Urban Built-Up Area Estimation and Change Detection of the Occupied West Bank, Palestine, Using Multi-temporal Aerial Photographs and Satellite Images

2019 ◽  
Vol 48 (2) ◽  
pp. 235-247 ◽  
Author(s):  
Ahmed Ghodieh
Keyword(s):  
Change Detection ◽  
Satellite Images ◽  
West Bank ◽  
Aerial Photographs ◽  
Area Estimation ◽  
Multi Temporal

scholarly journals Multi-temporal Satellite Images Change Detection Algorithm Based on NSCT

2011 ◽  
Vol 24 ◽  
pp. 252-256 ◽  
Author(s):  
Wei Cui ◽  
Zhenhong Jia ◽  
Xizhong Qin ◽  
Jie Yang ◽  
Yingjie Hu
Keyword(s):  
Change Detection ◽  
Satellite Images ◽  
Detection Algorithm ◽  
Multi Temporal

scholarly journals Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

2017 ◽  
Vol 9 (8) ◽  
pp. 804 ◽  
Author(s):  
Biao Wang ◽  
Jaewan Choi ◽  
Seokeun Choi ◽  
Soungki Lee ◽  
Penghai Wu ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Change Detection ◽  
Image Fusion ◽  
Land Cover Change ◽  
Satellite Images ◽  
High Resolution Satellite Images ◽  
Multi Temporal ◽  
Land Cover Change Detection

scholarly journals Multi-Temporal Change Detection Analysis of Vertical Sprawl over Limassol City Centre and Amathus Archaeological Site in Cyprus during 2015–2020 Using the Sentinel-1 Sensor and the Google Earth Engine Platform

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1884
Author(s):  
Athos Agapiou
Keyword(s):  
Change Detection ◽  
Satellite Images ◽  
Archaeological Site ◽  
Google Earth ◽  
City Centre ◽  
Time Interval ◽  
High Resolution Satellite Images ◽  
Multi Temporal ◽  
Google Earth Engine ◽  
The City

Urban sprawl can negatively impact the archaeological record of an area. In order to study the urbanisation process and its patterns, satellite images were used in the past to identify land-use changes and detect individual buildings and constructions. However, this approach involves the acquisition of high-resolution satellite images, the cost of which is increases according to the size of the area under study, as well as the time interval of the analysis. In this paper, we implemented a quick, automatic and low-cost exploration of large areas, for addressing this purpose, aiming to provide at a medium resolution of an overview of the landscape changes. This study focuses on using radar Sentinel-1 images to monitor and detect multi-temporal changes during the period 2015–2020 in Limassol, Cyprus. In addition, the big data cloud platform, Google Earth Engine, was used to process the data. Three different change detection methods were implemented in this platform as follow: (a) vertical transmit, vertical receive (VV) and vertical transmit, horizontal receive (VH) polarisations pseudo-colour composites; (b) the Rapid and Easy Change Detection in Radar Time-Series by Variation Coefficient (REACTIV) Google Earth Engine algorithm; and (c) a multi-temporal Wishart-based change detection algorithm. The overall findings are presented for the wider area of the Limassol city, with special focus on the archaeological site of “Amathus” and the city centre of Limassol. For validation purposes, satellite images from the multi-temporal archive from the Google Earth platform were used. The methods mentioned above were able to capture the urbanization process of the city that has been initiated during this period due to recent large construction projects.

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