STS理念下的《遥感图像信息处理》教学探索——以土地资源管理专业为例被引量：4

Teaching Method for the course Remote Sensing information Image Processing Based on the STS Education:A Case Study of Land Resource Management Speciality

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摘要当今的科学教育是科学与人文相融合的教育,而"STS"(科学、技术、社会)的目标就是培养人文内涵和科学素养兼备的人才,在科学教育中渗透素质教育。文中提出在《遥感图像信息处理》的教学中渗透"STS"理念,对教学的方式方法进行改革。该方法对培养学生的科学态度、发展学生团结互助、勇于创新的精神、形成独立思考和探索实践的能力具有重要意义,并在教学实践中取得了一定的效果。 Today＇s science education is an education which integrates science and humanities education, and the goals of STS （Science, Technology and Society） are to develop students with both scientific and cultural connotation and to infiltrate quality education in science education. In this study, STS philosophy is infiltrated in the teaching of the course Remote Sensing Image Information Processing to reform the teaching methods. This method is of value for students to develop a scientific attitude, a solidarity and innovative spirit, and independent thinking, and the ability to explore independently. This method has been tried in teaching practice and achieved satisfactory results.

作者徐丽华

机构地区西南大学资源环境学院

出处《西南农业大学学报（社会科学版）》 2008年第4期159-161,共3页 Journal of Southwest Agricultural University:Social Science Edition

关键词 STS遥感图像信息处理教学改革人文教育 STS remote sensing image information processing teaching reform humanities education

分类号 G642.4 [文化科学—高等教育学]

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参考文献3

1张继贤,杨贵军.单一时相遥感数据土地利用与覆盖变化自动检测方法[J].遥感学报,2005,9(3):294-299. 被引量：41
2张泽光.河北省坝上高原土地资源动态遥感监测[J].衡水学院学报,2007,9(1):115-117. 被引量：1
3贾竹君.STS教育及其在大学物理教学中的渗透策略[J].湖南科技学院学报,2006,27(5):300-302. 被引量：9

二级参考文献15

1MAS J F. Monitoring Land - cover Changes: A Comparison of Change Detection Techniques[J]. Int. J. Remote Sensing.1999,20(1):139-152.
2Daniel J. Hayes, Steven A. Sader. Comparison of Change-Detection Techniques for Monitoring Tropical Forest Clearing and Vegetation Regrowth in a Time Series[J]. Photogrammetric Engineering & Remote Sensing, 2001,67(9):1067-1075.
3Daniel L. Civco et al. A Comparison of Land Use and Land Cover Change Detection Methods[R]. 2002 ASPRS-ACSM Annual Conference and FIG ⅩⅩⅡ Congress, April 22-26, 2002.
4Molenaar, An Introduction to the Theory of Spatial Object Modeling for GIS[A]. Research Monographs in GIS series[C], Wiley & Francis, London,1998.
5Wang, Y, Civco DL. Three Artificial Neural Network Paradigms in High Dimensional Multisource Spatialdata Classification[A]. The Association of Chinese Professionals in GIS Geographic Information Science[C].1996,1(2):73-87.
6Niemeyer, I, Canty M J. Object-Oriented Post-Classification of Change Images[A]. Proceedings of SPIE's International Symposium on Remote Sensing, Toulouse, France, 17-21 September 2001, SPIE,2001 , 4545.
7Koeln, G, Bissonnette J. Cross-correlation Analysis: Mapping Land Cover Change with a Historic Land Cover Database and Recent,Single-date Multispectral Image[A].Proc. 2000 ASPRS Annual Convention, Washington, DC,2000.
8Hurd, J. D,Civco DL, LaBash C, et al. Coastal Wetland Mapping and Change Detection in the Northeast United States[A]. Proc. 1992 ASPRS/ACSM/RT'92 Convention[C]. Washington, D. C. 1:130-139,1992.
9Civco, D. L. Knowledge-based Land Use and Land Cover Mapping[A]. Proc. of the 1989 Annual Meeting of the American Society for Photogrammetry and Remote Sensing[C]. Baltimore,MD,1989.
10席专狄.STS教育与教学[J].内蒙古教育,2005,(3):23-23.