遥感土地覆盖类型识别的自组织神经树模型  

Self-organization Neural Tree Model for Recognition about Land Cover Type of Remote Sensing

作　　者：蔡煜东[1] 李伟[1] 许伟杰[1] 

机构地区：[1]中国科学院上海冶金研究所

出　　处：《环境遥感》1995年第2期132-136,共5页

摘　　要：本文提出遥感土地类型识别的自组织神经树模型，并选取一组标样作为研究对象。在所选例子中预测效率较高，结果表明，该方法性能良好，可望成为遥感土地覆盖类型识别的有效手段。The self-organization neural tree for the recognition about land covertype of remote sensing was presented in this paper,which a group of samples wasstudied.The successful rate was high.The results show that the neural networkmodel was good,and therefore it might be referred as an effective technique forthe recognition about land cover type of remote sensing.

关 键 词：遥感 土地 覆盖类型 神经网络 神经树模型 

分 类 号：F301.2[经济管理—产业经济]