scholarly journals Multitemporal High-Resolution Satellite Images for the Study and Monitoring of an Ancient Mesopotamian City and its Surrounding Landscape: The Case of Ur

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Giacomo Di Giacomo ◽  
Giuseppe Scardozzi
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Gulf War ◽  
Archaeological Remains ◽  
Important Data ◽  
High Resolution Satellite Images ◽  
Ancient City ◽  
Before And After ◽  
Surrounding Landscape ◽  
The City

The paper concerns the use of multitemporal high-resolution satellite images for the study of the ancient city of Ur, in southern Mesopotamia, inaccessible to scholars from 2003. The acquired dataset is composed by two Gambit KH-7 (1966) and one Corona KH-4B (1968) declassified spy space photos and by few images taken by the recent satellites for civilian use QuickBird-2 (2002, 2004, 2007), Ikonos-2 (2008), and WorldView-1 (2008). The processing of all these images and the integration with ASTER and SRTM DEMs allowed the acquisition of new data about the topographical layout of the city and its monuments and ancient roads; the georeferencing of all archaeological remains and traces visible on the images allowed the upgrade of the archaeological map of Ur. The research also provided important data concerning the reconstruction of the surrounding landscape, where a lot of traces of old channels and riverbeds of the Euphrates were identified in areas much modified and altered during the last decades by urbanization and agricultural works. Moreover, the multitemporal images allowed the monitoring of the conservation of the archaeological area, particularly before and after second Gulf War.

Visual Damage Interpretation of Buildings in Bam City using QuickBird Images following the 2003 Bam, Iran, Earthquake

2005 ◽  
Vol 21 (1_suppl) ◽  
pp. 329-336 ◽  
Author(s):  
Fumio Yamazaki ◽  
Yoshihisa Yano ◽  
Masashi Matsuoka
Keyword(s):  
High Resolution ◽  
Rural Areas ◽  
Strong Earthquake ◽  
Satellite Images ◽  
Field Survey ◽  
Visual Damage ◽  
High Resolution Satellite Images ◽  
Macroseismic Scale ◽  
The City ◽  
Event Image

A strong earthquake struck the city of Bam in southeast Iran on 26 December 2003. The earthquake brought massive destruction to the city and its surrounding rural areas. QuickBird, a high-resolution satellite, captured a clear image of Bam on 03 January 2004, eight days after the event. The city was also observed by QuickBird on 30 September 2003, about three months before the event. In this paper, using the pre-event image, the location of individual buildings was registered on GIS and the city blocks surrounded by major roads were assigned. Then, the visual damage interpretation based on the European Macroseismic Scale (EMS-98) was carried out building by building, comparing the pre-event and post-event images. The result of the damage inspection was compared with field survey data, and the accuracy and usefulness of the high-resolution satellite images in damage detection was demonstrated.

An Approach for Building Rooftop Border Extraction from Very High-Resolution Satellite Images

2021 ◽  
pp. 1-11
Author(s):  
Yasser Mostafa ◽  
Mahmoud Nokrashy O. Ali ◽  
Faten Mostafa ◽  
Mohamed Yousef
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
High Resolution Satellite Images ◽  
Very High

scholarly journals Accelerate disaster risk mapping using an automated zonal change detection model for loss estimation and recovery: a flood case study

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Ali Amasha
Keyword(s):  
Change Detection ◽  
Satellite Images ◽  
Flash Flood ◽  
Disaster Risk ◽  
Loss Estimation ◽  
Risk Mapping ◽  
Detection Model ◽  
Applied Model ◽  
High Resolution Satellite Images ◽  
Before And After

Abstract Background The flash flood still constitutes one of the major natural meteorological disasters harmfully threatening local communities, that creates life losses and destroying infrastructures. The severity and magnitude of disasters always reflected from the size of impacts. Most of the conventional research models related to flooding vulnerability are focusing on hydro-meteorological and morphometric measurements. It, however, requires quick estimate of the flood losses and assess the severity using reliable information. An automated zonal change detection model applied, using two high-resolution satellite images dated 2009 and 2011 coupled with LU/LC GIS layer, on western El-Arish City, downstream of Wadi El-Arish basin. The model enabled to estimate the severity of a past flood incident in 2010. Results The model calculated the total changes based on the before and after satellite images based on pixel-by-pixel comparison. The estimated direct-damages nearly 32,951 m2 of the total mapped LU/LC classes; (e.g., 11,407 m2 as 3.17% of the cultivated lands; 6031 m2 as 7.22% of the built-up areas and 4040 m2 as 3.62% of the paved roads network). The estimated cost of losses, in 2010 economic prices for the selected three LU/LC classes, is nearly 25 million USD, for the cultivation fruits and olives trees, ~ 4 million USD for built-up areas and ~ 1 million USD for paved roads network. Conclusion The disasters’ damage and loss estimation process takes many detailed data, longtime, and costed as well. The applied model accelerates the disaster risk mapping that provides an informative support for loss estimation. Therefore, decision-makers and professionals need to apply this model for quick the disaster risks management and recovery.

scholarly journals How can remote sensing techniques help monitoring the vine and maximize the terroir potential?

2018 ◽  
Vol 50 ◽  
pp. 02007
Author(s):  
Cecile Tondriaux ◽  
Anne Costard ◽  
Corinne Bertin ◽  
Sylvie Duthoit ◽  
Jérôme Hourdel ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Satellite Images ◽  
Sampling Strategy ◽  
Wine Quality ◽  
Wine Production ◽  
Spectral Bands ◽  
High Resolution Satellite Images ◽  
Remote Sensing Techniques ◽  
Set Up

In each winegrowing region, the winegrower tries to value its terroir and the oenologists do their best to produce the best wine. Thanks to new remote sensing techniques, it is possible to implement a segmentation of the vineyard according to the qualitative potential of the vine stocks and make the most of each terroir to improve wine quality. High resolution satellite images are processed in several spectral bands and algorithms set-up specifically for the Oenoview service allow to estimate vine vigour and a heterogeneity index that, used together, directly reflect the vineyard oenological potential. This service is used in different terroirs in France (Burgundy, Languedoc, Bordeaux, Anjou) and in other countries (Chile, Spain, Hungary and China). From this experience, we will show how remote sensing can help managing vine and wine production in all covered terroirs. Depending on the winegrowing region and its specificities, its use and results present some differences and similarities that we will highlight. We will give an overview of the method used, the advantage of implementing field intra-or inter-selection and how to optimize the use of amendment and sampling strategy as well as how to anticipate the whole vineyard management.

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