Mixed Pixels in the Image. Remote Sensing.

Mixed pixels in remote sensing refer to pixels in an image that contain more than one land cover or land use type. These pixels can occur due to the presence of multiple land cover types in the same area, or due to the limited spatial resolution of the image.

For example, a mixed pixel may contain both vegetation and water, or both urban and natural vegetation. In such cases, it can be difficult to assign a single class label to the pixel, as it contains multiple land cover types. This is a common problem in remote sensing, especially when using high-resolution satellite imagery or aerial imagery.

Mixed pixels can have a significant impact on the accuracy of image classification, as they can lead to misclassification of land cover types and can result in errors in land cover mapping. To overcome this problem, different methods such as Spectral mixture analysis, Object-based classification, Decision tree or Random Forest classifier, and Hybrid methods can be used to classify mixed pixels.

Overall, mixed pixels in remote sensing are a common problem that can have a significant impact on the accuracy of image classification. To overcome this problem, different methods can be used to classify mixed pixels and improve the accuracy of land cover mapping.

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