the GWR model results showed that all urbanization indicators were significantly associated with land subsidence across the whole study area in Wuhan. The results of bivariate Moran’s I and GWR results confirmed that the relationships between land subsidence and urbanization spatially varied in Wuhan at multiple spatial scales. Although scale dependence existed in both the bivariate Moran’s I and GWR models for land subsidence and urbanization indicators, a “best” spatial scale could not be confirmed because the disturbance of factors varied over different sampling scales. The results can advance the understanding of the relationships between land subsidence and urbanization, and they will provide guidance for subsidence control and sustainable urban planning.

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