This book is devoted to the theory and method of the change detection on very high-resolution remote sensing image. Since the very high-resolution remote sensing images have been used in the field of land cover or land use change detection, problems such as salt and pepper effect, single spectral feature and the difficulty of discrimination of change types always affect the accuracy of information extraction by using the object-based image analysis.

This book comprehensively introduces the filed from basic theory of remote sensing change detection to various key technologies such as multi-scale image segmentation, consistency difference analysis, genetic particle swarm optimization multi feature selection, adaptive weight change vector analysis and so on. Using numerous data examples, it explains the relevant concepts and theoretical background of the object-based change detection and proposes a theoretical method and process of multi-feature change detection of very high-resolution remote sensing images. The targeted audience is advance graduate students and researchers who wish to learn about the physical process underlying the image segmentation, feature selection and change detection by using the very high-resolution remote sensing in the perspective of the object-based image analysis.

The basis of English translation of this book, originally in Chinese, was facilitated by artificial intelligence. The content was later revised by the author for accuracy.