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Physical assessment of coastal vulnerability under enhanced land subsidence in Semarang, Indonesia, using multi-sensor satellite data

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TLDR
In this article, a coastal vulnerability index (CVI) was constructed to estimate the level of vulnerability of a coastline approximately 48.68 km in length using seven physical variables, namely, land subsidence, relative sea level change, coastal geomorphology, coastal slope, shoreline change, mean tidal range, and significant wave height.
About
This article is published in Advances in Space Research.The article was published on 2018-04-15. It has received 41 citations till now. The article focuses on the topics: Subsidence & Vulnerability index.

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Journal ArticleDOI

Monitoring of long-term land subsidence from 2003 to 2017 in coastal area of Semarang, Indonesia by SBAS DInSAR analyses using Envisat-ASAR, ALOS-PALSAR, and Sentinel-1A SAR data

TL;DR: In this paper, the authors used the Hyperbolic Method (HM) to connect the above unlinked SBAS results, which is often used to fit the monitored subsidence in practice as a geotechnical engineering tool.
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Key Factors Influencing Wider Adoption of Blue–Green Infrastructure in Developing Cities

TL;DR: In this paper, the authors identify socio-economic, cultural and political challenges influencing BGI adoption in Semarang city in Indonesia, and present a framework for facilitating local adoption, setting the principles of "inclusive, appropriate, and proactive" as pre-conditions for enhancing community resilience to flooding.
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Long-Term GIS Analysis of Seaside Impacts Associated to Infrastructures and Urbanization and Spatial Correlation with Coastal Vulnerability in a Mediterranean Area

Salvador García-Ayllón
- 13 Nov 2018 - 
TL;DR: In this article, a long-term GIS analysis has been carried out of the impacts from urbanization and seaside infrastructures suffered by a complex Mediterranean coastal area in Spain.
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Geospatial and statistical interpretation of lineaments: salinity intrusion in the Kribi-Campo coastland of Cameroon

TL;DR: In this article, the authors detected, mapped and analyzed lineaments from Landsat-8 satellite images of the coastal area of Kribi-Campo, Cameroon, to understand its spatial distribution, its extent and the potential effect on inland intrusion of saline water.
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Estimation of ground subsidence of New Delhi, India using PS-InSAR technique and Multi-sensor Radar data

TL;DR: In this article, a detailed investigation of active ground subsidance in New Delhi, National Capital Region (NCR) indicates a high rate of urban growth during the past decades, using multiple SAR sensor data and exploited the PS-InSAR technique.
References
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Book

Remote sensing and image interpretation

TL;DR: In this article, the authors present a textbook for introductory courses in remote sensing, which includes concepts and foundations of remote sensing; elements of photographic systems; introduction to airphoto interpretation; air photo interpretation for terrain evaluation; photogrammetry; radiometric characteristics of aerial photographs; aerial thermography; multispectral scanning and spectral pattern recognition; microwave sensing; and remote sensing from space.
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Remote Sensing and Image Interpretation

TL;DR: In this article, the concept of remote sensing elements of photogrammetry was introduced. Butterfly, thermal, and hyperspectral sensors were used to interpret multispectral, thermal and hypererspectral images.
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The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones:

TL;DR: In this article, the authors undertake the first global review of the population and urban settlement patterns in the Low Elevation Coastal Zone (LECZ), defined as the contiguous area along the coast that is less than 10 meters above sea level.
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Vulnerability to environmental hazards

TL;DR: For over 50 years, hazards researchers have focused on a series of fundamental questions: What is the human occupancy of hazard zones? How do people and societies respond to environmental hazards and whatfactors influence their choice of adjustments?.
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Radar interferogram filtering for geophysical applications

TL;DR: In this paper, a new adaptive filtering algorithm was proposed to dramatically lower phase noise, improving both measurement accuracy and phase unwrapping, while demonstrating graceful degradation in regions of pure noise.
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