پیشرفتها، چالشها و دیدگاهها درزَمینۀ تصحیح تصاویر ماهوارهای نور شب رایگان | ||
| نشریه سنجش از دور و GIS ایران | ||
| مقاله 2، دوره 16، شماره 1 - شماره پیاپی 61، 1403، صفحه 15-48 اصل مقاله (3.07 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.48308/gisj.2022.102886 | ||
| نویسندگان | ||
| فاطمه احمدی1؛ عباس کیانی* 2؛ یاسر ابراهیمیان قاجاری2 | ||
| 1دانشجوی کارشناسی ارشد مهندسی فتوگرامتری، دانشگاه صنعتی نوشیروانی بابل، بابل، ایران | ||
| 2استادیار گروه مهندسی نقشهبرداری، دانشکدة عمران، دانشگاه صنعتی نوشیروانی بابل، بابل، ایران | ||
| چکیده | ||
| سابقه و هدف: سنجش از دور منبع دادهای قدرتمند برای نقشهبرداری از مناطق شهری و نظارت بر پویایی شهرنشینی است. از بین دادههای سنجشازدوری، تصاویری که در شب اخذ میشوند راهی مؤثر برای نظارت بر فعالیتهای انسانی، در مقیاس جهانی، فراهم کرده است؛ زیرا این تصاویر با توجه به ویژگیها و قابلیتهایشان میتوانند مناطق شهری و سایر فعالیتهای انسانی را که ویژگی اصلیشان استفاده از نور در شب است، با اندازهگیری صحیح مکانی، از پسزمینۀ بدون نور جدا کنند. این تصاویر با نظارت مستمر و مداوم از منظرة شبانۀ جهانی، منبع و نتایج ارزشمندی از فعالیتهای انسانی را، از گذشته تا امروز، فراهم میکند و تجزیهوتحلیل سری زمانی این دادهها برای کشف، تخمین و نظارت بر پویایی اجتماعی و اقتصادی در کشورها، بهویژه مناطق فرعی که آمار رسمی مورد اعتمادی دربارة آنها وجود ندارد، بسیار ارزشمند است. با توجه به پیشرفت سنجندههای ماهوارهای نور شب در سالهای اخیر و تحقیقات جدید انجامشده درزَمینة دادههای نور شب، هدف از این تحقیق بررسی پیشرفتهای سنجندة شبانه، معرفی انواع دادهها و محصولات دردسترس، بررسی و بیان مزایا و معایب هریک و همچنین مروری بر روشها و راهحلهای مطرحشده در تحقیقات پیشین است تا مشکلات و محدودیتهای این تصاویر حل شود. مواد و روشها: هدف اصلی از این تحقیق معرفی و بررسی کلی دادههای نور شب، مزایا و چالشهای هریک و روشهای بیانشده بهمنظور تصحیح مشکلات و چالشهاست. مطالعات درزَمینة تصاویر نور شب DMSP اغلب بر دو بعد مکانی و زمانی تمرکز دارد. در بعد مکانی، نواقص ذاتی این مجموعه داده، یعنی مقادیر اشباعشدة مقادیر رقومی در مناطق مرکزی شهری و تأثیرات شکوفایی در مناطق حومة شهری و روستایی درخور توجه است. در بعد زمانی، بهدلیل فقدان کالیبراسیون در پردازنده، به فرایندهای اضافی روی محصولات سالیانة دادههای پایدار نور شب DMSP برای بررسی پویاییهای شهری نیاز است؛ روشهای کنونی تصحیحات مشکلات مکانی در دو دستة طیفی و غیرطیفی قرار میگیرد. روشهای مطرحشده برای تصحیح مشکلات زمانی این سنجنده نیز، در دو دستة کالیبراسیون سالیانة دادههای نور شب و تنظیم الگوی زمانی، بررسی شده است. تصاویر ماهیانة NPP-VIIRS محصولی است که علاوهبر مقادیر نورهای ثابت، مانند چراغهای شهرها و مسیرهای حملونقل، مقادیری نویزی مانند شعلههای گاز و سوختن زیستتوده و نویز پسزمینه را نیز شامل میشود؛ به همین دلیل، پیشاز استفاده لازم است پردازش شود. همچنین ازآنجاکه دقت موقعیتیابی دادههای لوجیا کمتر از وضوح مکانی آن است، جابهجایی تصویر در برخی مکانها ممکن است به 650 متر برسد؛ ازاینرو تصحیح هندسی در این تصویر انجام میشود. انواع این روشها در این مقاله بررسی شده است. بحث و بررسی: طی مقایسهای کلی، میتوان نتیجه گرفت که در بررسی عملکرد دادههای نور شب گوناگون، دادههای نور پایدار شبانة DMSP، بهرغم مشکلات و محدودیتهای موجود، دارای سری زمانی طولانیتری درقیاس با دادههای نور شب دیگر است زیرا دورة زمانی 1992 تا 2013 را دربرمیگیرد و همچنان، در بسیاری تحقیقات درزَمینة بررسی پویایی شهری و برآورد روند کلی رشد شهر، کاربرد دارد. درمقایسه، NPP-VIIRS از مزایایی برخوردار است و به نور کمتر نیز حساسیت نشان میدهد اما زمان عبور این ماهواره ساعت 1:30 بامداد است؛ در این ساعت شب، بسیاری از چراغها خاموش میشوند و به همین علت ممکن است، درمواردی که فقط از دادة نور شب برای بررسی مناطق شهری استفاده میشود، مناسب نباشد. همچنین طی بررسیهای انجامشده، این تصویر در تحقیقات درزَمینة فعالیتهای اقتصادی کاربرد بیشتری داشته است و حساسیتنداشتن آن به نور آبی ازLED ها در توانایی سنجنده، در تعیین کمّیت نورهای مصنوعی ساطعشده از زمین، تأثیر میگذارد. نتیجهگیری: این بررسی با هدف معرفی انواع دادههای نور شب سنجشازدوری و بررسی آنها انجام شده است و بهطور خلاصه میتوان گفت، درحال حاضر، تحقیقات درزَمینة تصحیح مشکلات مکانی اشباع و شکوفایی به دو دستة طیفی و غیرطیفی تقسیم میشوند. دستههای غیرطیفی اغلب فقط با استفاده از دادة نور شب و در برخی موارد، با استفاده از دادههای غیرسنجشازدوری ترکیب میشوند. بررسی روشهای طیفی نشان میدهد که اغلب این روشها از شاخصهای طیفی مربوط به پوشش گیاهی و دمای سطح زمین استفاده میکنند. درحال حاضر، تصحیح تصاویر DMSP از بعد زمانی با کالیبراسیون بین دادهها، بهطور خاص، با استفاده از روش مناطق مرجع ثابت یا پیکسلهای مرجع انجامشدنی است. از معتبرترین روشهای مطرحشده در این زمینه، روش منطقة مرجع است. پساز پایان مأموریت سنجندة DMSP-OLS، سنجندة VIIRS معرفی شده است. برخلاف دادة سالیانة این ماهواره، دادة ماهیانة آن بهعلت وجود نویزهای پسزمینه، نورهای سرگردان و مواردی ازایندست، نیاز به تصحیح دارد. طبق بررسیهای انجامشده براساس مطالعات موجود در روند تحقیقات، میتوان گفت بیشتر مطالعات و روشها سعی در حذف نویزها با استفاده از چارچوبی مشخص، اما با فرضهای متفاوت، دارند. درنَهایت، با توجه به چالشها و محدودیتهای فعلی ماهوارههای نور شب، چند پیشنهاد اصلی برای پیشرفت و توسعه در این زمینه مطرح میشود؛ ادغام دادههای DMSP-OLS با دادههای NPP-VIIRS یا با وضوح بالاتر دادههای لوجیا میتواند بیشتر مورد مطالعه قرار گیرد تا یک سری زمانی طولانیتر برای تحقیقات آینده، بهمنظور بررسی پویایی شهری و موارد مشابه، ایجاد شود. | ||
| کلیدواژهها | ||
| تصاویر ماهوارهای نور شب؛ مزایا و معایب تصاویر نور شب؛ روشهای تصحیح و پیشپردازش | ||
| عنوان مقاله [English] | ||
| The Advances, Challenges and Perspectives in the Correction Field of Free Night Light Satellite Image | ||
| نویسندگان [English] | ||
| Fatemeh Ahmadi1؛ Abbas Kiani2؛ yasser Ebrahimian Ghajari2 | ||
| 1Master Student of Photogrammetry Engineering, Babol Noshirvani University of Technology, Babol, Iran | ||
| 2Assistant Prof. of Civil Engineering Dep., Babol Noshirvani University of Technology, Babol, Iran | ||
| چکیده [English] | ||
| Introduction: Remote sensing provides a powerful data source for the mapping of urban areas and the monitoring of urban dynamics on a range of scales. Among the variues types of remote sensing data, images captured at night offer an effective means ofmonitoring human activities on a global scale. The distinctive features and capabilities of these images permit the separation of urban areas and other human activities, the main feature of which is the use of light at night by accurately measuring the location, from the background without light. Via providing uninterrupted and continuous monitoring from the night world perspective, these images provide a valuable source of information about human activities over time from the past to the present. The time series analysis of this data is highly valuable for discovering, estimating and monitoring social and economic dynamics in countries, especially sub-regions where there are no official statistics. With recent developments in night-time data satellite sensors and new research conducted in this field, this study aims to review the advances in night-time sensors, introduce the existing data and products, review and express the advantages and disadvantages of each one, and review the methods and solutions presented in previous research for solving the existing problems and limitations in order to improve these images. Materials and methods: The main objective of this research is to introduce and review the general charactristics of night-time light data, discussing their advantages, challenges, and methods for addressing these challenges. The majority of studies on DMSP night light images focus on two spatial and temporal dimensions. In the spatial dimension, inherent deficiencies of this dataset are observed, such as saturated numerical values in central urban areas and flourishing effects in suburban and rural areas. In the temporal dimension, the lack of calibration in the processor, necessitates the implementation of additional processes on annual products of stable DMSP night light data in order to examine urban dynamics. The existing methods for correcting spatial problems are divided into tow categories: spectral and non-spectral. Similarly, methods for addressing temporal issues are divided into two categories: annual calibration of night light data and adjustment of temporal patterns. NPP-VIIRS monthly images encompass various features including fixed light values such as city lights and transportation routes, as well as noise values such as gas flames, biomass burning, and background noise. Therefore, preprocessing is necessary before utilizing this data. Furthermore, the positioning accuracy of Loujia_01 data is lower than its spatial resolution, resulting in image displacement of up to 650 meters in some areas. Geometric correction is applied to rectify this issue, and various correction methods have been investigated. Discussion: A general comparison of the data sets reveals that, despite the existing problems and limitations, the DMSP stable night light data outperforms other night light datasets due to its longer time series, which spans from 1992 to 2013. This extended temporal coverage makes it a valuable resource for research on urban dynamics and estimating the overall growth trend of cities. On the other hand, NPP-VIIRS offers advantages and is sensitive to faint light sources. However, its passage time at 1:30 in the morning, when many lights are turned off, limits its utility for urban studies. Consequently, it may not be the optimal choice for exclusively investigating urban areas exclusively. Nevertheless, the NPP-VIIRS data is more useful in research related to economic activities. Furthermore, the sensor's lack of sensitivity to blue light emitted by LEDs impacts its ability to accurately quantify artificial light emissions from the ground. Conclusion: The objective of this study was to introduce types of remote sensing night light data and their analysis. In short, current research in the field of correcting spatial saturation and blooming problems is divided into two categories: spectral and non-spectral. Non-spectral methods typically rely solely on night light data, although they may also incorporate non-remote sensing data. Spectral methods often employ spectral indices that are related to vegetation and ground surface temperature. Currently, correcting DMSP images from the temporal dimension can be achieved through inter-data calibration, specifically via the fixed reference regions or reference pixels method. One of the most reliable methods in this field is the reference area method. Following the conclusion of the DMSP-OLS mission, the VIIRS was introduced. In contrast to the annual data of this satellite, the monthly data requires correction due to the presence of background noise, and stray lights. A reviews of existing studies indicates that the majority of methods aim to remove noise using specific frameworks although with differing assumptions. Finally, considering the current challenges and limitations of night light satellites, several recommendations for future progress and development in this field are put forth. Further investigation could be conducted into the integration of DMSP-OLS data with NPP-VIIRS data or higher resolution Loujia-01 data, with the objective of developing a longer time series for future research on urban dynamics. | ||
| کلیدواژهها [English] | ||
| Night light satellite images, Advantages and disadvantages of night light images, Correction and pre-processing methods | ||
| مراجع | ||
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