地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (9): 1799-1813.doi: 10.12082/dqxxkx.2020.190441
刘明杰1,2(), 徐卓揆1,3, 郜允兵2,4,*(
), 杨晶2,4, 潘瑜春2,4, 高秉博5, 周艳兵2,4, 周万鹏2,6, 王凌7
收稿日期:
2019-08-13
修回日期:
2019-12-14
出版日期:
2020-09-25
发布日期:
2020-11-25
通讯作者:
郜允兵
E-mail:2210478688@qq.com;gybgis@163.com
作者简介:
刘明杰(1995— ),男,贵州贵阳人,硕士生,研究方向为地理信息系统。E-mail:基金资助:
LIU Mingjie1,2(), XU Zhuokui1,3, GAO Yunbing2,4,*(
), YANG Jing2,4, PAN Yuchun2,4, GAO Bingbo5, ZHOU Yanbing2,4, ZHOU Wanpeng2,6, WANG Ling7
Received:
2019-08-13
Revised:
2019-12-14
Online:
2020-09-25
Published:
2020-11-25
Contact:
GAO Yunbing
E-mail:2210478688@qq.com;gybgis@163.com
Supported by:
摘要:
采用GRNN(Generalized Regression Neural Network)和RF(Random Forest)2种机器学习方法构建土壤有机质预测模型,以提高稀疏样本情况下的土壤有机质估算精度。依据北京市大兴区农用地2007年的土壤有机质采样数据,按MMSD准则(Minimization of the Mean of the Shortest Distances)抽稀为8种不同采样密度的样本(分别为2703、1352、676、339、169、85、43、22个样本),分别采用GRNN、RF和Ordinary kriging对各采样密度下的未知采样点进行预测,采用交叉检验的方式验证各采样密度下未知样点的预测精度。随着采样点密度的下降,样点间的空间自相关性逐渐减弱,半变异函数的拟和精度变差,预测点结果误差增大,预测的置信度降低。当抽稀到43个和22个采样点时,样点间的空间自相关性接近歼灭,半变异函数的决定系数较低且残差较大。普通克里格受到采样点数量和采样密度、样点的空间结构的影响比较明显,其预测精度随采样点数量的下降而下降。在85个采样点及以下时,其预测值与观测值之间没有显著的相关性。GRNN和RF的预测精度受采样密度的影响不大,其预测精度在一个较小的范围内波动,其预测值围绕观测值在一定阈值空间内震荡波动,具有较好的相关性,在85个及以下的采样密度时,预测精度相对普通克里格有较大的提升。普通克里格法不适合在稀疏样本条件下空间插值计算,尤其是在空间自相关性比较弱的情况下。机器学习模型能充分学习土壤间环境信息、样点空间邻近效应信息,兼顾属性相似性和空间自相关,具有更好的稳定性和适应性,不容易受到采样点数量、构型和采样密度等因素的影响,即使在采样点空间自相关性很弱的情况下也能做出稳定预测精度。
刘明杰, 徐卓揆, 郜允兵, 杨晶, 潘瑜春, 高秉博, 周艳兵, 周万鹏, 王凌. 基于机器学习的稀疏样本下的土壤有机质估算方法[J]. 地球信息科学学报, 2020, 22(9): 1799-1813.DOI:10.12082/dqxxkx.2020.190441
LIU Mingjie, XU Zhuokui, GAO Yunbing, YANG Jing, PAN Yuchun, GAO Bingbo, ZHOU Yanbing, ZHOU Wanpeng, WANG Ling. Estimating Soil Organic Matter based on Machine Learning Under Sparse Sample[J]. Journal of Geo-information Science, 2020, 22(9): 1799-1813.DOI:10.12082/dqxxkx.2020.190441
表1
土壤有机质含量方差分析"
方差来源 | 偏差平方和 | 自由度Df | 均方 | F | P | |
---|---|---|---|---|---|---|
用地类型 | 组间 | 351.750 | 4 | 87.938 | 6.871 | 0.000 |
组内 | 1023.868 | 80 | 12.796 | |||
总体 | 1375.618 | 84 | ||||
土壤质地 | 组间 | 356.405 | 3 | 118.802 | 9.442 | 0.000 |
组内 | 1019.213 | 81 | 12.583 | |||
总体 | 1375.618 | 84 | ||||
畜禽粪便利用强度 | 组间 | 241.351 | 5 | 48.270 | 3.362 | 0.008 |
组内 | 1134.267 | 79 | 14.358 | |||
总体 | 1375.618 | 84 | ||||
土壤类型 | 组间 | 0.945 | 2 | 0.472 | 0.028 | 0.972 |
组内 | 1374.674 | 82 | 16.764 | |||
总体 | 1375.618 | 84 | ||||
植被指数 | 组间 | 17.592 | 2 | 8.796 | 0.531 | 0.590 |
组内 | 1358.027 | 82 | 16.561 | |||
总体 | 1375.618 | 84 |
表2
研究区所有实验组土壤有机质含量描述性统计"
实验组 | 极大值/ (g/kg) | 极小值/ (g/kg) | 平均值/ (g/kg) | 标准差/ (g/kg) | 变异 系数 | 偏度 | 峰度 | K-S双侧 显著性 |
---|---|---|---|---|---|---|---|---|
D2703 | 24.73 | 1.20 | 10.49 | 3.91 | 37.28 | 0.147 | -0.098 | 0.302 |
D1352 | 24.73 | 1.65 | 10.53 | 3.92 | 37.23 | 0.159 | -0.003 | 0.632 |
D676 | 24.73 | 1.65 | 10.58 | 4.11 | 38.87 | 0.318 | 0.036 | 0.640 |
D339 | 24.73 | 1.81 | 10.55 | 3.94 | 37.32 | 0.223 | 0.292 | 0.946 |
D169 | 22.98 | 1.98 | 10.20 | 3.99 | 39.08 | 0.290 | 0.112 | 0.964 |
D85 | 18.05 | 2.03 | 10.93 | 4.05 | 37.01 | -0.181 | -0.804 | 0.934 |
D43_1 | 17.97 | 4.35 | 11.07 | 3.46 | 31.24 | -0.187 | -0.616 | 0.972 |
D43_2 | 17.73 | 2.98 | 10.07 | 4.17 | 41.39 | 0.122 | -0.893 | 0.951 |
D43_3 | 17.84 | 3.53 | 11.10 | 3.53 | 31.80 | -0.091 | -0.900 | 0.855 |
D43_4 | 19.67 | 2.02 | 10.33 | 4.04 | 39.13 | 0.128 | -0.064 | 0.906 |
D43_5 | 17.68 | 2.19 | 10.39 | 4.46 | 42.90 | -0.329 | -0.998 | 0.445 |
D22_1 | 18.28 | 3.53 | 10.70 | 4.30 | 40.13 | 0.293 | -0.988 | 0.611 |
D22_2 | 17.61 | 3.91 | 11.28 | 3.84 | 34.03 | -0.037 | -0.634 | 0.940 |
D22_3 | 16.40 | 3.72 | 10.49 | 3.60 | 34.29 | -0.380 | -0.692 | 0.783 |
D22_4 | 15.34 | 4.29 | 10.56 | 3.24 | 30.72 | -0.320 | -0.825 | 0.912 |
D22_5 | 17.86 | 2.36 | 9.35 | 4.36 | 46.60 | 0.260 | -0.540 | 0.999 |
表4
所有实验组GRNN、RF和普通克里格法的预测精度"
实验组 | RMSE | MRE/% | MAE | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Krige | GRNN | RF | Krige | GRNN | RF | Krige | GRNN | RF | |||
D2703 | 2.82 | 3.11 | 2.99 | 26.89 | 29.59 | 28.92 | 2.21 | 2.43 | 2.35 | ||
D1352 | 3.02 | 3.17 | 3.01 | 29.54 | 30.28 | 29.50 | 3.02 | 2.46 | 2.36 | ||
D676 | 3.45 | 3.34 | 3.23 | 33.00 | 31.94 | 30.50 | 2.74 | 2.65 | 2.57 | ||
D339 | 3.38 | 3.17 | 3.17 | 35.60 | 30.64 | 31.19 | 2.82 | 2.47 | 2.53 | ||
D169 | 3.55 | 3.41 | 3.31 | 35.92 | 36.64 | 34.39 | 2.83 | 2.75 | 2.61 | ||
D85 | 4.10 | 3.17 | 2.96 | 43.76 | 33.37 | 30.45 | 3.47 | 2.72 | 2.46 | ||
D43_1 | 3.36 | 2.84 | 2.72 | 30.40 | 25.63 | 23.73 | 2.74 | 2.31 | 2.18 | ||
D43_2 | 4.13 | 3.19 | 3.11 | 44.58 | 34.52 | 33.70 | 3.34 | 2.70 | 2.65 | ||
D43_3 | 3.68 | 3.14 | 3.31 | 35.53 | 30.26 | 31.93 | 3.17 | 2.67 | 2.91 | ||
D43_4 | 3.95 | 2.76 | 3.18 | 44.86 | 33.59 | 37.36 | 3.21 | 2.36 | 2.69 | ||
D43_5 | 4.69 | 3.42 | 3.61 | 67.44 | 38.46 | 47.36 | 4.06 | 2.70 | 3.01 | ||
D22_1 | 4.34 | 3.22 | 3.42 | 43.60 | 35.06 | 33.76 | 3.77 | 2.86 | 2.91 | ||
D22_2 | 4.31 | 2.43 | 2.62 | 65.64 | 24.60 | 26.55 | 3.83 | 2.13 | 2.28 | ||
D22_3 | 3.90 | 2.89 | 3.07 | 77.11 | 27.63 | 33.04 | 3.54 | 2.27 | 2.64 | ||
D22_4 | 3.53 | 2.56 | 2.86 | 58.38 | 23.23 | 27.42 | 3.03 | 2.18 | 2.45 | ||
D22_5 | 4.31 | 2.98 | 2.98 | 146.35 | 35.83 | 41.13 | 3.79 | 2.44 | 2.55 |
表5
所有实验组样本的空间自相关分析"
实验组 | 平均最短距离/m | Moran's I值 | Z得分 | P值 | 实验组 | 平均最短距离/m | Moran's I值 | Z得分 | P值 |
---|---|---|---|---|---|---|---|---|---|
D2703 | 371.45 | 0.35 | 56.78 | 0.00 | D43_3* | 2615.74 | 0.15 | 1.15 | 0.25 |
D1352 | 425.63 | 0.33 | 30.83 | 0.00 | D43_4* | 3109.01 | 0.15 | 1.30 | 0.19 |
D676 | 567.68 | 0.33 | 14.99 | 0.00 | D43_5* | 2909.11 | 0.08 | 0.83 | 0.41 |
D339 | 810.79 | 0.20 | 8.24 | 0.00 | D22_1* | 4237.90 | -0.32 | -1.39 | 0.17 |
D169 | 1285.91 | 0.17 | 5.68 | 0.00 | D22_2* | 4384.49 | -0.15 | -0.53 | 0.60 |
D85 | 1914.45 | 0.19 | 3.06 | 0.00 | D22_3* | 3662.95 | -0.10 | -0.19 | 0.85 |
D43_1 | 2792.95 | 0.22 | 2.41 | 0.02 | D22_4* | 4342.87 | 0.10 | 0.74 | 0.46 |
D43_2 | 3110.80 | 0.14 | 1.52 | 0.13 | D22_5* | 4723.02 | -0.11 | -0.48 | 0.63 |
表6
3种土壤有机质影响因素探测结果"
实验组 | 土地利用类型 | 土壤质地 | 畜禽粪便影响强度 | |||||
---|---|---|---|---|---|---|---|---|
q值 | p值 | q值 | p值 | q值 | p值 | |||
D2703 | 0.182 | 0.000 | 0.199 | 0.000 | 0.148 | 0.000 | ||
D1352 | 0.209 | 0.000 | 0.190 | 0.000 | 0.139 | 0.000 | ||
D676 | 0.198 | 0.000 | 0.233 | 0.000 | 0.171 | 0.000 | ||
D339 | 0.212 | 0.000 | 0.189 | 0.000 | 0.138 | 0.000 | ||
D169 | 0.210 | 0.000 | 0.229 | 0.000 | 0.202 | 0.000 | ||
D85 | 0.256 | 0.067 | 0.259 | 0.016 | 0.175 | 0.035 | ||
D43 | 0.500 | 0.004 | 0.177 | 0.071 | 0.345 | 0.050 | ||
D22 | 0.496 | 0.016 | 0.477 | 0.049 | 0.742 | 0.034 |
表7
GRNN、RF和普通克里格法的预测值与观测值的相关性分析"
实验组 | Krige | GRNN | RF | 实验组 | Krige | GRNN | RF |
---|---|---|---|---|---|---|---|
D2703 | 0.686** | 0.608** | 0.642** | D43_3 | 0.155 | 0.388* | 0.392** |
D1352 | 0.635** | 0.590** | 0.637** | D43_4 | 0.153 | 0.669** | 0.576** |
D676 | 0.543** | 0.581** | 0.616** | D43_5 | -0.067 | 0.591** | 0.577** |
D339 | 0.450** | 0.580** | 0.578** | D22_1 | -0.137 | 0.572** | 0.590** |
D169 | 0.433** | 0.500** | 0.545** | D22_2 | -0.343 | 0.709** | 0.630** |
D85 | 0.175 | 0.599** | 0.660** | D22_3 | -0.094 | 0.584** | 0.440* |
D43_1 | 0.210 | 0.532** | 0.594** | D22_4 | -0.102 | 0.547** | 0.398* |
D43_2 | 0.129 | 0.559** | 0.627** | D22_5 | 0.054 | 0.635** | 0.762** |
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