另一种理解这些概念的方式如下: 深度:在根位置画一条水平线，并将这条线作为地面。所以根结点的深度是0，它所有的子结点都向下增长所以每一层结点的深度都是+ 1。

高度:同样的水平线，但这次地面位置是外部节点，这是树的叶子，向上计数。

另一种理解这些概念的方式如下: 深度:在根位置画一条水平线，并将这条线作为地面。所以根结点的深度是0，它所有的子结点都向下增长所以每一层结点的深度都是+ 1。

高度:同样的水平线，但这次地面位置是外部节点，这是树的叶子，向上计数。

树的高度和深度是相等的……

但是节点的高度和深度是不相等的，因为…

高度是通过从给定节点遍历到可能最深的叶来计算的。

深度是从根到给定节点.....的遍历计算的

树的整体深度等于树的高度，树的级别也一样，但如果对于特定的节点高度不等于深度，因为深度的定义表明从根节点到该节点的最长路径，对于高度，它是从该节点到叶节点。

总体树，D=H=L 但D可能不等于H。

我想写这篇文章是因为我是一名计算机专业的本科生，我们越来越多地使用OpenDSA和其他开源教科书。从评分最高的答案来看，似乎教高度和深度的方式一代一代都在改变，我把这篇文章贴出来是为了让每个人都意识到这种差异现在是存在的，希望不会在任何程序中导致错误!谢谢。

摘自OpenDSA数据结构和算法书:

If n1, n2,...,nk is a sequence of nodes in the tree such that ni is the parent of ni+1 for 1<=i<k, then this sequence is called a path from n1 to nk. The length of the path is k−1. If there is a path from node R to node M, then R is an ancestor of M, and M is a descendant of R. Thus, all nodes in the tree are descendants of the root of the tree, while the root is the ancestor of all nodes. The depth of a node M in the tree is the length of the path from the root of the tree to M. The height of a tree is one more than the depth of the deepest node in the tree. All nodes of depth d are at level d in the tree. The root is the only node at level 0, and its depth is 0. Figure 7.2.1: A binary tree. Node A is the root. Nodes B and C are A's children. Nodes B and D together form a subtree. Node B has two children: Its left child is the empty tree and its right child is D. Nodes A, C, and E are ancestors of G. Nodes D, E, and F make up level 2 of the tree; node A is at level 0. The edges from A to C to E to G form a path of length 3. Nodes D, G, H, and I are leaves. Nodes A, B, C, E, and F are internal nodes. The depth of I is 3. The height of this tree is 4.

简单的回答是: 深度: 1. 树:从树的根节点到叶节点的边/弧的数量称为树的深度。 2. 节点:从根节点到该节点的边数/弧数称为该节点的深度。