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5

I've downloaded these granules and notice the same shift. It appears to be geographic processing error on ESA's behalf. I've never encountered a shift like this before. The image metadata is the same for both, which means some error occurred before the Level 1-C product. (the 100*100Km granules have already been processed, for more information look here) I ...


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the anomaly has been identified and is currently under investigation. It is not systematic as far as we know. Please report this kind of anomaly to the Copernicus help desk. Thanks Sébatien CLERC S2 Mission Performance Center


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You can download Sentinel 2 Imagery by going to the Sentinel Data Access Portal and selecting the Sentinel Data Hub Once you have arrived here select Scientific Hub In the top right hand corner select Sign Up (Enter all your info and verify the email they send you) Login to your new account. Begin your search by using the search bar and type in ...


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Looking at their site, they clearly state that: Circa year 2000 Landsat 7 cloud-free image composite (first) Reference multispectral imagery from the first available year, typically 2000. If no cloud-free observations were available for year 2000, imagery was taken from the closest year with cloud-free data, within the range 1999–2012. Circa ...


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As PolyGeo mentioned in his comment, your question is too broad. There are plenty of satellite images with high spatial resolution including QuickBird, Ikonos, WorldView-1 and WorldView-2 (spatial resolution of 0.46 m), and you can check sample image of WorldView-2, WorldView-3 now provide data at 0.31 m resolution. Answering this question will not be easy, ...


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Arc GIS have introduced the image classification tool in version 10. If You want to classify the images using Arc Map. Check this tutorial of the tool. You may also use other softwares like ENVI or ERDAS IMAGINE for this purpose. For the case of ENVI this tutorial guides you through the process and can perform both supervised and unsupervised ...


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There is no definitive way to determine the bands without vendor metadata. However, you can infer which bands are which by looking at a spectral profile of image reflectance values at features such as water and vegetation. For example, near infrared values in your imagery will be very low for water features and very high for healthy green vegetation. The red ...


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Layer stacking is a process for combining multiple images into a single image. In order to do that the images should have the same extent (number of rows and number of columns), which means you will need to resample other bands which have different spatial resolution to the target resolution. In other words, all images/bands should have same spatial ...


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Yes, there are Tasseled Cap Coefficients for the RapidEye sensors available: Brightness, Greenness and Yellowness. Yellowness - instead of the commonly derived Wetness (e.g. Landsat) - was derived because the RapidEye sensors do not have SWIR bands (SWIR bands respond to moisture variation, e.g. in soil/vegetation). Yellowness instead shows the variation of ...


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Just adding one more option, AWS hosts Landsat scenes on S3 https://aws.amazon.com/public-data-sets/landsat/ To do land cover classification, you could also consider using Sentinel 2 data. Sentinel 2A has been launched a few months ago, its 10m resolution with 13 spectral bands. The Copernicus program grants full open access to the sentinel data: ...


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@Mr. Che and @Aaron have given great answers regarding two different things to do, but i would like to point out that there is actually a quick and easy way to use the landsat data without dealing with implementing the fmask algorithm or doing the atmospheric correction yourself: by using the surface reflectance data processed based on Landsat data. They are ...


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Can you tell me what module are you using ? You should be able to do that. You need to use the "Edit ENVI Header" and then open the Edit Attributes. When you are there scroll down to "Data Ignore Value" and set to Zero.


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McNemar's test is a test for paired proportions, I do not see how it applies to a multi-class confusion matrix. Commonly, it is applied to validate logistic models. You cannot hope to aggregate the entire confusion matrix into an 2x2 contingency matrix and expect a valid hypothesis test. I suppose that you could iterate through classes, deriving an ...



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