首页 -> 文献共享 -> 外文文献-> 正文

Classifying environmentally significant urban land uses with satellite imagery

作者：Mi-Hyun Park, Michael K. Stenstrom   出版商：ELSEVIER   出版日期：2007 年 1 月
Abstract:We investigated Bayesian networks to classify urban land use from satellite imagery.Landsat Enhanced Thematic Mapper Plus (ETM+) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80–95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and
inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.
查看全文 本地浏览
相关数据
暂无相关数据！
相关文章
暂无相关文献！
●  上一篇： Digital interpretation and management of land cover- a case study of Cyprus     ●  下一篇： 竞奏共鸣下的 “ 对话 ” ——— 从 《 地图 》 解读谭盾音乐    
声明：本站文献资源来源于网络，仅供学习交流使用，不得以任何形式用于商业用途，请于浏览后24小时内删除。如有疑问欢迎与我们联系，感谢您的支持。