Estimating Soil Organic Matter based on Machine Learning Under Sparse Sample

Mingjie LIU; Zhuokui XU; Yunbing GAO; Jing YANG; Yuchun PAN; Bingbo GAO; Yanbing ZHOU; Wanpeng ZHOU; Ling WANG

doi:10.12082/dqxxkx.2020.190441

[1] OndrasekG, Baki?Begi? H, ZovkoM et al. Biogeochemistry of soil organic matter in agroecosystems & environmental implications[J]. Science of The Total Environment, 658, 1559-1573(2019).

[2] 徐云鹤, 方斌. 江浙典型茶园土壤有机质空间异质性分析[J]. 地球信息科学学报, 2015,17(5):622-630. [ XuY H, FangB. Study on spatial heterogeneity of the soil organic matter in typical tea gardens of Jiangsu Province and Zhejiang Province[J]. Journal of Geo-information Science, 2015,17(5):622-630. ] [ Xu Y H, Fang B. Study on spatial heterogeneity of the soil organic matter in typical tea gardens of Jiangsu Province and Zhejiang Province[J]. Journal of Geo-information Science,2015,17(5):622-630. ]

[3] 陈桂香, 高灯州, 曾从盛, 等. 福州市农田土壤养分空间变异特征[J]. 地球信息科学学报, 2017,19(2):216-224. [ ChenG X, GaoD Z. Characteristics of the spatial variation of soil nutrients in farmland of Fuzhou City[J]. Journal of Geo-information Science, 2017,19(2):216-224. ] [ Chen G X, Gao D Z. Characteristics of the spatial variation of soil nutrients in farmland of Fuzhou City[J]. Journal of Geo-information Science, 2017,19(2):216-224. ]

[4] WiesmeierM, UrbanskiL, HobleyE et al. Soil organic carbon storage as a key function of soils - A review of drivers and indicators at various scales[J]. Geoderma, 333, 149-162(2019).

[5] GuoZ, AdhikariK, ChellasamyM et al. Selection of terrain attributes and its scale dependency on soil organic carbon prediction[J]. Geoderma, 340, 303-312(2019).

[6] 黄昌勇, 徐建明. 土壤学(第三版)[M]. 北京: 中国农业出版社, 2010: 29-43[ HuangC Y, XuJ M. Soil Science(3rd edition)[M]. Beijing: China Agricultural Press, 2010: 29-43. ] [ Huang C Y, Xu J M. Soil Science (3rd edition)[M]. Beijing: China Agricultural Press, 2010:29-43. ]

[7] PaulE A. The nature and dynamics of soil organic matter: Plant inputs, microbial transformations, and organic matter stabilization[J]. Soil Biology and Biochemistry, 98, 109-126(2016).

[8] KhanK S, MackR, CastilloX et al. Microbial biomass, fungal and bacterial residues, and their relationships to the soil organic matter C/N/P/S ratios[J]. Geoderma, 271, 115-123(2016).

[9] TuC, HeT, LuX et al. Extent to which pH and topographic factors control soil organic carbon level in dry farming cropland soils of the mountainous region of Southwest China[J]. CATENA, 163, 204-209(2018).

[10] SunW, ZhuH, GuoS. Soil organic carbon as a function of land use and topography on the Loess Plateau of China[J]. Ecological Engineering, 83, 249-257(2015).

[11] 杨晓. 县域土壤有机质空间分布研究——以山东省诸城市为例[D]. 济南:山东农业大学, 2018. [ YangX, Study on spatial distribution of soil organic matter in the county area: A case study of Zhucheng City, Shandong Province[D]. Jinan: Shandong Agricultural University, 2018. ] [ Yang X, Study on spatial distribution of soil organic matter in the county area: A case study of Zhucheng City, Shandong Province[D]. Jinan: Shandong Agricultural University, 2018. ]

[12] 高凤杰, 马泉来, 韩文文, 等. 黑土丘陵区小流域土壤有机质空间变异及分布格局[J]. 环境科学, 2016,37(5):1915-1922. [ GaoF J, MaQ L, HanW W, et al. Spatial variability and distribution pattern of soil organic matter in a mollisol watershed of China[J]. Environmental Science, 2016,37(5):1915-1922. ] [ Gao F J, Ma Q L, Han W W, et al. Spatial variability and distribution pattern of soil organic matter in a mollisol watershed of China[J]. Environmental Science, 2016,37(5):1915-1922. ]

[13] 宋莎, 李廷轩, 王永东, 等. 县域农田土壤有机质空间变异及其影响因素分析[J]. 土壤, 2011,43(1):44-49. [ SongS, LiT X, WangY D, et al. Spatial variability of soil organic matter and its influencing factors at county scales[J]. Soils, 2011,43(1):44-49. ] [ Song S, Li T X, Wang Y D, et al. Spatial variability of soil organic matter and its influencing factors at county scales[J]. Soils, 2011,43(1):44-49. ]

[14] 王宗明, 张柏, 宋开山, 等. 东北平原典型农业县农田土壤养分空间分布影响因素分析[J]. 水土保持学报, 2007(2):73-77.

[15] 孔祥斌, 张凤荣, 王茹. 近20年城乡交错带土壤养分时间空间变异特征分析——以北京市大兴区为例[J]. 土壤, 2004(6):636-643. [ KongX B, ZhangF R, WangR. Spatial and temporal variation of soil nutrients in periurban region: A case study of Daxing County in Beijing City[J]. Soils, 2004(6):636-643. ] [ Kong X B, Zhang F R, Wang R. Spatial and temporal variation of soil nutrients in periurban region: A case study of Daxing County in Beijing City[J]. Soils, 2004(6):636-643. ]

[16] 秦静, 孔祥斌, 姜广辉, 等. 北京典型边缘区25年来土壤有机质的时空变异特征[J]. 农业工程学报, 2008,24(3):124-129. [ QinJ, KongX B, JiangG H, et al. Characteristics of spatio-temporal changes of soil organic matter in typical fringe in Beijing for 25 years[J]. Transactions of the Chinese Society of Agricultural Engineering, 2008,24(3):124-129. ] [ Qin J, Kong X B, Jiang G H, et al. Characteristics of spatio-temporal changes of soil organic matter in typical fringe in Beijing for 25 years[J]. Transactions of the Chinese Society of Agricultural Engineering, 2008,24(3):124-129. ]

[17] 胡克林, 余艳, 张凤荣, 等. 北京郊区土壤有机质含量的时空变异及其影响因素[J]. 中国农业科学, 2006,38(4):764-771. [ HuK L, YuY, ZhangF R, et al. The Spatial-Temporal variability of soil organic matter and its influencing factors in suburban area of Beijing[J]. Scientia Agricultura Sinica, 2006,38(4):764-771. ] [ Hu K L, Yu Y, Zhang F R, et al. The Spatial-Temporal variability of soil organic matter and its influencing factors in suburban area of Beijing[J]. Scientia Agricultura Sinica, 2006,38(4):764-771. ]

[18] 赵汝东, 孙焱鑫, 王殿武, 等. 北京地区耕地土壤有机质空间变异分析[J]. 土壤通报, 2010,41(3):552-557. [ ZhaoR D, SunY X, WangD Y, et al. Research on spatial variability of soil organic matter in Beijng field[J]. Chinese Journal of Soil Science, 2006(4):764-771. ] [ Zhao R D, Sun Y X, Wang D Y, et al. Research on spatial variability of soil organic matter in Beijng field[J]. Chinese Journal of Soil Science, 2006(4):764-771. ]

[19] 李启权, 王昌全, 岳天祥, 等. 基于神经网络模型的中国表层土壤有机质空间分布模拟方法[J]. 地球科学进展, 2012,27(2):175-184.

[20] 李启权, 王昌全, 张文江, 等. 基于神经网络模型和地统计学方法的土壤养分空间分布预测[J]. 应用生态学报, 2013,24(2):459-466.

[21] 江叶枫, 郭熙, 叶英聪, 等. 应用集成BP神经网络模型预测土壤有机质空间分布[J]. 江苏农业学报, 2017,33(5):1044-1050. [ JiangY F, GuoZ, YeY C, et al. Spatial distribution of soil organic matter predicted by BP neural network ensemble model[J]. Jiangsu Journal of Agricultural Sciences, 2017,33(5):1044-1050. ] [ Jiang Y F, Guo Z, Ye Y C, et al. Spatial distribution of soil organic matter predicted by BP neural network ensemble model[J]. Jiangsu Journal of Agricultural Sciences, 2017,33(5):1044-1050. ]

[22] 江叶枫, 郭熙. 基于辅助变量和回归径向基函数神经网络(R-R BFNN)的土壤有机质空间分布模拟[J]. 浙江农业学报, 2018,30(4):640-648. [ JiangY F, GuoZ. Prediction of soil organic matter distribution based on auxiliary variables and regression-radial basis function neural network (R-RBFNN) model[J]. Acta Agriculturae Zhejiangensis, 2018,30(4):640-648. ] [ Jiang Y F, Guo Z. Prediction of soil organic matter distribution based on auxiliary variables and regression-radial basis function neural network (R-RBFNN) model[J]. Acta Agriculturae Zhejiangensis, 2018,30(4):640-648. ]

[23] 江叶枫, 郭熙, 叶英聪, 等. 省域尺度土壤有机质空间分布的神经网络法预测[J]. 江苏农业学报, 2017,33(4):828-835. [ JiangY F, GuoZ, YeY C, et al. Prediction of spatial distribution of soil organic matter at provincial scale with neural network[J]. Jiangsu Journal of Agricultural Sciences, 2017,33(4):828-835. ] [ Jiang Y F, Guo Z, Ye Y C, et al. Prediction of spatial distribution of soil organic matter at provincial scale with neural network[J]. Jiangsu Journal of Agricultural Sciences, 2017,33(4):828-835. ]

[24] PouladiN, M?llerA B, TabatabaiS et al. Mapping soil organic matter contents at field level with Cubist, Random Forest and Krige[J]. Geoderma, 342, 85-92(2019).

[25] 宋英强, 杨联安, 冯武焕, 等. 基于多源辅助变量和极限学习机的蔬菜地土壤有机质预测研究[J]. 土壤通报, 2017,48(1):118-126. [ SongY Q, YangL A, FengW H, et al. Prediction for soil organic matter in vegetable fields based on cooperative variables and extreme learning machine algorithm[J]. Chinese Journal of Soil Science, 2017,48(1):118-126. ] [ Song Y Q, Yang L A, Feng W H, et al. Prediction for soil organic matter in vegetable fields based on cooperative variables and extreme learning machine algorithm[J]. Chinese Journal of Soil Science, 2017,48(1):118-126. ]

[26] ZeraatpishehM, AyoubiS, JafariA et al. Digital mapping of soil properties using multiple machine learning in a semi-arid region, central Iran[J]. Geoderma, 338, 445-452(2019).

[27] FengY, CuiN, HaoW et al. Estimation of soil temperature from meteorological data using different machine learning models[J]. Geoderma, 338, 67-77(2019).

[28] 何勇, 张淑娟, 方慧. 基于人工神经网络的田间信息插值方法研究[J]. 农业工程学报, 2004,20(3):120-123. [ HeY, ZhangS J, FangH. Interpolation method of field information based on the artificial neural network[J]. Transactions of The Chinese Society of Agricultural Engineering, 2004,20(3):120-123. ] [ He Y, Zhang S J, Fang H. Interpolation method of field information based on the artificial neural network[J]. Transactions of The Chinese Society of Agricultural Engineering, 2004,20(3):120-123. ]

[29] ChenD, ChangN, XiaoJ et al. Mapping dynamics of soil organic matter in croplands with MODIS data and machine learning algorithms[J]. Science of The Total Environment, 669, 844-855(2019).

[30] RansomK M, NolanB T, A.Traum J et al. A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA[J]. Science of The Total Environment, 602, 1160-1172(2017).

[31] KnollL, BreuerL, BachM. Large scale prediction of groundwater nitrate concentrations from spatial data using machine learning[J]. Science of The Total Environment, 668, 1317-1327(2019).

[32] SaurabhDas, RohitChakraborty, AnimeshMaitra. A random forest algorithm for nowcasting of intense precipitation events[J]. Advances in Space Research, 60, 1271-1282(2017).

[33] BonelliM G, FerriniM, ManniA. Artificial neural networks to evaluate organic and inorganic contamination in agricultural soils[J]. Chemosphere, 186, 124-131(2017).

[34] 侯艺璇, 赵华甫, 吴克宁, 等. 基于BP神经网络的作物Cd含量预测及安全种植分区[J]. 资源科学, 2018,40(12):2414-2424. [ HouY X, ZhaoH N, WuK N, et al. Prediction of crop Cd content and zoning of safety planting based on BP neural network[J]. Resources Science, 2018,40(12):2414-2424. ] [ Hou Y X, Zhao H N, Wu K N, et al. Prediction of crop Cd content and zoning of safety planting based on BP neural network[J]. Resources Science, 2018,40(12):2414-2424. ]

[35] KhosraviV, DoulatiArdejani F, YousefiS et al. Monitoring soil lead and zinc contents via combination of spectroscopy with extreme learning machine and other data mining methods[J]. Geoderma, 318, 29-41(2018).

[36] GB 9834-88.土壤有机质测定法[S]. [ GB 9834-88. Method for determination of soil organic matter[S]. ]

[37] DaiW, HuangY. Relation of soil organic matter concentration to climate and altitude in zonal soils of China[J]. Catena, 65, 87-94(2006).

[38] SarkarS, RoyA K, MarthaT R. Soil depth estimation through soil-landscape modelling using regression kriging in a Himalayan terrain[J]. International Journal of Geographical Information Science, 27, 2436-2454(2013).

[39] 许信旺. 不同尺度区域农田土壤有机碳分布与变化[D]. 南京:南京农业大学, 2008. [ XuX W, Regional distribution and variation of SOC storage in agricultural soils at different scales[D]. Nanjing Agricultural University, 2008. ] [ Xu X W, Regional distribution and variation of SOC storage in agricultural soils at different scales[D]. Nanjing Agricultural University,2008. ]

[40] 高凤杰, 吴啸, 师华定, 等. 基于贝叶斯最大熵的黑土区小流域土壤有机质空间预测[J]. 环境科学研究, 2019,32(8):1365-1373. [ GaoF J, WuX, ShiH D, et al. Prediction of spatial distribution of soil organic matter in a mollisol watershed of China based on BME method[J/OL]. Research of Environmental Sciences, 2019,32(8):1365-1373. ] [ Gao F J, Wu X, Shi H D, et al. Prediction of spatial distribution of soil organic matter in a mollisol watershed of China based on BME method[J/OL]. Research of Environmental Sciences, 2019,32(8):1365-1373. ]

[41] GB 18596-2001.畜禽养殖业污染物排放标准[S]. [ GB 18596-2001. Discharge standard of pollutants for livestock and poultry breeding[S]. ] [GB 18596-2001. Discharge standard of pollutants for livestock and poultry breeding[S]. ]

[42] 李帷, 李艳霞, 杨明, 等. 北京市畜禽养殖的空间分布特征及其粪便耕地施用的可达性[J]. 自然资源学报, 2010,25(5):746-755. [ LiW, LiY X, YangM, et al. Spatial distribution of livestock and poultry production and land application accessibility of animal manure in Beijing[J]. Journal of Natural Resources, 2010,25(5):746-755. ] [ Li W, Li Y X, Yang M, et al. Spatial distribution of livestock and poultry production and land application accessibility of animal manure in Beijing[J]. Journal of Natural Resources, 2010,25(5):746-755. ]

[43] 任丽, 杨联安, 王辉, 等. 基于随机森林的苹果区土壤有机质空间预测[J]. 干旱区资源与环境, 2018,32(8):141-146. [ RenL, YangL A, WangH, et al. Spatial prediction of soil organic matter in apple region based on random forest[J]. Journal of Arid Land Resources and Environment, 2018,32(8):141-146. ] [ Ren L, Yang L A, Wang H, et al. Spatial prediction of soil organic matter in apple region based on random forest[J]. Journal of Arid Land Resources and Environment, 2018,32(8):141-146. ]

[44] 沈掌泉, 周斌, 孔繁胜, 等. 应用广义回归神经网络进行土壤空间变异研究[J]. 土壤学报, 2004,41(3):471-475. [ ShenZ Q, ZhouB, KongF S, et al. Study on spatial variety of soil properties by means of generalized regression neural network[J]. Acta Pedologica Sinica, 2004,41(3):471-475. ] [ Shen Z Q, Zhou B, Kong F S, et al. Study on spatial variety of soil properties by means of generalized regression neural network[J]. Acta Pedologica Sinica, 2004,41(3):471-475. ]

[45] 范曼曼, 吴鹏豹, 张欢, 等. 采样密度对土壤有机质空间变异解析的影响[J]. 农业现代化研究, 2016,37(3):594-600. [ FanM M, WuP B, ZhangH, et al. Effect of sampling density on spatial variability analysis of soil organic matter[J]. Research of Agricultural Modernization, 2016,37(3):594-600. ] [ Fan M M, Wu P B, Zhang H, et al. Effect of sampling density on spatial variability analysis of soil organic matter[J]. Research of Agricultural Modernization, 2016,37(3):594-600. ]

[46] 姜怀龙, 李贻学, 赵倩倩. 县域土壤有机质空间变异特征及合理采样数的确定[J]. 水土保持通报, 2012,32(4):143-146. [ JiangH L, LiY X, ZhaoQ Q. County-scale spatial variability of soil organic matter distribution and determination of reasonable sampling density[J]. Bulletin of Soil and Water Conservation, 2012,32(4):143-146. ] [ Jiang H L, Li Y X, Zhao Q Q. County-scale spatial variability of soil organic matter distribution and determination of reasonable sampling density[J]. Bulletin of Soil and Water Conservation, 2012,32(4):143-146. ]