Practice teaching of landscape survey course based on ecognition remote sensing image interpretation* Technology

Abstract

With the rapid development of modern 3S technology (Remote Sensing, Geography Information Systems, and Global Positioning Systems) and the rise of the digital landscape research globally, it has become the inevitable development trend for the landscape architecture teaching to make full use of Remote Sensing (RS) interpretation technology, improve the landscape survey digital platform, enrich the landscape analysis of objective data, find the inherent law of natural and man-made environment, and stimulate the scientific and technological progress of landscape architecture. To this end, based on the application status of RS image interpretation technology in the field of contemporary landscape architecture, this paper studies the application of eCognition RS image interpretation technology in the practice teaching of landscape survey. Firstly, through comparison of related technologies, the advantages and its teaching application possibility of eCognition image interpretation technology were stated. Secondly, various stages of eCognition RS image interpretation technology in assisting landscape design were analysed, highlighting the teaching application in landscape survey; besides, specific examples were taken to explain and verify how to carry out the practice teaching of landscape survey. Finally, the application characteristics of eCognition RS image interpretation technology and the future development trend of landscape RS teaching were summarized. The application results show that the introduction of eCognition RS image interpretation technology into practice teaching of landscape architecture can effectively improve teaching efficiency and learning effects, and promote the simultaneous development of students’ practical ability, analytical ability and judgment ability. Moreover, it has broad application prospects in the teaching parts of landscape survey, assessment, design and performance. The research findings are of great significance to promote the application of RS image interpretation technology in landscape teaching.