What is meant by "object-based image analysis"?

"Object-based image analysis" refers to a method that involves classifying and analyzing groups of similar pixels rather than focusing solely on individual pixels. This approach is designed to enhance the accuracy and efficiency of image analysis by taking into account the spatial relationships and contextual information of pixel groups, which often correspond to real-world objects or features.

In contrast to methods that work with individual pixels, such as pixel-based classification, object-based analysis recognizes that many features in an image (like buildings, vegetation, or water bodies) can be represented as discrete objects. This allows for better differentiation between classes by using characteristics such as shape, size, texture, and the relationships between adjacent groups of pixels.

This method is particularly advantageous in remote sensing applications where complexity and variability of features can lead to misclassifications if only pixel intensities are considered. By focusing on groups of pixels that share common attributes, object-based image analysis can deliver more meaningful and contextually relevant classifications of the landscape being analyzed.