激光与光电子学进展, 2019, 56 (5): 051101, 网络出版: 2019-07-31 复制并引用该论文  本文已被引 1 次  被引通知

图 & 表

图 1. 人类不同程度干扰下的土壤光谱曲线

Fig. 1. Soil spectral curves under different human disturbance degrees

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图 2. 土壤有机质含量与光谱反射率及其变换的相关性分析。(a) I区;(b) Ⅱ区;(c) Ⅲ区

Fig. 2. Correlation analysis among soil organic matter content, spectral reflectance, and its transformation. (a) Zone Ⅰ; (b) zone Ⅱ; (c) zone Ⅲ

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图 3. 轻度干扰区R小波系数与土壤有机质含量的相关系数图

Fig. 3. Correlation scalogram between R wavelet coefficient and soil organic matter content in mild disturbance zone

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图 4. 中度干扰区R小波系数与土壤有机质的相关系数图

Fig. 4. Correlation scalogram between R wavelet coefficient and soil organic matter in moderate disturbance zone

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图 5. 重度干扰区R小波系数与土壤有机质含量相关系数图

Fig. 5. Correlation scalogram between R wavelet coefficient and soil organic matter content in severe disturbance zone

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图 6. 土壤有机质预测值与实测值散点图。(a) Ⅰ区;(b) Ⅱ区;(c) Ⅲ区

Fig. 6. Scatter plots of predicted and measured values of soil organic matter. (a) Zone Ⅰ; (b) zone Ⅱ; (c) zone Ⅲ

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图 7. 土壤有机质含量实测值与预测值的Kriging插值图。(a) Ⅰ区;(b) Ⅱ区;(c) Ⅲ区

Fig. 7. Kriging interpolation plots of measured and predicted values of soil organic matter content. (a) Zone Ⅰ; (b) zone Ⅱ; (c) zone Ⅲ

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表 1研究区内3类典型干扰区基本情况

Table1. Basic status of three typical disturbance zones in study area

Type Disturbance intension Vegetation type Soil type Vegetation coverage /% Ⅰ Mild Native vegetation Sierozem soil ≥30 Ⅱ Moderate Native vegetation、cash crops Sierozem soil 15-30 Ⅲ Severe Cash crops、man-made forest Sierozem soil ≤15

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表 2土壤有机质含量的描述统计量

Table2. Descriptive statistics of soil organic matter content

Type Sampleset Number ofsamples Minimumvalue /(g·kg-1) Maximumvalue /(g·kg-1) Meanvalue /(g·kg-1) Standarddeviation /(g·kg-1) CV Ⅰ Whole set 30 6.507 14.707 10.257 2.004 0.195 Calibration set 18 7.952 14.17 10.344 1.753 0.169 Validation set 12 6.507 14.707 10.127 2.409 0.238 Ⅱ Whole set 30 6.182 15.221 8.939 2.284 0.255 Calibration set 18 6.786 14.797 8.658 1.884 0.218 Validation set 12 6.182 15.221 9.36 2.818 0.301 Ⅲ Whole set 30 3.619 13.107 7.977 2.297 0.288 Calibration set 18 3.619 12.133 7.483 1.935 0.259 Validation set 12 4.695 13.107 8.717 2.67 0.306

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表 3选择的敏感波长

Table3. Selection of sensitive wavelengths

Type Spectral transformation Sensitive bands /nm Ⅰ R 746,762,805,1818,1824 R′ 619,645,715,1467,2270 lg(1/R) 699,762,781,800,1824 Ⅱ R 436,450,508,522,545 R′ 407,426,1100,1634,2417 lg(1/R) 434,453,500,523,534 Ⅲ R 536,1192,1254,1300,1555 R′ 418,860,1156,1822,2329 lg(1/R) 536,1192,1244,1256,1300

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表 4土壤有机质含量反演模型的建模集与验证集结果

Table4. Calibration and validation results of inversion model for soil organic matter content

Type Model Calibration set Validation set R2 RRMSE R2 RRMSE RRPD Ⅰ R 0.372 1.350 0.335 2.391 1.183 R′ 0.695 0.908 0.628 1.589 1.873 lg(1/R) 0.441 1.273 0.486 1.718 1.352 CWT 0.752 0.848 0.717 1.132 2.150 Ⅱ R 0.274 1.561 0.289 2.396 0.872 R′ 0.668 1.102 0.616 1.812 1.671 lg(1/R) 0.368 1.336 0.421 2.350 1.207 CWT 0.706 0.914 0.689 1.709 2.090 Ⅲ R 0.245 1.474 0.214 2.491 0.944 R′ 0.624 1.040 0.582 2.074 1.548 lg(1/R) 0.289 1.397 0.270 3.443 0.609 CWT 0.652 1.135 0.630 1.985 2.013

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叶红云, 熊黑钢, 张芳, 王宁, 马利芳. 基于CWT的人类不同程度干扰下干旱区土壤有机质含量估算研究[J]. 激光与光电子学进展, 2019, 56(5): 051101. Hongyun Ye, Heigang Xiong, Fang Zhang, Ning Wang, Lifang Ma. CWT-Based Estimation of Soil Organic Matter Content in Arid Area Under Different Human Disturbance Degrees[J]. Laser & Optoelectronics Progress, 2019, 56(5): 051101.