基于均值置信区间带的高光谱特征波段选择与树种识别

以柏木、雷竹和无患子野外高光谱数据为基础,在统计学理论和实践分析的基础上,提出了利用均值置信区间带筛选树种间最佳特征区分波段及利用Manhattan距离和Min-Max区间相似度识别树种的问题。研究结果表明:(1)柏木与雷竹之间的最佳区分波段为358～386,452～1 145和1 314～2 500 nm,柏木与无患子之间的最佳区分波段为350～446,497～527,553～1 330,1 355～2 400和2 436～2 500 nm,雷竹与无患子之间的最佳区分波段为434～555,580～1 903,1 914～2 089,2 172～2 457和2 475～2 500 nm;(2)在最佳区分波段内,同种树种间的Manhattan距离远小于异种树种间的Manhattan距离,同种树种间的Min～Max区间相似度远大于异种树种间的Min～Max区间相似度,Manhattan距离和Min～Max区间相似度可以有效区分和识别不同类型的树种。

Hyperspectral feature band selection based on mean confidence interval and tree species discrimination

In the present study, based on the leaf-level hyperspectral data of BaiMu, LeiZhu and WuHuanZi, the authors come up with two solutions through the theory of statistics; the first one is that optimal discriminating band between tree species is extracted by mean interval confidence, the other one is that tree species is discriminated by the Manhattan distance and the Min Max interval similarity. The research results showed that (1) the optimal discriminating bands between BaiMu and LeiZhu are around 350-446, 497-527, 553-1 330, 1 355-2 400 and 2 436-2 500 nm; the optimal discriminating bands between BaiMu and WuHuanZi are around 434-555, 580-1 903, 1 914-2 089, 2 172-2 457 and 2 475-2 500 nm; the optimal discriminating bands between LeiZhu and WuHuanZi are around 434-555, 580-1 903, 1 914-2 089, 2 172-2 457 and 2 475-2 500 nm; and this result is helpful for us to find maximum difference to identifying tree species respectively. (2) In these optimal discriminating bands, we find that the Manhattan distance between the same species is far less than the different species; but the Min-Max interval similarity between the same species is far more than the different species, so this result could help us to discriminate and identify different types of tree species effectively.