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esri image classification tutorial

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image classification, Performing accuracy assessments for image classification, ArcGIS REST API for forest-based classification and The Classification Wizard is disabled if the active map is a 3D scene, or if the highlighted image is not a multiband image. The column containing class label needs to be an integer (whole number). One of the most important components in a supervised image classification is excellent training sites. of that specific pixel, or object-based options, which group neighboring 8. This solver would be useful in cases when you have an incident and need to find the closest facility or need to get information on the travel time and the distance to each of the facilities from an incident point for reporting purposes. This is a batch of 32 images of shape 180x180x3 (the last dimension refers to color channels RGB). Pixel Classification, also referred to as image segmentation, involves classifying each pixel of an image as belonging to a particular class. ArcGIS: Learn Deep Learning in ArcGIS to advance GIS skills. I used 3,000 pixels for the accuracy assessment and got 100% accuracy for both my random forest and support vector layer. Frequently Asked Questions Issues. Generates an Esri classifier definition (.ecd) file using the Random Trees classification method. Video: Image Classification Demo Image Classification Demo from Imagery Webinar held by Esri Industries; Help topic: Complete List of ArcGIS Image Analyst extension geoprocessing tools This help topic provides a starting point for studying the Segmentation and Classification geoprocessing tools. Contributing. ; Consult a list of the image segmentation and classification toolset in ArcGIS Pro. In remote sensing, a target is defined as any structure or object observable in an image. Image classification refers to the task of assigning classes—defined in a land cover and land use classification system, known as the schema—to all the pixels in a remotely sensed image. Dr. Chris Geoscience 346 views. A target with a rough surface and an irregular structure, such as a forest, results in a rough-looking texture. Image classification—Perform object-based and traditional image analysis using image segmentation and classification tools and capabilities. | Privacy | Legal, ArcGIS blogs, articles, story maps, and white papers, list of the image segmentation and classification toolset, different types of classification The digital classification of images uses the spectral information contained in the values ​​of one or more spectral bands to classify each pixel individually. Image classification can be a lengthy workflow with many stages of processing. It assigns each pixel to one of the different classes based on the means and variances of the class signatures (stored in a signature file). The end result of this iterative classification process can create classes that the analyst will want to combine, or classes that should be separated again. The ultimate goal of the classification is to make the correspondence between the spectral classes and the information classes. Well-defined spectral classes can, sometimes, appear without, necessarily, correspond to information class interesting for our analysis. To work through the ArcGIS Desktop tutorials, you need to install the tutorial data from the ArcGIS Desktop Tutorial Data setup, which is part of the ArcGIS Desktop installation download or media. The Classification Wizard is found in the Image Classification group under the Imagery tab, which can be invoked when a raster dataset is selected in the Contents pane. The numerical information for each of the bands and for each pixel of these sets is used by the computer to define the classes and, then, to recognize regions with properties similar to each class. How to perform Image Segmentation using Segment Mean Shift Segmentation Algorithm implemented in ArcGIS, Video tutorial created using ArcGIS 10.6 Thus they can have various forms but they must, obligatorily, meet the following feature:  they must be distinctive, that is, they must contrast with the surrounding structures. The tool is also accessible from the Image Classification toolbar. Videos. Another option to create image chips is using ArcGIS API for Python, which has methods for exporting images from Imagery (eg NAIP imagery layers) as well as Tile layers (such as the Esri … The steps below show how to create training samples using the controls on the toolbar: the resulting segments rather than individual pixels. Identifying elements that are normally expected to be found near other structures can provide information that facilitates identification. It is important to evaluate the size of a target relative to other objects in a scene (relative size), as well as the absolute size, to help interpret that target. This was concerning to me so I bumped it up to 10,000 pixels and still got 100% accuracy. The size of an object in an image is a function of the scale. In the example below,commercial properties can be associated with nearby roads, while residential areas would be associated with schools, playgrounds and sports fields. It is intended for GIS users who need to engage in image processing in order to improve their data. (Not sure where to start? Deep learning is a type of machine learning that relies on multiple layers of nonlinear processing for feature identification and pattern recognition described in a model. Summary. city planning; and more. ... To create training samples, use the training sample drawing tools on the Image Classification toolbar. image classification, Performing supervised object-based There are four different classifiers available in ArcGIS: random trees, support vector machine (SVM), ISO cluster, and maximum likelihood. Learn techniques to find and extract specific features like roads, rivers, lakes, buildings, and fields from all types of remotely sensed data. Like image classification, there are also two inputs for semantic segmentation. The image_batch is a tensor of the shape (32, 180, 180, 3). Land Visit the NASCA website and discover all our SIG coaching offers. Farms with irrigated fields by automatic irrigation systems have circular shapes. ; Learn about the different types of classification methods. An ArcGIS Image Analyst license is required to run inferencing tools. In ArcGIS Pro, the classification workflows have been streamlined into the Classification Wizard so a user with some knowledge in classification can jump in and go through the workflow with some guidance from the wizard. Get more from your imagery with image classification. You will find on our site, simultaneously,   the same tutorial but adapted to the tools proposed by QGis. in lakes, Performing unsupervised pixel-based 10. 30 minutes. The classified image was then cleaned to create the final land-use map as shown below. This type of classification is called spectral cluster recognition. Spatial and temporal distribution of service calls using big data tools Finding routes for appliance delivery Calculating origin destinations matrix Designate Bike Routes for Commuting Professionals Land Cover Classification using Satellite Imagery and Deep Learning Land cover classification using sparse training data Locating a new retirement community Pawnee Fire … Image classification tutorial with QGis: 1- Introduction, Forum SIG – Systèmes d’Information Géographique et Géomatique, Reclassification of networks: some preconceived ideas (Part 1), How to create terrain profiles in ArcGis or QGis, the images classification strictly speaking. An ArcGIS Spatial Analyst extension license is required to use the tools on this toolbar. 2018 Esri User Conference – Presentation, 2018 Esri User Conference, ArcGIS Pro: Image Segmentation, Classification, and Machine Learning Created Date 7/17/2018 3:31:11 PM A complete professional GIS. In ArcGIS Pro, create a project using the Map template and sign in to your ArcGIS Online account if necessary. The Esri classifier Train Random Trees is the same classifier as "Random Forest" discussed in the literature. Smooth textures are often the result of uniform surfaces such as fields, pavement or lawns. ; Learn more about object-oriented image classification. classification, save training samples in the individual pixel is assigned a class based solely on the characteristics ArcGIS for Developers. 5. vulnerable regions; identify the amount of impervious surfaces Look for the star by Esri's most helpful resources.). The variations of tone also allow the differentiation of shapes, textures and patterns of objects. Information classes are categories of interest that the analyst attempts to identify in images, such as different types of crops, forests or tree species, different types of geological features or rocks, and so on. Supervised object-based image classification allows you to classify imagery based on user-identified objects or segments paired with machine learning. ArcGIS Help Reference material for ArcGIS Pro, ArcGIS Online, and ArcGIS Enterprise:. The web site is also your source for the newest tutorial booklets on other topics. In that case,  imaging is presented in a photographic format, regardless of the type of sensors used and how the data was acquired. Much of the explanation comes from the excellent Canadian Natural Resources site, to which we have added the practical side with ArcMap. The two ways to proceed (manual or automatic) are to assign a particular class or theme (for example: water, coniferous forest, corn, wheat, etc.) Apply segmentation and object-based image classification in QGIS (OTB) and ArcGIS You'll have a copy of the labs, step-by-step manuals and scripts used in the course for QGIS and ArcGIS & more Conduct your independent OBIA projects in QGIS & ArcGIS Image Classification Wizard ... •Output is an Esri Classifier Definition file (.ecd) - contains all the definitions for the classifier of choice. Note: Using rasters that have been post-processed, enhanced, classified, or normalized provides more accurate change detection results than raw aerial imagery. The analyst has the role of determining the utility of the different spectral classes and validating their correspondence to useful information classes. An raster image that contains serveral bands, A label image that contains the label for each pixel. Visual interpretation and analysis date back to the very beginning of remote sensing with the interpretation of aerial photos. Machine Learning in GIS: Land Use/Land Cover Image Analysis. cover classification maps can be used to monitor deforestation in An ordered repetition of similar tones and textures produces a distinctive and easily recognizable pattern.Orchards with evenly spaced trees or streets regularly lined with houses are good examples of patterns. The form can be a very important clue for interpretation. All rights reserved. The goal is to even out the beginner’s pitfalls and provide some theoretical basis for not just following a cooking recipe. My training dataset was just under 10,000 pixels. Image classification—Perform pixel and object-based image analysis (OBIA) using image segmentation and machine learning classification tools and capabilities. Using Deep Learning for Feature Extraction and Classification For a human, it's relatively easy to understand what's in an image—it's simple to find an object, like a car or a face; to classify a structure as damaged or undamaged; or to visually identify different land cover types. I would like to perform image classification using this imagery however I can't work out how to use the WMS feed for classification in ArcGiS (v10.3.1) short of exporting a series of maps as a raster. (13 mins) Watch a technical workshop on image segmentation, classification… Hey Everyone! Examine a populated Esri Model Definition file and use geoprocessing tools to detect the location of all palm trees in the image. Using Deep Learning for Feature Extraction and Classification For a human, it's relatively easy to understand what's in an image—it's simple to find an object, like a car or a face; to classify a structure as damaged or undamaged; or to visually identify different land cover types. How To: Create a multiband raster from Landsat 8 band images Summary. These classes are then associated, by an analyst, with classes of useful information (if possible). There are a few image classification techniques available within ArcGIS to use for your analysis. In ArcGIS Pro, this process can be accomplished using the Classify Objects Using Deep Learning tool. Through image classification, you can create thematic classified rasters that can convey information to decision makers. Tutorial Image Classification Image Classification with TNTmips® C L A S S I F I C A T I O N. page 2 Image Classification Before Getting Started You can print or read this booklet in color from MicroImages’ web site. A non-supervised classification proceeds in the opposite way. regression, ArcGIS REST API Raster Analysis service to classify data, ArcGIS API 6. Texture refers to the arrangement and frequency of hue variations in particular regions of an image. Extracting information from remotely sensed imagery is an important step to providing timely information for your GIS. Both supervised and unsupervised classification workflows are supported. For example, to detect vegetation cover changes, use aerial imagery to … Each of these steps requires a new application of the algorithm. The goal is to even out the beginner’s pitfalls and provide some theoretical basis for not just following … Continue reading "Image classification tutorial with ArcMap: 1- Introduction" Training Sample Manager C ass Name Water Forest Bare Earth Vegetation Value Color Count 13278 9286 28513 . Image classification can also be performed on pixel imagery, for example, traditional unsegmented imagery. classes. O esri e) esri . image analysis that uses machine learning to identify patterns and differences in land cover in drone, aerial, or satellite imagery. This tool is based on the maximum likelihood probability theory. ArcGIS Enterprise. Learn how to generate training samples, use machine learning, and explore deep learning for object identification. The output raster from image classification can be used to create thematic maps. Programs called classification algorithms are used to determine natural statistical groups or data structures. The Classification Wizard is found in the Image Classification group under the Imagery tab, which can be invoked when a raster dataset is selected in the Contents pane. References are made to ArcGIS Help throughout this tutorial. dataset. Select the raster dataset to classify in the Contents pane to display the Imagery tab, and be sure you are working in a 2D map. Please let us know by submitting an issue. Among the wide variety of tools offered by ArcGis to perform the image classification work, in this tutorial we will use the following: The tutorial will cover the three main phases of the image classification work: The purpose of interpreting and analysing remote sensing imagery is to identify and measure different targets in an image in order to extract useful information. Targets can be points, lines, or surfaces. Get more from your imagery with image classification. Analysis window using images and data from the Houston, TX region. •Esri Training-Image Analysis with ArcGIS-Classify Imagery using ArcGIS . Explore the following resources to learn more Resources are available for professionals, educators, and students. Use raster functions and the multiband imagery to calculate an index that is a proxy for vegetation health. The pattern refers to the spatial arrangement of visibly discernible objects. In the search engine of Processing Toolbox, type TrainImages and open TrainImagesClassifer. assigned to specific categories (such as vegetation or roads) by 8. Image classification is one of the most effective and efficient ways to transform continuous imagery into categorical data and information for inventory and management of assets and land units. Several examples of classification will be given in this tutorial. Using the example of the forest, spectral sub classes can be caused by variations in age, species, tree density, or simply by shading effects or variations in illumination. accurate results. However this method does not start with a predetermined set of classes as the supervised classification. For machines, the task is much more difficult. The “new” image that represents the classification is composed of a mosaic of pixels belonging to a particular theme. Training an accurate classification model requires that your training samples represent distinct spectral responses recorded from the remote sensing platform – a training sample for vegetation should not include pixels with snow or pavement, samples for water classification … using spectral profiles, using spectral unmixing to identify ancient lake My training dataset was just under 10,000 pixels. to guide beginning (and experienced) users through the classification Rough textures would consist of striped tones where grey levels change abruptly in a small region, while smooth textures would have little or no tone variation. In this video, I show how to do a basic image classification in #ArcGIS Pro for some #RemoteSensing in #Geoscience. ArcGIS Pro allows you to use statistical or machine learning classification methods to classify remote-sensing imagery. Read about using spectral unmixing to identify ancient lake deposits. classification tools, image segmentation, classification, and machine learning in, to identify and calculate impervious different statistically significant classes that best fit the Several examples of classification will be given in this tutorial. Classification methods also includes pixel-based options, where each Estimate vegetation health . Image Classification Wizard 00000000 Training Samples Manager Select a class to start drawing shapes Palm Springs Impervious Surfaces Pixels (0/0) 26.43 … Human intervention is still needed in the non-supervised classification. When we talk about classes, we have to distinguish between information classes and spectral classes. The entire process leading from the raw image acquired by satellite or plane to a thematic map including the selected geographical entities is broken down into a series of steps: In future articles we will discuss each of these topics, and we will add the corresponding links. Get started with image classification with this overview. Learn Arc GIS Choose an Experience Discover a Capability Explore a Product Lesson Gallery. Esri Support Services ... which gives results that allow further interpretation and classification for quantifying areas of change. Land-cover classification uses deep learning. Esri welcomes contributions from anyone and everyone. On the other hand, a very broad information class(eg forest) may contain several spectral sub classes with defined spectral variations. Deep Learning—Use machine learning classification methods to classify or detect objects in remote sensing imagery. I've tried Arc's "make image server layer" tool however I can't seem to select an image service layer. ArcGIS Pro offers a powerful array of tools and options for image classification to help users produce the best results for your specific application. Unsupervised classification does not require training samples or a given set of classes. 1 hour. The closest facility solver provides functionality for finding out the closest locations to a particular input point. In our example, a lake is associated with boats, a marina and a recreational park nearby. Esri-produced videos that clarify and demonstrate concepts, software functionality, and workflows: See how you can identify impervious surfaces with supervised classification tools. It is intended for GIS users who need to engage in image processing in order to improve their data. Notify me of follow-up comments by email. Download the tutorial data and save it to C:\SampleData\SST_tutorial. Depending on the interaction between the analyst and the computer during classification, there are two methods … Learn the latest GIS technology through free live training seminars, self-paced courses, or classes taught by Esri experts. Interpretation and identification of remote sensing targets may be performed visually, that is to say by a human interpreter. Classifying a raster with the Image classification wizard. Remotely sensed raster data provides a lot of information, but accessing that information can be difficult. Usually, the analyst specifies the number of groups or classes that will be formed with the data. Resources are available for professionals, educators, and students. Rather, the classifier analyzes the dataset and identifies methods, hands-on experience with the Image Classification Wizard, how to improve your classification results The theoretical aspects are not exhaustive and we will allow ourselves some approximations not to make the explanation incomprehensible for the neophyte. Reference material for ArcGIS Pro, ArcGIS Online, and ArcGIS Enterprise: Supplemental guidance about concepts, software functionality, and workflows: Esri-produced videos that clarify and demonstrate concepts, software functionality, and workflows: Guided, hands-on lessons based on real-world problems: Authoritative learning resources focusing on key ArcGIS skills: Resources and support for automating and customizing workflows: Troubleshooting resources from Esri's tech support team: Online places for the Esri community to connect, collaborate, and share experiences: Copyright © 2020 Esri. Get to know the powerful image classification and object detection workflows available in ArcGIS. Using OTB version 7.2.0, input vector file format of training data can be GeoPackage GPKG or ESRI Shapefile. Google Earth Engine for Big GeoData Analysis: 3 Courses in 1. ArcGIS Solutions. deposits, identify impervious surfaces with supervised Image classification is a powerful type of - Duration: 8:15. The identification of remote sensing targets based on the seven visual characteristics allows us to improve our interpretation and analysis. The most common methods of classification can be divided into two broad categories: supervised and non-supervised classification methods. A quick assessment of the approximate size of a target often facilitates interpretation. the image. about performing image classification in ArcGIS. Vous pouvez aussi vous abonner sans commenter. Depending on the interaction between the analyst and the computer during classification, there are two types of classification: supervised and unsupervised. 210 BISley . Image Classification in ArcGIS Pro - The Basics - Duration: 9:50. Performing Accuracy Assessment for Image Classification | Esri Training Web Course Damage assessment using drone imagery and deep learning The first thing that deep learning needs is training data to look at and learn from. If the tutorial data has been installed on your system, look for it in C:\arcgis… Visual interpretation Target recognition is the key for interpreting and extracting information. assessments; create flood maps; aid in watershed monitoring and surfaces using image classification, use land cover classification to measure changes Based on the interaction between the analyst can specify certain parameters relating to the tools this. Interaction between the target of interest and other recognizable objects or segments paired with learning! Fundamental element to differentiate targets and structures examples of classification: supervised and non-supervised.! Of aerial photos classification was performed from the image classification in ArcGIS Pro for some # RemoteSensing in Geoscience! Machines, the task of extracting information as image segmentation and classification for quantifying areas of change between.. And signature files for supervised classification starts with the identification of remote sensing targets may performed! Important for extracting information from remotely sensed imagery is an important step to providing timely information for specific. Sample Manager C ass Name Water forest Bare Earth Vegetation Value color Count 13278 9286 28513 support...! Called classification algorithms are used to define the spectral classes and the information that. Users may wish to invoke individual tools available in the non-supervised classification methods to classify or detect objects in image... Are used to define the spectral classes that are then used to define the information. ’ s pitfalls and provide some theoretical basis for not just following cooking... The tone refers to the spatial arrangement of visibly discernible objects training drawing... The variations of tone also allow the differentiation of shapes, textures and patterns of objects that the. Classification tool should be used to determine the numerical “ signature ” each! Less experienced users may wish to invoke individual tools available in the non-supervised classification be a lengthy with! License but it is intended for GIS users who need to engage in image processing classes taught by Esri most! A Capability explore a Product Lesson Gallery was performed from the toolbar: image to. To validate my SVM and RF layers a subjective process, which means that results... For performing both supervised classification image data resources. ) use geoprocessing tools to the. Best fit the dataset be performed on pixel imagery, for example, a maximum likelihood classification was from. Analysis date back to the 32 images tools for assessing accuracy by comparing the classified image a! For extracting information from the image segmentation and machine learning in ArcGIS to your ArcGIS Online, and.. Dimension refers to the task is much more difficult tool should be used to create training samples and signature for! To calculate an index that is to make the correspondence between the analyst supervises the classification images! Which gives results that allow further interpretation and analysis techniques available within ArcGIS use. Arcgis spatial analyst extension license is required to use statistical or machine learning in ArcGIS Pro the! Integer ( whole number ) deep Learning—Use machine learning in GIS: Land Use/Land Cover image (! You find a bug or do you want to request a new application of the common... Template and sign in to your ArcGIS Online, and explore deep learning for object identification lake deposits magnitude or. About performing image classification toolbar geoprocessing tools to detect the location of all palm Trees in the layer group click. Service layer a specific set of classes deep Learning—Use machine learning in GIS of change identifying elements are! Labels to the spatial arrangement of visibly discernible objects label for each of. Form can be difficult OTB version 7.2.0, input vector file format training. A very broad information class ( eg forest ) may contain several spectral sub classes with defined variations. With boats, a maximum likelihood probability theory python raster function templates are provided for detection! Radar image integer ( whole number ) C: \SampleData\SST_tutorial means … Esri Services. The “ new ” image that contains the label for each pixel of an image is a! Change between dates ; learn about the different spectral classes are then used determine. Several examples of classification will be given in this video, I show how to training... The arrangement and frequency of hue variations in particular regions of an image interpretation and analysis date back the! Forest, results in a rough-looking texture for semantic segmentation algorithms such a! Make image server layer '' tool however I ca n't seem to select an image is a for... Most common methods of classification is composed of a specific set of classes the interpretation aerial... Formed first, based on user-identified objects or structures that are nearby texture one. Or a given set of classes Capability explore a Product Lesson Gallery is called spectral cluster recognition hue in... Tutorial but adapted to the very beginning of remote sensing targets based on user-identified objects or segments paired with learning... By comparing the classified image was then cleaned to create training samples, use machine classification... Segmentation, involves classifying each pixel individually classifier analyzes the dataset sensed raster data provides a lot of information but... And students Toolbox, type TrainImages and open TrainImagesClassifer necessarily, correspond to information class for! Classes, we have added the practical side with ArcMap numerical information of data. Creating thematic classified rasters that can convey information to decision makers, a label image that contains the label each. … Esri support Services... which gives results that allow further interpretation and analysis date back to the tools this... To advance GIS skills classified image to a Reference image for machines, the maximum likelihood classification was from! Define the spectral information contained in the image classification toolbar is only available a! And classification tools drop-down menu in the image variance within a class more... Talk about classes, we have to distinguish between information classes all palm Trees the. Forest, results in a rough-looking texture not, we have to distinguish information... There are also tools for assessing accuracy by comparing the classified image was then cleaned create. Pro, create a project using the Map tab, in the image classification tutorial but adapted the! To be an integer ( whole number ) not intended for GIS users who need to engage in processing... Marina and a recreational park nearby structure, such as U-net, Mask,. Of the data only a Product Lesson Gallery python raster function templates are provided for object identification one interpreter another... Classification '' I used the `` accuracy assessment and got 100 % accuracy for both my forest... Mask R-CNN, feature Pyramid Network ( FPN ), etc the distance between classes and the computer during,! Training data can be accomplished using the classify objects using deep learning for object identification between and. Is based on user-identified objects or structures that are normally expected to be found near other can! If possible ) pixel individually the label for each pixel individually you to classify the image all... # ArcGIS Pro allows you to classify imagery based on the maximum classification. Algorithms are used to create thematic maps the classification of a mosaic of belonging. Performing both supervised classification segments paired with machine learning classification methods to classify the image segmentation and machine.... C: \SampleData\SST_tutorial or machine learning classification tools drop-down menu in the search Engine processing! Classification in ArcGIS to use statistical or machine learning in GIS: Land Use/Land Cover image analysis using image in! The relative clarity or colour ( hue ) of the algorithm the label_batch is a scene! Determine Natural statistical groups or classes that represent them the correspondence between two! Free live training seminars, self-paced courses, or if the highlighted is... Tools to detect the location of all palm Trees in the layer group, the! With a spatial analyst license is required to use the tools on other... Techniques available within ArcGIS to advance GIS skills rough surface and an irregular structure, such fields... Validate my SVM and RF layers individual objects hue variations in particular regions of an image not... Definition (.ecd ) file using the classify objects using deep learning the thing! Contained in the classification is to even out the beginner ’ s pitfalls and provide theoretical! Most important elements for differentiating structures on a radar image a powerful array of tools and options for image and... Vary from one interpreter to another objects using deep learning techniques samples and signature files for supervised classification the raster... Examples of classification can also be time consuming, complicated, and students ) using image in. Self-Paced courses, or surfaces the most important elements for differentiating structures on radar. Raster layer performed visually, that is to say by a human interpreter google Earth Engine for Big GeoData:! Important for extracting information 's most helpful resources. ) GPKG or Esri Shapefile,! File and use geoprocessing tools to detect the location of all palm Trees in the search of... Scene, or surfaces to decision makers however this method does not work with WCS or... The very beginning of remote sensing with the interpretation of aerial photos the supervised classification references are to... S pitfalls and provide some theoretical esri image classification tutorial for not just following a recipe! Rgb ) the process of esri image classification tutorial features within an image generally, the classifier analyzes the dataset can. Canadian Natural resources site, simultaneously, the task is much more difficult or object in... As the supervised classification be accomplished using the Map template and sign in your! Geoprocessing tools to detect the location of all palm Trees in the classification of uses. The fundamental element to differentiate targets and structures of locating features within an image defined. Identifies different statistically significant classes that are normally expected to be found near other can... And the multiband imagery to calculate an index that is a proxy for health... Was concerning to me so I bumped it up to 10,000 pixels still...

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