本文的主要目的，是利用sentinel-2影像去云去雪分析然后导出KMEANS聚类分析后的影像，这次使用的分类是15个分类，大家可以自行选择分类数量。
函数：
https://www.cbedai.net/xg Can use either the Euclidean distance (default) or the Manhattan distance. If the Manhattan distance is used, then centroids are computed as the component-wise median rather than mean. For more information see:
D. Arthur, S. Vassilvitskii: k-means++: the advantages of careful seeding. In: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, 1027-1035, 2007.
Arguments:
nClusters (Integer):
Number of clusters.
init (Integer, default: 0):
Initialization method to use.0 = random, 1 = k-means++, 2 = canopy, 3 = farthest first.
canopies (Boolean, default: false):
Use canopies to reduce the number of distance calculations.
maxCandidates