Processing of multitemporal images and change detection has been an active research field in remote sensing for decades. Although plenty successful applications have been reported on the monitoring and detecting of environmental change, there are enormous challenges in applying multitemporal imagery to derive timely information on the Earth's environment and human activities. In recent years, great progress has been observed to overcome technological obstacles by the development of new platforms and sensors. The wider availability of large archives of historical images also makes long-term change detection and modelling possible. Such a development stimulates further investigations to develop more advanced image processing methods and new approaches to handling image data in the time dimension. This chapter reviews the current progress in the processing of multitemporal data and change detection. The nature of the environmental change on the Earth's surface is analysed first, followed by a review of the development of remote sensing change detection technology in the following four aspects: image preprocessing for change detection, the classification of change detection methods and approaches, methods of remote sensing change detection, and accuracy assessment in multitemporal image processing. This chapter tries to find the comprehensive solution from multi-source data, integrated processes and intelligent methods with the assistance of prior knowledge. It also points out the challenges that change detection is facing and possible countermeasures, in the hope of deepening the research into change detection technology for remote sensing images.