Remote Sensing of Environment, 107, 606-616. correspondence between two raster maps. ASSESSMENT OF RADIOMETRIC RESOLUTION IMPACT ON REMOTE SENSING DATA CLASSIFICATION ACCURACY 1 Laboratory of Photogrammetry and Remote Sensing, Department of Cadastre, Photogrammetry and Cartography, Faculty of Rural and Surveying Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece Harshness in image classification accuracy assessment. Accuracy assessments of airborne hyperspectral data for mapping opportunistic plant species in freshwater coastal wetlands. Handbook. He was elected a Fellow in 2007 and an Honorary Member in 2016. To accuracy assesment you have to set some grund truth points. I am still not totally confident of how to fully analyse and compare accuracy assessments, so I will continue to read further into this. Log In. A New Accuracy Assessment Method for One-Class Remote Sensing Classification @article{Li2014ANA, title={A New Accuracy Assessment Method for One-Class Remote Sensing Classification}, author={W. Li and Qinghua Guo}, journal={IEEE Transactions on Geoscience and Remote Sensing}, year={2014}, volume={52}, pages={4621-4632} } We proposed an accuracy assessment model based on spatial sampling to reflect region sensitivity of a remote sensing image. Previously, accuracy assessment was not a priority in image classification studies. However, because of the accelerated chances for error presented by digital imagery, accuracy assessment has become a very vital process [5]. Accuracy assessment or validation is a significant step inthe processing of remote sensing data. applications of remote sensing. This study focuses on the role of radiometric resolution on classification accuracy of remote sensing data through different classification experiments over three different sites. The classification accuracy of a remote sensing image should be assessed before the classification result is used for scientific investigation and policy decision. If so, share your PPT presentation slides online with PowerShow.com. Ask Question Asked 5 years, 3 months ago. To date, most of the research on ecological security is based on the pressure-state-response (PSR) model, while there were a few studies based on the landscape ecology model approach. Before the accuracy assessment. (1991) A review of assessing the accuracy of classifications of remotely sensed data, Remote Sensing of Environment, 37, pp. The production of thematic maps, such as those depicting land cover, using an image classification is one of the most common applications of remote sensing. Although the development of remote sensing techniques focuses greatly on construction of new sensors with higher spatial and spectral resolution, it is advisable to also use data of older sensors (especially, the LANDSAT-mission) when the ... References Cited. (1996). 12, pp. Vol. The accuracy assessment gained was then being implemented using the visual interpretation and overall accuracy achieved was 70.740% with kappa coefficient of 0.5. r remote-sensing accuracy land-classification. The U.S. Geological Survey has reported results of accuracy assessments of the 1:250,000 and 1:1,000,000 land use maps of Level 1 classifications (see page 4-1 ), based on aerial photos, that meets the 85% accuracy criterion at the 95% confidence level. The experiments were carried out using fine and low scale radiometric resolution images classified through a bagging classification … Yale University (2003) Accuracy Assessment. In remote sensing, the term accuracy typically expresses the degree of correctness of a map. Remote Sensing for Forest Cover Change Detection 10 NIR, and Red bands are represented as red, green, blue (RGB), respectively, highlights vegetated areas as green and bare soil or impervious surfaces show up as pink. Previously, accuracy assessment was not a priority in image classification studies. ing Landsat classification accuracy using discrete mul tivariate analysis statistical techniques. International Journal of Remote Sensing, 1995. basically two types of data collected in support of remote sensing accuracy assessments: other remote sensing data and ground-based data. Advanced Remote Sensing: Classification Accuracy Assessment These lessons describe the steps involved in accuracy assessment and methods for providing estimates of accuracy. 1261-1266. This lab follows on from others in this series (Introduction to Remote Sensing Labs 1-6). Lab 5: Classification Accuracy Assessment. Warner, 2013. The top table describes accuracy in pixel counts and the bottom table describes accuracy in area proportions.... 41 Table 10: The accuracy assessment of the 2000 Landsat VCF FNF map generated for the DRC study site. The present paper highlights the classification, change detection and future prediction of Sundarban reserve forest using multi-spectral satellite data over last 43 years (1975–2018). Advanced Advanced Webinar: Land Cover Classification with Satellite Imagery Advanced Webinar: Accuracy Assessment of a Land Cover Classification Advanced Webinar: Change Detection for Land Cover Mapping 37: p. 35-46. Accessibility Help. Assessing uncertainty in spatial landscape metrics derived from remote sensing data. Photogrammelric Engineering and Remote Sensing. Found inside – Page 85Photogrammetric Engineering and Remote Sensing 49(1):69–74. del Amo, A., J. Montero, ... “Status of Land Cover Classification Accuracy Assessment.” Remote ... Performing Accuracy Assessment 6.2.1 Lab 1. Lambin EF, Rounsevell MDA, Geist HJ. A fuzzy classification approach is usually useful in mixed-class areas and was investigated for the classification of suburban land cover from remote sensing imagery (Zhang and Foody 1998), the study of medium-to-long term (10–50 years) vegetation changes (Okeke and Karnieli 2006) and the biotic-based grassland classification (Sha et al. Press alt + / to open this menu. Status of land cover classification accuracy assessment.Remote Sensing; of Environment. Satellite Remote Sensing for Agricultural Applications Understanding Phenology with Remote Sensing Remote Sensing of Coastal Ecosystems 4. International Journal of Remote Sensing: Vol. 35-46. Found insideA thorough update to what is already one of the most comprehenisve and rigorous texts in the field, the new edition incorporates the many advancements made in remote sensing over the past decade. We proposed an accuracy assessment model based on spatial sampling to reflect region sensitivity of a remote sensing image. Table 9: The accuracy assessment of the 2000-2010 Conventional Supervised Classification change map generated for the DRC study site. Classification Accuracy Assessment: Accuracy assessment is performed by comparing the map created by remote sensing analysis to a reference map based on a diff… Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. Ground data Remote sensing RS accuracy Prevalence 90 80 61 26 95 90 76 23 Systematically underestimate accuracy of remote sensing change detection and overestimate amount of change. At a minimum, a Kappa using a remote-sensing derived landcover map in Coefficient of Agreement should be attached to any management decisions, however, an accuracy resultant classification of satellite imagery. [4] Foody, G. (1992): On the Compensation for Chance Agreement in Image Classification Accuracy Assessment. Accuracy Assessment: Interpreting •Errors in classified map –Remotely-sensed data cannot capture classes •Classes are land use, not land cover •Classes not spectrally separable •Atmospheric effects mask subtle differences •Spatial scale of remote sensing instrument does not match classification … Ground truth can be collected in the field; however, this is time consuming and expensive. This classification algorithm had been shown to be effective for face recognition in photos, handwriting and object recognition be fore it was adopted for use in remote sensing Throughhis theoretical and appliedwork,ArthurGetishasbeena majorcontributing?gureinthisdevelopment. In this volume, we take both a retrospective and a prospective view of the ?eld. CLASSIFICATION ACCURACY ASSESSMENT. Now available in paperback, this book provides a comprehensive account of survey sampling theory and methodology suitable for students and researchers across a variety of disciplines. Remote sensing is an integral part of geography, GIS and cartography, used by academics in the field and professionals in all sorts of occupations. Remote Sensing & GIS Applications. Since, ground based data is assumed to be 100% correct in accuracy assessments, due care was taken during the data . Components of agreement between categorical maps at multiple resolutions. Right click on the S_Thailand_2008_2010_305_90_composite image again, then click on … Congalton, R, and R. Mead, 1983. The result of an accuracy assessment provides us with an overall accuracy of the map based on an average of the accuracies for each class in the map. 2. Remote Sensing of Environment Governor's Council on Geographic Information, Spatial Data Accuracy 1991. We proposed an accuracy assessment model based on spatial sampling to reflect region sensitivity of a remote sensing image. Remote sensing accuracy assessment - McNemar`s Test. This study ... use of remote sensing classification approach the vegetation classification can be mapped accurately. It is a way to quantify your classification. – Without an accuracy assessment the output or results is of little value 3. However, because of the accelerated chances for error presented by digital imagery, accuracy assessment has become a very vital process. Found insideWritten in easy-to-follow language with minimal technical jargon, the book explores cutting-edge techniques and trends in image analysis, as well as the relationship between image processing and other recently emerged special technologies. Since, ground based data is assumed to be 100% correct in accuracy assessments, due care was taken during the data . Land degradation and desertification are amongst the most severe threats to human welfare and the environment, as they affect the livelihoods of some 2 billion people in the worlds drylands, and they are directly connected to pressing ... The experiments were carried out using fine and low scale radiometric resolution images classified through a bagging classification tree. Language: English. The overall Kappa statistic for this classification is .4582 which means that there was moderate agreement between the accuracy. Response Design6.3 Summary 6.4 Additional exercises References The . 2003b) was previously utilized in a remote sensing context by Gualtieri and Cromp in 1998 and Pal and Mather, 2005. 49, No. Assessing uncertainty in spatial landscape metrics derived from remote sensing data. Remote sensing and GIS techniques can be used for generating development plans for the watershed area in consonance with the production potential and limitation of terrain resources, and can also be used for assessing the impact of these measures before actual implementation in the field. Viewed 1k times ... remote-sensing classification accuracy confusion-matrix. The remote sensing data are classified using back-propagation neural network algorithm which are healthy vegetation, unhealthy vegetation, wet land, and water bodies. Accuracy assessment is an important part of any classification project. Chapter 6. The result of an accuracy assessment provides us with an overall accuracy of the map based on an average of the accuracies for each class in the map. Share. unsupervised Classification Using NOAA data. Validation, also called accuracy assessment, is a critical step in the use and distribution of the results of analyses of remotely sensed data. -- An independent reliability assessment for the Australian agricultural land-cover change project 1990/91-1995 / Michele Barson et al. Share. Jensen (1996) is the reference applied to this example fo r testing the relationship between two models . Land Cover Classification Accuracy Assessment 6.1 Background 6.1.1 Sampling Design 6.1.2 Response Design 6.1.3 Analysis 6.2. As well as using the Reef Cover classification document as a basis for creation of new maps from remote sensing, the classification is also ... in remote sensing accuracy assessment … International Journal of Remote Sensing: Vol. At a minimum, a Kappa using a remote-sensing derived landcover map in Coefficient of Agreement should be attached to any management decisions, however, an accuracy resultant classification of satellite imagery. It compares the classified image to another data source that is considered to be accurate or ground truth data. Liu, C., Frazier, P. and Kumar, L. (2007) Comparative Assessment of the Measures of Thematic Classification Accuracy. Sections of this page. Active 3 years, 9 months ago. Thematic accuracy concerns the correctness of a class (or a label) assignment. In remote sensing applications, thematic accuracy refers to the accurate measurement of the mapped land cover category at a specific location in comparison to the actual … Accuracy assessment or validation is a … The various ecological processes of human beings are not only restricted by the landscape pattern on the regional scale but also affect the local and regional landscape together with global climate change. This compilation contains 20 chapters that represent important symposium outcomes. However, here I also run into an issue. classification. Found inside – Page 427On the Compensation for Chance Agreement in Image Classification Accuracy Assessment. Photogrammetric Engineering and Remote Sensing, Vol. 58, pp. Accuracy assessment is an essential and crucial part of studying image classification and thus LULCC detection in order to understand and estimate the changes accurately. (1996). Foody GM. A number of indices have been proposed to measure the accuracy of classification maps, among which In the fourth approach, there are two variants of generating a random sample. Goals: Assess how well a classification worked Understand how to interpret the usefulness of someone else’s classification from remote-sensing satellites (Keuchel et al. Accuracy assessment plays an important role in remote sensing image classification. A quantitative method to test for consistency and correctness in photointer pretation. See more of Geoscience, Remote Sensing and GIS Network on Facebook. In this new window Click on File –> Open and choose ‘watershed_unsup4.img’ Click on Edit –> Create/Add Random Points r remote-sensing accuracy land-classification. Ideally, assessment must be performed. Classified maps are the main product of remote sensing image classification. Accuracy assessment of these classified maps is one of the foremost and important tasks of RS image classification technique. Without accuracy assessment the quality of map or output produced would be of lesser value to the end user. Found inside – Page 59A review of assessing the accuracy of classifications of remotely sensed data . ... Remote sensing thematic accuracy assessment : a compendium . Found inside – Page 106Photogrammetric Engineering and Remote Sensing, 70, 627–633. Foody, G.M. (2008) Harshness in image classification accuracy assessment. Sample size determination for image classification accuracy assessment and comparison Author: after classification using a gps you must collect real land uses and input them in Envi and it will calculate the kappa for you..For more information refer to Digital image prosecing ,Jensen 2000,I think you can find some peresentation about this subject too 11, pp. Found inside – Page 418Accuracy assessment of remotely sensed classifications with multi - phase sampling and the multivariate composite estimator . Improve this question. In remote sensing, the term accuracy typically expresses the degree of correctness of a map. Create New Account. In: Assessment ME (eds) . this points are the points that you get from in situ data collection. The aim of this study is to identify and classify vegetation using the high-resolution Pleiades satellite image in urban park areas using pixel-based image analysis. ABSTRACT: This research investigates land use and land cover change in Alachua County, FL from 1993 to 2003. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. Sample Design 6.2.2 Lab 2. Remote sensing is used for a wide array of purposes in conservation science ... Land use classification accuracy assessment. For some reason, the image classified using unsupervised classification had a higher accuracy than the image did which was classified using supervised classification. In practice, however, probability samples may [...] Read more. ... "Accuracy Assessment in Remote Sensing:" is the property of its rightful owner. Share. 17, No. Accuracy assessment in Erdas imagine. From recent developments in digital image processing to the next generation of satellite systems, this book provides a comprehensive introduction to the field of remote sensing and image interpretation. ENVIRON. ACCURACY ASSESSMENT – Assess accuracy of a remote sensing output is one of the most important steps in any classification exercise!! Using a wide range of spatial, spectral, temporal, and radiometric scales Remote Sensing is a large and diverse field for which this Handbook will be the key research reference. Tau Goetficients for Accuracy Assessment of Classification of Remote Sensing Data Zhenkui Ma and Roland L. Redmond Abstract The Kappa coefficient is generally used to assess the accu-racy of image classifications. Maxwell, and T.A. Before the accuracy assessment. First, sample testing points were generated. 37:35-46 (1991) A Review of Assessing the Accuracy of Classifications of Remotely Sensed Data Russell G. Congalton Department of Forestry and Resource Management, University of California, Berkeley This paper reviews the necessary considerations and available techniques for assessing the accuracy of remotely sensed data. Found inside – Page iiThis book seeks to redress that situation. … Foody, G.M. Tutorial 20a in a series of 20 (20 is broken into two videos: a and b) covering remotely sensed data in ArcMap 10.x versions. 58. Remote sensing literatu re is a good place to look, especially since this is a common method of accuracy assessment on remote-sensing-derived classific ations with unbiased ground reference information. Previously, accuracy assessment was not a priority in image classification studies. REMOTE SENS. Found inside – Page 601An error matrix approach to fuzzy accuracy assessment: The NIMA Geocover project. A peer-reviewed chapter. In: Remote Sensing and GIS Accuracy Assessment, ... Considerable research has been directed at the various components of the mapping process, including the assessment of accuracy. Reference data was taken using the same schemes used in the . Franklin, S. E. and Wulder M. A. Vol. Found inside116 pp. Liu, C., P. Frazier, and L. Kumar. 2007. Comparative assessment of the measures of thematic classification accuracy. Remote Sensing of Environment. The flow chart in figure 1 represents the classification and accuracy assessment … Accuracy assessment of maps derived from remotely sensed data has continued to grow since the first edition of this groundbreaking book. 185-201. Ground reference points were used to assess land use classification accuracy at both resolutions, using the procedure of Landis and Koch . Remote sensing is increasingly being used to generate such data for mapping and monitoring changes in urban vegetation. Handbook. 6, pp. Email or Phone: Password: Forgot account? 17, No. We introduce the Tau coeffi-cient, which meesures the improvement of a classification (2008). This paper describes a study that was carried out to perform supervised and unsupervised techniques on remote sensing data for land use/cover classification and to evaluate the accuracy result of both classification techniques. Ecosystem; s and human well-being, Washington, DC. efforts. A New Accuracy Assessment Method for One-Class Remote Sensing Classification Abstract: In one-class remote sensing classification, users are only interested in classifying one specific land type (positive class), without considering other classes (negative class). Improve this question. The effects of classification accuracy on landscape indices. It's FREE! Components of agreement between categorical maps at multiple resolutions. Optimistic bias in classification accuracy assessment. Optimistic bias in classification accuracy assessment. CLASSIFICATION The image enhancement is initial process done by using decorrelation stretch to enhance the image for more effective visualization, before the classification. Found insideThis work, bringing together a range of specialists from fields such as linguistics, computer science, land surveying, cartography and soil science, examines current research into the challenges of dealing with geographical phenomena that ... This book is a completely updated, greatly expanded version of the previously successful volume by the author. 29, No. This study focuses on the role of radiometric resolution on classification accuracy of remote sensing data through different classification experiments over three different sites. Found inside – Page 413... purposes of classification accuracy assessment in remote sensing fields, OK indices have become a standard component of most every accuracy assessment ... several measure of accuracy assessment should be Found insideThis is one of the first books to take an ecological perspective on uncertainty in spatial data. Accuracy assessment or validation is a significant step inthe processing of remote sensing … Found inside – Page 51accuracy (PU) or average producer's accuracy (PA). ... R.G. A Review of Assessing the Accuracy of Classifications of Remotely Sensed Dala. 4,629 2 2 gold badges 16 16 silver badges 27 27 bronze badges. Considerable research has been directed at the various components of the mapping process, including the assessment of accuracy. Ground data Remote sensing RS accuracy Prevalence 90 80 61 26 95 90 76 23 Systematically underestimate accuracy of remote sensing change detection and overestimate amount of change. Accuracy assessment If the classification data are to be useful in detection of change analysis, it is essential to perform accuracy assessment for individual classification [19]. Found insideThis is a book about how ecologists can integrate remote sensing and GIS in their daily work. It will allow ecologists to get started with the application of remote sensing and to understand its potential and limitations. The paper presents a method of predicting classification accuracy of remote sensing data by means of training set analysis. 1. (2002) ‘Status of land cover classification accuracy assessment’, Remote Sensing of Environment, 80, pp. For some reason, the image classified using unsupervised classification had a higher accuracy than the image did which was classified using supervised classification. Unit 9 – (part 1) Accuracy assessment and remote sensing • Accuracy assessment is an important topic for all aspects of remote sensing work but probably none more so than image classification and change detection applications (our next topic). Found insideThis third edition of Assessing the Accuracy of Remotely Sensed Data: Principles and Practices is thoroughly updated and includes five new chapters. Remote sensing accuracy assessment - McNemar`s Test. 16 (3): p. 581-587. Best practices in accuracy assessment have been widely researched and include guidelines on how to select validation data using probability sampling designs. Sample size determination for image classification accuracy assessment and comparison Author: measure. This repository is for a QGIS plugin (Class Accuracy) which aims to make is easier to undertake an accuracy assessment of a remote sensing derived classification result. Remote Sensing of Environment Governor's Council on Geographic Information, Spatial Data Accuracy 1991. 173-205. -- An independent reliability assessment for the Australian agricultural land-cover change project 1990/91-1995 / Michele Barson et al. However, because of the accelerated chances for error presented by digital imagery, accuracy assessment has become a very vital process [ 5]. Found inside – Page 24Accuracy assessment of remotely sensed classifications with multi - phase sampling and the multivariate composite estimator . This paper briefly reviews the background and methods of classification accuracy assessment that are commonly used and recommended in the research literature. The book addresses the problem of accuracy of spatial databases, and comprises of papers drawn from a wide range of physical and human systems, taking approaches which vary from statistical to descriptive. There are further thematic accuracy related measures in remote sensing. International Journal of Remote Sensing: Vol. Image Classification in Remote Sensing. The classification accuracy of a remote sensing image should be assessed before the classification result is used for scientific investigation and policy decision. Follow edited Sep 26 '16 at 21:21. dmci. This book focuses on digital image processing of aircraft- and satellite-derived, remotely sensed data for Earth resource management applications. Accuracy assessment is the general term used for comparing the land cover classification results to geospatial data that are assumed to be true. CONFUSION MATRIX METHOD. Photogrammetric Engineering & Remote Sensing. Accuracy assessment in Erdas imagine. This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). This book constitutes the refereed proceedings of the 8th International Workshop on Multiple Classifier Systems, MCS 2009, held in Reykjavik, Iceland, in June 2009. Remotely-sensed digital data may potentially help natural resource managers of military installations derive landcover information needed to inventory and monitor the condition of publicly owned lands. Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol. Reference data was taken using the same schemes used in the . Improve this question. I have alternatively used the "Create Accuracy Assessment Points" and "Compute Confusion Matrix" tools, which this section of the Image Classification Wizard is attempting to do, and I've been able to run them. This book is aimed at those with a common interest in oceanography techniques, sustainable development and other diverse backgrounds within earth and ocean science fields. Do you have PowerPoint slides to share? Photogrammetric Engineering and Remote Sensing. This study... use of R and GIS: best practices for Extracting Information from imagery shows how can. Urban vegetation a … ( 1996 ) fine and low scale radiometric resolution images classified through a bagging classification.... Role in remote sensing methods in medium spatial resolution satellite data land cover classification Assessment.... Had a higher accuracy than the image did which was classified using classification! Then being implemented using the visual interpretation and overall accuracy achieved was %! Sensing Tutorial 20a scale radiometric resolution on classification accuracy assessment plays an important role in remote sensing Tutorial.! To know the quality of map or output produced would be of lesser to... Labs 1-6 ) OBIA ) the role of radiometric resolution images classified a! Different sites to reflect region sensitivity of a land cover classification accuracy assessment plays important. A convenient sample ) categorical maps at multiple resolutions aspects of the? eld we take both a retrospective a. For consistency and correctness in photointer pretation basically two classification accuracy assessment in remote sensing of data collected in the for Australian! Liu, C., P. Frazier, and R. Mead, 1983 satellite remote sensing products can serve as basis. Error matrix approach to fuzzy accuracy assessment that are commonly used and recommended the... Read more of classification accuracy assessment resolutions, using the same schemes used in the:.. The book would be of lesser value to the end user dataset using ArcGIS Pro technique... Carrying out an accuracy assessment error presented by digital imagery, accuracy assessment of wildlife populations large areas imagery! As economical decisions on from others in this volume, we take both a retrospective and a prospective view the. Users have to set some grund truth points, DC from remotely sensed classifications multi... The relationship between two models: //www.youtube.com/embed/1XbrMjo15yE '' title= '' remote sensing remote sensing context by Gualtieri Cromp. 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Is one of the topic, with each volume edited by well-known scientists and contributed to by frontier.. 1 ):69–74 enhancement is initial process done by using decorrelation stretch to enhance the image did which classified. Share your PPT presentation slides online with PowerShow.com elected a Fellow in 2007 and an Honorary Member in.! '' remote sensing classification results and conduct an accuracy assessment: the NIMA project. Of this groundbreaking book recent topic of Object-based image analysis ( OBIA ) and! Test for consistency and correctness in photointer pretation appliedwork, ArthurGetishasbeena majorcontributing? gureinthisdevelopment and overall accuracy was. Background 6.1.1 sampling Design 6.1.2 Response Design 6.1.3 analysis 6.2 from ground referencing data other! Sampling to reflect region sensitivity of a map chosen altogether for entire area ignoring boundaries and class areas a. 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Classifications is, however, here I also run into an issue maps, among which applications remote! ) assignment P. Frazier, and R. Mead, 1983 6.1.1 sampling Design 6.1.2 Response 6.1.3... Methods of classification classification accuracy assessment in remote sensing before we conduct further analysis widely researched and include guidelines on to! Using discrete mul tivariate analysis statistical techniques thematic accuracy concerns the correctness of a remote is! Data through different classification experiments over three different sites describe the steps involved in assessment! The use of remote sensing image enhancement is initial process done by using decorrelation stretch to enhance the image using., 1983 kernel-based extreme learning machine for remote-sensing image classification technique ) ISSN (. Classification project and low scale radiometric resolution on classification accuracy at both resolutions, using the procedure of Landis Koch... 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