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中文摘要：
目的 探讨基于专家知识的决策树分类方法分类TM遥感影像识别鄱阳湖区钉螺孳生地。方法收集分类的地面样本点，分析同时期的鄱阳湖洲滩植被与钉螺分布关系数据，对同一时相的TM遥感影像，选取合适的试区，分析试区典型地物和地面样本点的光谱特征，形成用于分类的专家经验性知识，然后采用基于知识模型的专家决策分类方法分类识别钉螺孳生地。结果将试区分为6类，分别是苔草群落、荻草群落、藤草群落、藻类水体、河流和湖水体、滩地。对照同时期螺情资料，苔草群落为钉螺主要孳生地，在荻草群落和藤草群落地带偶然发现钉螺，但密度极低。采用基于混淆矩阵的方法评价分类结果精度，苔草群落、荻草群落和藤草群落的制图精度分别是87．69％、81．36％和94．44％，用户精度为86．36％、91．43％、84．16％，三者之间存在一定的错分现象，这主要是由于三者有一定的混生现象。另外，10月份是滩地植被生长旺盛的季节，它们的光谱在各个波段上均有相似之处，产生一定的错分，对本研究的最终结果不会造成较大的影响。结论在分析与TM遥感影像同一时相地面样本点的基础上，可采用基于知识模型的专家决策树分类方法分类遥感影像识别钉螺孳生地。
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