基于物候相机归一化植被指数估算高寒草地植物地上生物量的季节动态

陈哲, 汪浩, 王金洲, 石慧瑾, 刘慧颖, 贺金生

Estimation on seasonal dynamics of alpine grassland aboveground biomass using phenology camera-derived NDVI

CHEN Zhe, WANG Hao, WANG Jin-Zhou, SHI Hui-Jin, LIU Hui-Ying, HE Jin-Sheng

表2 2018和2019年生长季高寒草地手持式植物冠层光谱仪测量的归一化植被指数(NDVIRS)(x)与地上生物量(y)之间的经验模型构建

Table 2 Fitted regression equations between normalized difference of vegetation index measured by RapidSCAN (NDVIRS)(x) and aboveground biomass (y) of alpine grassland across the growing seasons of 2018 and 2019

月份 Month 模型 Model 回归方程 Regression equation R2 RMSE RMSEr (%) 5月 May (n = 56) 线性 Linear y = 397.3x - 130.6 0.67 13.62 25.38 对数 Logarithm y = 186.0ln(x) + 198.3 0.65 14.32 26.68 指数 Exponent y = 2.0e6.9x 0.65 13.03 24.28 乘幂 Power y = 615.1x3.3 0.67 12.45 23.19 多项式 Quadratic y = 491.7x2 - 83.7x - 14.7 0.65 12.88 24.00 6月 June (n = 34) 线性 Linear y = 1080.5x - 595.7 0.75 24.99 21.12 对数 Logarithm y = 730.4ln(x) + 423.1 0.73 26.82 22.66 指数 Exponent y = 0.7e7.7x 0.74 22.25 18.80 乘幂 Power y = 939.7x5.2 0.74 21.95 18.55 多项式 Quadratic y = 3363.7x2 - 3537.5x + 979.2 0.77 20.04 16.94 7月 July (n = 64) 线性 Linear y = 952.0x - 508.5 0.72 39.94 18.54 对数 Logarithm y = 730.2ln(x) + 416.7 0.71 40.35 18.73 指数 Exponent y = 8.4e4.2x 0.73 38.00 17.64 乘幂 Power y = 517.6x3.3 0.73 37.65 17.48 多项式 Quadratic y = 1422.3x2 - 1248.1x + 339.51 0.72 38.95 18.08 8月 August (n = 51) 线性 Linear y = 532.0x - 105.1 0.18 38.72 13.43 对数 Logarithm y = 375.4ln(x) + 403.0 0.16 39.01 13.53 指数 Exponent y = 81.9e1.7x 0.16 34.73 12.04 乘幂 Power y = 402.3x1.2 0.14 35.28 12.23 多项式 Quadratic y = 5968.0x2 - 8287.3x + 3134.3 0.29 31.70 10.99 9月 September (n = 63) 线性 Linear y = 507.3x - 85.5 0.61 38.17 19.30 对数 Logarithm y = 292.5ln(x) + 371.7 0.61 38.18 19.31 指数 Exponent y = 48.0e2.5x 0.62 37.92 19.18 乘幂 Power y = 448.2x1.4 0.63 37.68 19.06 多项式 Quadratic y = -48.0x2 + 563.9x - 101.8 0.61 37.87 19.15