Document Type : Research Paper

Authors

1 Professor in Geography, University of Tarbiat Modarres, Iran

2 Associated professor in Geography, University of Zanjan, Iran

3 Msc in remote sensing and GIS, University of Tarbiat Modarres, Iran

Abstract

Extended Abstract
Introduction
 Due to the large dimensions of earthquake damages and losses, more rapid procedures are required to identify damaged buildings. Field studies and old procedures are no longer efficient enough because of being time consuming, costly and requiring lots of workforce. This research seeks to identify the buildings damaged by earthquakes through analyzing the spectral response of urban houses to the reflective bands and effective factors, before and after the earthquake, for recognizing buildings damaged in the earthquake and compare the results of the reflective bands with each other, and then, determine the most efficient band among them. The earthquake stricken city of Bam was selected as the case study of this research. In order to identify the damaged urban houses, satellite imagery and remote sensing reflective bands were considered for detecting the changes, distinguishing the bands, and analyzing the spectral reflection profile.
 
Materials and Methods
 The high resolution Quick bird satellite, photographed the city of Bam just eight days after the earthquake on January 3, 2004. The satellite also had taken a clear image of Bam about three months before the earthquake on September 30, 2003, that, with regard to the objectives of the research and the capabilities of the images taken, these Quick Bird satellite images were selected to study and investigate in this field. The method of this research is to analyze the spectral reflection profile and the factors affecting it. Since the multi-spectral remote sensing is a set of reflective, emissive or backscattering energy from the study area in electromagnetic multi-spectral bands, the aim of this research is to describe why terrestrial phenomena show different responses to the electromagnetic spectrum, and to analyze their spectral curve as well. To this end, we established an analytical strategy to achieve a better interpretation of the blue (band 1: 450 - 520 nm), green (band 2: 520 - 600 nm), red (band 3: 630 - 690 nm), and infrared (band 4: 760 - 900 nm) reflective bands. And the earthquake stricken city of Bam was selected as the case study of this research in order to identify the damaged urban houses by analyzing the spectral reflection profile and factors affecting it.
 
Results and Discussion
Urban housing is composed of various materials (concrete, asphalt, metal, plastic and soil) by man in various ways for building houses. When earthquake strikes, these houses might be destroyed. Therefore, satellite multi-temporal images before and after the earthquake were selected as data for analyzing the electromagnetic spectrum curve of the study area. In this research, the vulnerability of urban houses is different from one place to another. Therefore, educational samples of the case study from different parts of the city such as those which have been completely destroyed, partially destroyed or have remained intact, were selected. Then, the spectral response analysis of the urban houses was carried out in 4 blue (band 1: 450 - 520 nm) green (band 2: 520 - 600 nm) red (band 3: 630 - 690 nm) and Infrared (band 4: 760 - 900 nm) reflective bands before and after the earthquake in order to identify effective factors and the bands independent of these factors comparing with other bands. The results show that, before the earthquake occurs, some factors such as shadows cause a sharp decrease in the reflection in all bands, the atmospheric scattering at short wavelengths with increasing spectral reflection, the angle of sunshine, type of material, the surface smoothness or roughness of the surface, the time of the day, the height and texture had a great impact on the 3 blue, green and red reflective bands. Infrared band with a rectangular shape in spectral curve is a band independent of the aforementioned factors (with the exception of the shadow and surface smoothness of the materials).
 
Conclusion
The results obtained from analyzing the spectral response of the urban houses in four reflective bands (Blue, Green, Red and Infrared) indicated that in general, the urban houses had high reflection and shadows had less reflection before the earthquake. After the earthquake, urban houses showed an irregular and significant reduction in spectral reflection, and the spectral reflection curve was irregular as well. However, the method of analyzing the spectral reflection profile is a point estimation method and does not result in a map, and this method is often used to check the accuracy of other methods.
 

Keywords

1- باسودب، باتا؛ 1394؛ روش‌های تحقیق در سنجش از دور ترجمه علوی پناه؛ ناشر دانشگاه تهران،چاپ اول، 141.
2- برگی، خسرو؛ 1394؛ «اصول مهندسی زلزله» انتشارات جهاد دانشگاهی(ماجد)، 559.
3- پل ام، میذر؛ 1380؛ «پردازش کامپیوتری تصاویر سنجش از دور» مترجم نجفی دیسفانی م، انتشارات سمت چاپ چهارم، 445.
4- رسولی، علی اکبر؛ 1378؛ «مبانی سنجش ازدور کاربردی با تأکید برپردازش تصاویر ماهواره‌ای» دانشگاه تبریز،777 .
5- رسولی، محمودزاده؛ علی‌اکبر، حسن؛ 1389؛ «مبانی سنجش از دور پایه» انتشارات علمیران،192.
6- شماعی، حیدرزاده، لطفی مقدم؛ علی، نجمه، بابک؛ 1392؛ «سنجش عوامل آسیب رسان ناشی از زلزله در منطقه یک تهران با استفاده از GIS»؛ نشریه علمی پژوهشی جغرافیا و برنامه‌ریزی (دانشکده جغرافیا)، سال 17،شماره 43، صفحات 93-122.
7- شیعه، حبیبی، ترابی؛ اسماعیل، کیومرث، کمال؛ 1389 «بررسی آسیب پذیری شبکه ارتباطی شهرها در مقابل زلزله با استفاده از روش IHWP  و GIS» باغ نظر؛ سال هفتم شماره سیزدهم، صفحات 35-48.
8- عزیزی، همافر؛ میلاد، محمد مهدی؛1391؛ «آسیب شناسی لرزه ای معابر شهری (مطالعه موردی محله کارمندان کرج» نشریه هنرهای زیبا- معماری و شهرسازی شماره 3 دوره 17 صفحات 5-15.
9- علوی پناه، سید کاظم؛ 1395؛ «کاربرد سنجش از دور در علوم زمین (علم خاک)»؛ انتشارات دانشگاه تهران، چاپ هشتم، 496.
10- کوران، پل؛ 1373، «اصول سنجش از دور»؛  ترجمه  رضا حائر؛ انتشارات مرکز سنجش از دور ایران،278.
11- لیلسند و کیفر، 1391؛ «اصول و مبانی سنجش از دور و تعبیر و تفسیر تصاویر هوایی و ماهواره‌ای»؛ ترجمه مالمیریان؛ سازمان جغرافیایی نیروهای مسلح- 350.
12- مباشری، محمدرضا؛ 1393؛ «مبانی فیزیک در سنجش از دور و فناوری ماهواره‌ای»؛ انتشارات دانشگاه صنعتی خواجه نصیر الدین طوسی، چاپ اول، 592.
13- مجد، زبیری؛ علیرضا، محمود؛ 1392؛ «آشنایی با فن سنجش از دور و کاربرد در منابع طبیعی»؛ انتشارات دانشگاه تهران، چاپ دهم، 318.
14- ملاحت، اورنگ؛ 1386؛ «سنجش کیفیت محیط در بازسازی  پس از سانحه (مطالعه موردی فضای عمومی شهر بم)»؛ پایان‌نامه کارشناسی ارشد، مجتبی رفیعیان، دانشگاه تربیت مدرس.
15- Bhatta B, 2011, Research Methods in Remote Sensing, Oxford university press, 128.
16- Bhatta B, 2011, Remote Sensing and GIS, 2nd edn, Oxford university press, 321.
17- Brunner. D, Lemoine. G, Bruzzone. L, 2010, Earthquake Damage assessment of Buildings Using VHR Optical and SAR Imagery, IEEE Transactions on Geoscience and Remote sensing, Vol. 48.2403- 2420.
18- Chini. M, Cinti. F. R, Stramondo. S, 2011, Co-seismic surface effects from very high resolution panchromatic image: the case of the 2005 kashmir (pakistan) earthquake, Nat Hazards, Vol 11, 931-943.
19- Chiroiu. L,2005, Damage assessment of the 2003 Bam (Iran) earthquake using Ikonos Imagery, earthquake spectra, Vol 21, Page 219-224.
20- Derya. O, 2004, Post_earthquake Damage assessment using satellite and aerial video imagery, thesis submitted  for international institute of geo information seience.
21- Jensen. J.R, 2006, Remote sensing of the environment an earth resource perspective, 2edn. Prentice Hall, Upper Saddle River, 445.
22- Kosso P, 2011, A Summary of scientific metho, Springer Heidelberg Kuhn TS, 3rd, university of Chicago press, Chicago and London, 212.
23- Kohiyama. M, Yamazaki. F, 2005, Damge detection for 2003 Bam (Iran) earthquake using Terra-Aster satellite Imagery, earthquake spectra, Vol 21, 267-274.
24- Lillesend. T. M, and Kiefer. P. W, 1994, Remote sensing and image interpretation, john Wiley &Sons, Inc, USA
25- Lunetta. S. R, and Elvidge. D, 1999, Remote sensing change detection (Environmental Monitoring Methods and Applications). Taylor & Francis, New York, 334.
26- Martinelli. A, Cifani. G, Cialone. G, Corazza. L, Petracca. A, Petrucci. G, 2008, Building vulnerability assessment and damage scenarios in Celano (Italy) using a quick survey data-based methodology, Soil Dynamics and Earthquake Engineering 28, 875- 889.
27- Matsuoka. M, Yamazaki. F,2005, Building damage mapping of  the 2003 Bam (Iran) earthquake using Envisat/A SAR intensity imagery, earthquake spectra, Vol 21, s285-s294.
28- Saito. K, Spence. R, Foley. C,2005, Visual damage assessment using high-resolution satellite images following the 2003 Bam (Iran) earthquake, earthquake spectra, Vol 21, pp309-318.
29- UNDP, 2004, reducing disaster Risk, A Challenge for Development Zadeh. LA,(1965), Fuzzy sets, Information and Control 8, 338- 353.
30- Vu. T, Matsuoka. M, Yamazaki. F, 2005, Detection and Animation of damage using very high-resolution satellite data following the 2003 Bam (Iran) earthquake,  earthquake spectra, Vol 21, s319-s327.
31- Yamazaki. F, Yano. Y, Matsuoka. M, 2005, Visual damage interpretation of buildings in Bam city using Quick brid  images following the 2003 Bam (Iran) earthquake, earthquake spectra, Vol 21, 329-336.
32- Yano. Y, Yamazaki. F, Matsuoka. M, Vu. T. T,2004, Building damage detection of the 2003 Bam (Iran) earthquake using Quick Bird image, seismological society of America, 84, 1831-1841, proceeding of the 25th Asian Conference on Remote Sensing, CD-ROM.