Pixel-Based Classification

Pixel-based classification is a method used in remote sensing and image analysis to categorize each individual pixel in an image, such as satellite photos or aerial images. It involves analyzing the color, brightness, and other spectral features of each pixel to determine what type of land cover it represents—like water, forest, urban areas, or farmland. This approach treats each pixel independently, making it useful for detailed, high-resolution mapping. It’s widely used in environmental monitoring, land use planning, and resource management to provide accurate, pixel-level information about the Earth's surface.