基于多源数据及三层模型的小班林型识别

黄健, 吴达胜, 方陆明

Identification of sub-compartment forest type based on multi-source data and three-tier models

HUANG Jian, WU Dasheng, FANG Luming

表6 基于LightGBM-4及3种雷达遥感因子及特征选择方案的建模精度对比

Table 6 Accuracy comparison based on the LightGBM-4 and the three schemes with remote sensing factors and feature selection

林型 forest type 雷达遥感因子及特征选择方案 radar remote sensing factor and feature selection scheme 方案A plan A 方案B plan B 方案C plan C 用户精度/% UA 生产者精度/% PA 用户精度/% UA 生产者精度/% PA 用户精度/% UA 生产者精度/% PA 山核桃林 Carya cathayensis forest 91.87 92.93 92.32 93.24 92.32 93.05 阔叶混交林 broad-leaved mixed forest 63.36 59.96 62.93 59.79 63.22 58.97 其他硬阔林 other hard broad-leaved forest 60.43 63.00 59.97 63.34 57.97 62.27 杉木林 Cunninghamia lanceolata forest 85.93 81.79 86.28 81.82 86.42 81.47 毛竹林 Phyllosstachys edulis forest 94.86 94.32 94.46 94.19 95.03 93.83 茶树林 Camellia sinensis forest 92.27 92.27 92.76 93.03 92.15 93.31 马尾松林 Pinus massoniana forest 69.77 75.51 69.94 75.79 69.14 75.86 总体精度/% OA 83.08 83.21 82.91 Kappa系数 0.80 0.80 0.80