Spatiotemporal deformation patterns of the Lake Urmia Causeway as characterized by multisensor InSAR analysis

Karimzadeh, Sadra; Matsuoka, M.; Ogushi, Fumitaka

doi:10.1038/s41598-018-23650-6

Cited by 28 publications

(10 citation statements)

References 19 publications

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“…Although SBAS is a technique, it can also be considered as an algorithm for SAR processing too. Previous studies revealed that SBAS was an effective technique to monitor land subsidence in Iran [30][31][32][33][34][35]52]. Here, we follow the SBAS InSAR method introduced by Berardino et al to derive mean velocity displacement values.…”

Section: Sbas Time Series Analysismentioning

confidence: 99%

Remote Sensing X-Band SAR Data for Land Subsidence and Pavement Monitoring

Karimzadeh

Matsuoka

2020

Sensors

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In this study, we monitor pavement and land subsidence in Tabriz city in NW Iran using X-band synthetic aperture radar (SAR) sensor of Cosmo-SkyMed (CSK) satellites (2017–2018). Fifteen CSK images with a revisit interval of ~30 days have been used. Because of traffic jams, usually cars on streets do not allow pure backscattering measurements of pavements. Thus, the major paved areas (e.g., streets, etc.) of the city are extracted from a minimum-based stacking model of high resolution (HR) SAR images. The technique can be used profitably to reduce the negative impacts of the presence of traffic jams and estimate the possible quality of pavement in the HR SAR images in which the results can be compared by in-situ road roughness measurements. In addition, a time series small baseline subset (SBAS) interferometric SAR (InSAR) analysis is applied for the acquired HR CSK images. The SBAS InSAR results show land subsidence in some parts of the city. The mean rate of line-of-sight (LOS) subsidence is 20 mm/year in district two of the city, which was confirmed by field surveying and mean vertical velocity of Sentinel-1 dataset. The SBAS InSAR results also show that 1.4 km2 of buildings and 65 km of pavement are at an immediate risk of land subsidence.

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Section: Sbas Time Series Analysismentioning

confidence: 99%

Remote Sensing X-Band SAR Data for Land Subsidence and Pavement Monitoring

Karimzadeh

Matsuoka

2020

Sensors

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“…New satellite constellations of SAR missions such as Cosmo-SkyMed, TerraSAR-X, and ALOS-2 can guarantee high-resolution SAR data for different applications. SAR interferometry (InSAR) is a powerful technique that uses the phase and amplitude information of at least two SAR images with the same geometry and characteristics to extract the displacement rate of earthquakes [19][20][21][22][23][24][25][26], ground subsidence [14][15][16][17][18], volcanic activity [27][28][29][30], mining activities [7,31], structures [32][33][34], and landslides [35][36][37][38][39][40][41][42]. The technique enables us to overcome the challenges of conventional methods.…”

Section: Introductionmentioning

confidence: 99%

Ground Displacement in East Azerbaijan Province, Iran, Revealed by L-band and C-band InSAR Analyses

Karimzadeh

Matsuoka

2020

Sensors

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Iran, as a semi-arid and arid country, has a water challenge in the recent decades and underground water extraction has been increased because of improper developments in the agricultural sector. Thus, detection and measurement of ground subsidence in major plains is of great importance for hazard mitigation purposes. In this study, we carried out a time series small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) analysis of 15 L-band PALSAR-2 images acquired from ascending orbits of the ALOS-2 satellite between 2015 and 2020 to investigate long-term ground displacements in East Azerbaijan Province, Iran. We found that two major parts of the study area (Tabriz and Shabestar plains) are subsiding, where the mean and maximum vertical subsidence rates are −10 and −98 mm/year, respectively. The results revealed that the visible subsidence patterns in the study area are associated with either anthropogenic activities (e.g., underground water usage) or presence of compressible soils along the Tabriz–Shabestar and Tabriz–Azarshahr railways. This implies that infrastructure such as railways and roads is vulnerable if progressive ground subsidence takes over the whole area. The SBAS results deduced from L-band PALSAR-2 data were validated with field observations and compared with C-band Sentinel-1 results for the same period. The C-band Sentinel-1 results showed good agreement with the L-band PALSAR-2 dataset, in which the mean and maximum vertical subsidence rates are −13 and −120 mm/year, respectively. For better visualization of the results, the SBAS InSAR velocity map was down-sampled and principal component analysis (PCA) was performed on ~3600 randomly selected time series of the study area, and the results are presented by two principal components (PC1 and PC2).

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“…However, there are more processes related to irrigation and reduced water availability that might lead to unusable agricultural land, such as degradation of soils (e.g. salinization) 55 , subsidence 47,78 , desertification 79,80 , and sink hole formation because of lowered groundwater tables 81,82 . Until recently, the share of degrading crop areas in the wetter northwest of Iran is rather low, however it might increase in the future if water will continue to be used as unsustainably as in the last decades.…”

Section: Agricultural Areas and Associated Vegetation Growthmentioning

confidence: 99%

Interrelations of vegetation growth and water scarcity in Iran revealed by satellite time series

Behling

Roessner

Foerster

et al. 2022

Sci Rep

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Iran has experienced a drastic increase in water scarcity in the last decades. The main driver has been the substantial unsustainable water consumption of the agricultural sector. This study quantifies the spatiotemporal dynamics of Iran’s hydrometeorological water availability, land cover, and vegetation growth and evaluates their interrelations with a special focus on agricultural vegetation developments. It analyzes globally available reanalysis climate data and satellite time series data and products, allowing a country-wide investigation of recent 20+ years at detailed spatial and temporal scales. The results reveal a wide-spread agricultural expansion (27,000 km$$^2$$ 2 ) and a significant cultivation intensification (48,000 km$$^2$$ 2 ). At the same time, we observe a substantial decline in total water storage that is not represented by a decrease of meteorological water input, confirming an unsustainable use of groundwater mainly for agricultural irrigation. As consequence of water scarcity, we identify agricultural areas with a loss or reduction of vegetation growth (10,000 km$$^2$$ 2 ), especially in irrigated agricultural areas under (hyper-)arid conditions. In Iran’s natural biomes, the results show declining trends in vegetation growth and land cover degradation from sparse vegetation to barren land in 40,000 km$$^2$$ 2 , mainly along the western plains and foothills of the Zagros Mountains, and at the same time wide-spread greening trends, particularly in regions of higher altitudes. Overall, the findings provide detailed insights in vegetation-related causes and consequences of Iran’s anthropogenic drought and can support sustainable management plans for Iran or other semi-arid regions worldwide, often facing similar conditions.

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Spatiotemporal deformation patterns of the Lake Urmia Causeway as characterized by multisensor InSAR analysis

Cited by 28 publications

References 19 publications

Remote Sensing X-Band SAR Data for Land Subsidence and Pavement Monitoring

Remote Sensing X-Band SAR Data for Land Subsidence and Pavement Monitoring

Ground Displacement in East Azerbaijan Province, Iran, Revealed by L-band and C-band InSAR Analyses

Interrelations of vegetation growth and water scarcity in Iran revealed by satellite time series

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