The Space-Borne SBAS-DInSAR Technique as a Supporting Tool for Sustainable Urban Policies: The Case of Istanbul Megacity, Turkey

In today’s urbanizing world, home of 28 megacities, there is a growing need for tools to assess urban policies and support the design and implementation of effective development strategies. Unsustainable practices of urbanization bring major implications for land and environment, and cause a dramatic increase of urban vulnerability to natural hazards. In Istanbul megacity, disaster risk reduction represents a challenging issue for urban managers. In this paper, we show the relevance of the space-borne Differential SAR Interferometry (DInSAR) technique as a tool for supporting risk management, and thus contributing to achieve the urban sustainability. To this aim, we use a dataset of high resolution SAR images collected by the TerraSAR-X satellite that have been processed through the advanced (multi-temporal) Small BAseline Subset (SBAS)—DInSAR technique, thus producing spatially-dense deformation velocity maps and associated time-series. Results allow to depict an up-to-date picture of surface deformations occurring in Istanbul, and thus to identify urban areas subject to potential risk. The joint analysis of remotely sensed measurements and ancillary data (geological and urban development information) provides an opportunity for city planners and land professionals to discuss on the mutual relationship between urban development policies and natural/man-made hazards

Testing the generalization efficiency of oil slick classification algorithm using multiple sar data for deepwater horizon oil spill

Marine oil spills due to releases of crude oil from tankers, offshore platforms, drilling rigs and wells, etc. are seriously affecting the fragile marine and coastal ecosystem and cause political and environmental concern. A catastrophic explosion and subsequent fire in the Deepwater Horizon oil platform caused the platform to burn and sink, and oil leaked continuously between April 20th and July 15th of 2010, releasing about 780,000 m3 of crude oil into the Gulf of Mexico. Today, space-borne SAR sensors are extensively used for the detection of oil spills in the marine environment, as they are independent from sun light, not affected by cloudiness, and more cost-effective than air patrolling due to covering large areas. In this study, generalization extent of an object based classification algorithm was tested for oil spill detection using multiple SAR imagery data. Among many geometrical, physical and textural features, some more distinctive ones were selected to distinguish oil and look alike objects from each others. The tested classifier was constructed from a Multilayer Perception Artificial Neural Network trained by ABC, LM and BP optimization algorithms. The training data to train the classifier were constituted from SAR data consisting of oil spill originated from Lebanon in 2007. The classifier was then applied to the Deepwater Horizon oil spill data in the Gulf of Mexico on RADARSAT-2 and ALOS PALSAR images to demonstrate the generalization efficiency of oil slick classification algorithm. 5 Yildiz Technical University, Civil Engineering Faculty, Geodesy and Photogrammetry Engineering Dept., Davutpasa Campus, 34220 Esenler, Istanbul, Turkey

The Space-Borne SBAS-DInSAR Technique as a Supporting Tool for Sustainable Urban Policies: The Case of Istanbul Megacity, Turkey

In today’s urbanizing world, home of 28 megacities, there is a growing need for tools to assess urban policies and support the design and implementation of effective development strategies. Unsustainable practices of urbanization bring major implications for land and environment, and cause a dramatic increase of urban vulnerability to natural hazards. In Istanbul megacity, disaster risk reduction represents a challenging issue for urban managers. In this paper, we show the relevance of the space-borne Differential SAR Interferometry (DInSAR) technique as a tool for supporting risk management, and thus contributing to achieve the urban sustainability. To this aim, we use a dataset of high resolution SAR images collected by the TerraSAR-X satellite that have been processed through the advanced (multi-temporal) Small BAseline Subset (SBAS)—DInSAR technique, thus producing spatially-dense deformation velocity maps and associated time-series. Results allow to depict an up-to-date picture of surface deformations occurring in Istanbul, and thus to identify urban areas subject to potential risk. The joint analysis of remotely sensed measurements and ancillary data (geological and urban development information) provides an opportunity for city planners and land professionals to discuss on the mutual relationship between urban development policies and natural/man-made hazards

DInSAR-Based Detection of Land Subsidence and Correlation with Groundwater Depletion in Konya Plain, Turkey

In areas where groundwater overexploitation occurs, land subsidence triggered by aquifer compaction is observed, resulting in high socio-economic impacts for the affected communities. In this paper, we focus on the Konya region, one of the leading economic centers in the agricultural and industrial sectors in Turkey. We present a multi-source data approach aimed at investigating the complex and fragile environment of this area which is heavily affected by groundwater drawdown and ground subsidence. In particular, in order to analyze the spatial and temporal pattern of the subsidence process we use the Small BAseline Subset DInSAR technique to process two datasets of ENVISAT SAR images spanning the 2002–2010 period. The produced ground deformation maps and associated time-series allow us to detect a wide land subsidence extending for about 1200 km2 and measure vertical displacements reaching up to 10 cm in the observed time interval. DInSAR results, complemented with climatic, stratigraphic and piezometric data as well as with land-cover changes information, allow us to give more insights on the impact of climate changes and human activities on groundwater resources depletion and land subsidence