Editorial for Special Issue “Monitoring Land Subsidence Using Remote Sensing”

Fabris, Massimo; Cenni, Nicola; Fiaschi, Simone

doi:10.3390/rs13091771

Cited by 5 publications

(1 citation statement)

References 22 publications

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“…Land subsidence is one of the main problems in coastal cities and deltas worldwide caused by natural and or human activities, including in Indonesia (Buffardi & Ruberti, 2023). This problem has existed since the 1980s until now, due to rapid physical development and exacerbating sustainable development in the future (Pravitasari et al, 2020(Pravitasari et al, , 2022Sarah, 2022).…”

Section: Background Of the Studymentioning

confidence: 99%

Combined Land Subsidence Analysis in Jakarta Based on Ps-InSAR and MICMAC Methods

Handika,

Widodo,

Pravitasari

2024

Jurtekling

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Penurunan muka tanah menjadi salah satu masalah di kota-kota pesisir delta di dunia, seperti Jakarta. Di kota ini, penurunan tanah sudah merata di seluruh wilayah. Berbagai faktor penyebab penurunan muka tanah dapat menimbulkan dampak secara ekologi, ekonomi, maupun sosial. Dampak yang terjadi umumnya berupa retaknya bangunan dan perluasan banjir. Oleh karena itu, kami perlu melakukan pengukuran dan pemantauan secara cepat dan berkala. Persistent Scatterer Interferometry Synthetic Aperture Radar (PS-InSAR) ialah metode yang digunakan untuk mendeteksi besaran nilai penurunan muka tanah di daerah perkotaan. Metode ini mampu menghasilkan gambar SAR dari distribusi ribuan titik pantau identifikasi faktor penyebab penurunan muka tanah di Jakarta. Hasil PS-InSAR terdeteksi nilai laju penurunan muka tanah rata-rata sebesar -5,71 cm/tahun, yang dominan berada di wilayah Jakarta Utara dan Jakarta Barat. Terdapat beberapa faktor penyebab penurunan muka tanah, kami melakukan analisis faktor ini menggunakan metode MICMAC (Matrix of Cross Impact Multiplications Applied to a Classification). Metode ini membantu mengidentifikasi hubungan dan relevansi antar faktor penyebab penurunan muka tanah. Hasil metode ini menunjukkan bahwa eksploitasi air tanah berlebihan dan konsolidasi alami tanah aluvial sebagai faktor yang berpengaruh signifikan terjadinya penurunan muka tanah di wilayah Jakarta. Abstract Land subsidence is one of the problems in delta coastal cities in the world, such as Jakarta. In this city, land subsidence has been evenly distributed throughout the region. Various factors causing land subsidence can have ecological, economic, and social impacts. The impacts that occur generally include the cracking of buildings and the expansion of flooding. Therefore, we need to carry out measurements and monitoring quickly and regularly. Persistent Scatterer Interferometry Synthetic Aperture Radar (PS-InSAR) is a method used to detect the magnitude of land subsidence in urban areas. This method is capable of producing SAR images from the distribution of thousands of monitoring points to identify factors causing land subsidence in Jakarta. PS-InSAR results detected an average land subsidence rate of -5.71 cm/year, which was dominant in the North Jakarta and West Jakarta areas. Several factors cause land subsidence, we analyzed these factors using the MICMAC (Matrix of Cross Impact Multiplications Applied to a Classification) method. This method helps identify the relationship and relevance between factors causing land subsidence. The results of this method produce excessive groundwater exploitation and natural consolidation of alluvial soil as factors that have a significant influence on land subsidence in the Jakarta area.

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Section: Background Of the Studymentioning

confidence: 99%

Combined Land Subsidence Analysis in Jakarta Based on Ps-InSAR and MICMAC Methods

Handika,

Widodo,

Pravitasari

2024

Jurtekling

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Land subsidence hazard assessment based on novel hybrid approach: BWM, weighted overlay index (WOI), and support vector machine (SVM)

et al. 2022

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Land subsidence is a morphological phenomenon, which causes negative environmental and economic consequences for human societies. Therefore, identifying the areas prone to subsidence can be one of the necessary measures for reducing the potential risks. This study aims to evaluate the efficiency of the support vector machine (SVM) algorithm and weighted overlay index (WOI) models in zoning the rate of land subsidence hazard in Hashtgerd plain, Iran. First, the 19 criteria include groundwater depletion, groundwater extraction, aquifer thickness, alluvium thickness, aquifer recharge, well density, drainage density, groundwater depth, lithology, bedrock depth, average annual precipitation, average annual temperature, climate type, agricultural use, urban use, industrial use, distance from rivers and streams, distance from roads, distance from faults were considered. Then, the layers were weighed based on the Best-Worst Method (BWM). The results of BWM indicated that the factors of groundwater extraction (0.219), lithology (0.157), and groundwater depletion (0.079) have a greater effect on the potential for subsidence hazard. Moreover, the results of validation by performing ROC curve showed that the accuracy of RBF-SVM, LN-SVM, SIG-SVM, PL-SVM, and WOI were 95.7, 94.3, 94.9, 93.2, and 90%, respectively. Based on the ROC results, all of the models for preparing the subsidence hazard map in Hashtgerd plain exhibit excellent accuracy. Therefore, all of the models used here can predict the areas vulnerable to subsidence properly. In this study, the five land subsidence hazard maps were used as new input factors and integrated using fuzzy gamma-ensemble methods to make better hazard maps. The results of the ensemble model indicated that 19.3% of Hashtgerd plain is in the zone of high to very high sensitivity. The results of this study can help planners in managing and reducing the possible hazards of subsidence.

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Land subsidence susceptibility mapping based on InSAR and a hybrid machine learning approach

Alesheikh,

Chatrsimab,

Rezaie

et al. 2024

The Egyptian Journal of Remote Sensing and Space Sciences

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Editorial for Special Issue “Monitoring Land Subsidence Using Remote Sensing”

Abstract: Land subsidence is a geological hazard that affects several different communities around the world [...]

Cited by 5 publications

References 22 publications

Combined Land Subsidence Analysis in Jakarta Based on Ps-InSAR and MICMAC Methods

Combined Land Subsidence Analysis in Jakarta Based on Ps-InSAR and MICMAC Methods

Land subsidence hazard assessment based on novel hybrid approach: BWM, weighted overlay index (WOI), and support vector machine (SVM)

Land subsidence susceptibility mapping based on InSAR and a hybrid machine learning approach

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