基于Sentinel-2A的孙吴地区土壤有机质反演研究
陈超群, 戴慧敏, 冯雨林, 杨泽, 杨佳佳

Sentinel-2A based inversion of the organic matter content of soil in the Sunwu area
CHEN Chao-Qun, DAI Hui-Min, FENG Yu-Lin, YANG Ze, YANG Jia-Jia
表4 基于PLSR模型的土壤有机质反演
Table 4 Inversion of soil organic matter by PLSR
数学
变换
拟合模型 建模集 测试集
R2 RMSE/% R2 RMSE/%


R y = 6.3252 - 0.1679 x 1 1 - 0.3836 x 2 - 0.4512 x 3 - 0.6285 x 4 - 0.6827 x 5 - 0.6340 x 6 + 0.5943 x 7 - 0.5943 x 8 - 0.5199 x 9 - 0.5565 x 10 0.0275 2.0263 0.0155 2.0925
1/R y = 5.2818 + 0.0001 x 1 + 0.000017 x 2 0.0439 1.9847 0.0657 2.0375
lgR y = 5.4429 - 0.5202 x 1 - 0.2827 x 2 + 1.1558 x 3 - 1.5976 x 4 - 0.5254 x 5 + 3.3470 x 6 0.0525 1.9757 0.0609 2.0406
Ra y = 6.0894 + 48.0295 x 1 - 110.9565 x 2 + 21.8818 x 3 + 78.5713 x 4 - 33.5780 x 5 - 10.4766 x 6 - 5.2279 x 7 0.0159 2.0136 0.0121 2.0917
FDR y=5.8376-23.9683x1+67.1411x2-63.9701x3+44.2371x4 0.0223 2.0071 0.0409 2.0632
SDR y = 6.1351 + 4.19 x 1 + 14.4844 x 2 + 59.2323 x 3 0.0200 2.0093 0.0238 2.0800
FDLR y = 5.0094 + 1.7352 x 1 - 6.2089 x 2 + 6.6447 x 3 - 5.4056 x 4 + 3.6822 x 5 - 11.4086 x 6 - 3.5433 x 7 - 3.0895 x 8 0.0524 1.9779 0.071 2.0366
组合 y = 8.8137 - 0.0162 x 1 + 1.7147 x 2 + 0.4484 x 3 - 0.1764 x 4 - 1.1268 x 5 - 0.4075 x 6 - 0.5233 x 7 - 1.5618 x 8 - 0.8610 x 9 - 1.2728 x 10 0.0434 1.9852 0.0400 1.9933



R y = 5.77391 - 8.6669 x 1 - 0.6491 x 2 + 9.5163 x 3 - 26.4628 x 4 + 8.9020 x 5 + 6.6144 x 6 0.0203 2.0318 0.0035 2.0539
1/R y = 5.80955 + 0.0002 x 1 + 0.0001 x 2 + 0.0009 x 3 - 0.1832 x 4 - 0.0226 x 5 + 0.2048 x 6 0.0234 2.2798 0.09 2.0390
lgR y = 4.40343 - 0.4786 x 1 - 0.0567 x 2 + 0.0415 x 3 + 0.0548 x 4 + 0.0692 x 5 + 0.0786 x 6 0.0480 2.0029 0.0408 2.0124
Ra y = 5.95664 - 0.4164 x 1 - 0.8538 x 2 - 2.1607 x 3 - 2.2302 x 4 - 2.3068 x 5 - 2.6665 x 6 0.0051 2.0475 0.0023 2.0525
FDR y = 5.65109 - 33.6899 x 1 + 85.8885 x 2 - 75.5978 x 3 - 13.8874 x 4 + 28.8994 x 5 - 6.2782 x 6 0.0365 2.0149 0.0207 2.0356
SDR y = 5.55202 + 13.2022 x 1 - 29.3378 x 2 + 42.5214 x 3 + 53.8592 x 4 - 3.5595 x 5 - 2.0586 x 6 0.0331 2.0496 0.0200 2.0520
FDLR y = 4.69522 - 0.0386 x 1 - 0.7984 x 2 - 0.6553 x 3 - 0.1570 x 4 - 0.0148 x 5 + 0.0701 x 6 0.0463 2.0046 0.0418 2.0118
组合 y = 1.2967 x 1 + 0.2947 x 2 + 2.6967 x 3 + 0.5528 x 4 + 0.8238 x 5 + 0.7684 x 6 - 0.2272 x 7 - 0.6389 x 8 + 1.0292 x 9 + 1.3686 x 10 - 1.8264 x 11 + 0.7614 x 12 - 0.1926 x 13 + 1.2489 x 14 - 0.1014 x 15 - 0.3382 x 16 + 0.9709 x 17 - 0.3017 x 18 + 1.5403 x 19 + 2.7079 x 20 + 0.0221 x 21 - 3.4156 x 22 + 3.8703 x 23 + 4.6421 x 24 - 0.5339 x 25 - 1.746 x 26 - 1.7177 0.0760 1.9518 0.0363 2.0183