{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T05:41:33Z","timestamp":1783489293074,"version":"3.55.0"},"reference-count":64,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,9,15]],"date-time":"2021-09-15T00:00:00Z","timestamp":1631664000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA23100502"],"award-info":[{"award-number":["XDA23100502"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Analyzing rice yields and multidimensional environmental factors at a fine scale facilitates the discovery of the planting environment patterns that guide the spatial layout of rice production. This study uses Pucheng County, Fujian Province, a demonstration county of China Good Grains and Oils, as the research area. Using actual rice yield sample data and environment data, a yield simulation model based on random forest regression is constructed to realize a fine-scale simulation of rice yield and its spatial distribution pattern in Pucheng County. On this basis, we construct a method system to identify spatial combination patterns between rice yields and fine-scale multidimensional environmental planting suitability using rice yield data and environmental planting suitability evaluation data. We categorize the areas into four combination model areas to analyze the spatial correlation model of planting suitability, multidimensional environment, and yield: higher-yield and higher-suitability cluster\u2013comprehensive environmental-advantage areas, high-yield and high-suitability cluster\u2013soil condition-limited areas, moderate-yield and moderate-suitability cluster\u2013irrigation and drainage condition-limited areas, and low-yield and low-suitability cluster\u2013site condition-limited areas. The following results are found. (1) The rice yield simulation model, which is based on random forest regression, considers the various complex relationships between yield and natural as well as human factors to realize the refined simulation of rice yields at a county scale. (2) The county rice yield has a strong positive spatial correlation, and the spatial clustering characteristics are obvious; these relationships can provide a basis for effectively implementing intensive rice planting in Pucheng County. (3) We construct a spatial combination pattern recognition method based on rice yield and environmental planting suitability. We can use this method to effectively identify the spatial relationship between yield and planting suitability as well as the shortcomings and advantages of different regions in terms of the climate, soil, irrigation, site, mechanical farming, and similar factors. On this basis, we can provide regional rice planting guidance for Pucheng County. In addition, this method system also provides a new perspective and method for research into spatial combination models and related spatial issues.<\/jats:p>","DOI":"10.3390\/ijgi10090612","type":"journal-article","created":{"date-parts":[[2021,9,15]],"date-time":"2021-09-15T12:00:44Z","timestamp":1631707244000},"page":"612","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Rice Yield Simulation and Planting Suitability Environment Pattern Recognition at a Fine Scale"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1702-1564","authenticated-orcid":false,"given":"Daichao","family":"Li","sequence":"first","affiliation":[{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianqin","family":"Liang","sequence":"additional","affiliation":[{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingfeng","family":"Wang","sequence":"additional","affiliation":[{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheng","family":"Wu","sequence":"additional","affiliation":[{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaowei","family":"Xie","sequence":"additional","affiliation":[{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaqi","family":"Lu","sequence":"additional","affiliation":[{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00704-016-1852-4","article-title":"Suitability assessment and mapping of Oyo State, Nigeria, for rice cultivation using GIS","volume":"129","author":"Ayoade","year":"2017","journal-title":"Theor. Appl. Climatol."},{"key":"ref_2","first-page":"2879","article-title":"Research progress of remote sensing monitoring of crop spatial pattern","volume":"43","author":"Tang","year":"2010","journal-title":"Chin. Agric. Sci."},{"key":"ref_3","first-page":"7","article-title":"Temporal and Spatial Variation Characteristics of Rice Yield in Jiangsu Province","volume":"37","author":"Du","year":"2014","journal-title":"J. Nanjing Agric. Univ."},{"key":"ref_4","first-page":"51","article-title":"Correlation analysis between annual rice yield fluctuations and meteorological factors in the growing season","volume":"49","author":"Yi","year":"2021","journal-title":"Jiangsu Agric."},{"key":"ref_5","first-page":"67","article-title":"Soil Temperature Changes and Rice Yield Effect under Water-saving Irrigation Conditions in the Area of Well Irrigated Rice in Cold Region","volume":"27","author":"Sun","year":"2008","journal-title":"J. Irrig. Drain."},{"key":"ref_6","unstructured":"Wang, M. (2016). Research on Yield Estimation Method Based on the Simulation of Rice Yield Elements. [Master\u2019s Thesis, Nanjing University of Information Technology]."},{"key":"ref_7","first-page":"74","article-title":"Simulation Study on Rice Yield under Different Irrigation System","volume":"3","author":"Tang","year":"2018","journal-title":"Water Conserv. Tech. Superv."},{"key":"ref_8","first-page":"2","article-title":"Simulation of my country\u2019s rice yield changes under climate change scenarios","volume":"22","author":"Xiong","year":"2001","journal-title":"Chin. Agric. Meteorol."},{"key":"ref_9","unstructured":"Feng, H. (2010). Research on Dynamic Prediction Technology of Rice Yield at County Level Based on Crop Model and GIS. [Master\u2019s Thesis, Anhui Agricultural University]."},{"key":"ref_10","unstructured":"Shen, X. (2020). Research on the Economic and Environmental Effects of Rice Planting Patterns and Their Spatial Layout Optimization Strategies. [Ph.D. Thesis, Huazhong Agricultural University]."},{"key":"ref_11","first-page":"211","article-title":"Research on Spatio-temporal Simulation of Chinese Rice Yield Based on DSSAT Model","volume":"10","author":"Du","year":"2015","journal-title":"Mod. Agric. Technol."},{"key":"ref_12","first-page":"353","article-title":"Spatiotemporal evolution of traditional soybean planting structure in Songnen Plain from 1996 to 2016","volume":"69","author":"Liu","year":"2014","journal-title":"J. Appl. Ecol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"108317","DOI":"10.1016\/j.agrformet.2020.108317","article-title":"Modelling wheat yield with antecedent information, satellite and climate data using machine learning methods in Mexico","volume":"300","author":"Salvador","year":"2021","journal-title":"Agric. For. Meteorol."},{"key":"ref_14","first-page":"1223","article-title":"The effect of chilling injury on rice yield in Heilongjiang Province","volume":"67","author":"Liu","year":"2012","journal-title":"Acta Geogr. Sin."},{"key":"ref_15","first-page":"23","article-title":"Factors Influencing Grain Production of Henan Province Based on Gray Correlation","volume":"1","author":"Li","year":"2009","journal-title":"Asian Agric. Res."},{"key":"ref_16","first-page":"868","article-title":"Analysis of Factors Influencing on Rice Yield in Main Rice Production Areas in Yongsheng County, Yunnan Province","volume":"25","author":"Qi","year":"2010","journal-title":"J. Yunnan Agric. Univ."},{"key":"ref_17","first-page":"95","article-title":"Effects of high temperature stress in different periods on the growth period and yield of rice in Jiangsu Province","volume":"2","author":"Wang","year":"2015","journal-title":"Crop. J."},{"key":"ref_18","first-page":"156","article-title":"Evolution and influencing factors of crop planting structure in Hunan Province","volume":"41","author":"An","year":"2021","journal-title":"Econ. Geogr."},{"key":"ref_19","first-page":"89","article-title":"A review of research on the impact of climate change on rice production","volume":"46","author":"Zeng","year":"2021","journal-title":"Northeast. Agric. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Whetton, R.L., Zhao, Y., Nawar, S., and Mouazen, A.M. (2021). Modelling the Influence of Soil Properties on Crop Yields Using a Non-Linear NFIR Model and Laboratory Data. Soil Syst., 5.","DOI":"10.3390\/soilsystems5010012"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Luh, Y.-H., and Chang, Y.-C. (2021). Effect of Climate Change on Staple Food Production: Empirical Evidence from a Structural Ricardian Analysis. Agronomy, 11.","DOI":"10.3390\/agronomy11020369"},{"key":"ref_22","first-page":"7","article-title":"Reasonable distribution and high-yield cultivation of winter green manure in Jiangxi","volume":"9","author":"Xiao","year":"1981","journal-title":"Jiangxi Agric. Sci. Technol."},{"key":"ref_23","first-page":"353","article-title":"Temporal and spatial distribution characteristics of spring corn in the three provinces of northeast china based on crop spatial distribution model","volume":"69","author":"Tan","year":"2014","journal-title":"Acta Geogr. Sin."},{"key":"ref_24","unstructured":"Huang, Y. (2014). Research on Development Strategy of Characteristic Agriculture Industrialization in Pucheng County. [Master\u2019s Thesis, Fujian Agriculture and Forestry University]."},{"key":"ref_25","unstructured":"Jiang, S. (2010). Impacts of Climate and Soil Temporal and Spatial Changes in Pucheng County on Cultivated Land\u2019s Potential for Food Crops. [Master\u2019s Thesis, Fujian Agriculture and Forestry University]."},{"key":"ref_26","first-page":"1484","article-title":"Research on comprehensive suitability evaluation method of rice planting environment","volume":"23","author":"Wang","year":"2021","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_27","first-page":"19","article-title":"Study on cultivated land suitability evaluation for rice and index determination","volume":"3","author":"Li","year":"2013","journal-title":"J. Agric."},{"key":"ref_28","first-page":"150","article-title":"Changes of grain production pattern and its influencing factors in Henan province","volume":"32","author":"Xue","year":"2013","journal-title":"Reg. Res. Dev."},{"key":"ref_29","first-page":"45","article-title":"Research on resource misallocation and China\u2019s industrial total factor productivity and regional differences under spatial effects","volume":"4","author":"Dong","year":"2021","journal-title":"Study Pract."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1007\/s11294-009-9246-3","article-title":"OLS and GWR Approaches to Agricultural Convergence in the EU-15","volume":"16","author":"Sassi","year":"2010","journal-title":"Int. Adv. Econ. Res."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Phitakwinai, S., Auephanwiriyakul, S., and Theera-Umpon, N. (2016, January 24\u201329). Multilayer perceptron with Cuckoo search in water level prediction for flood forecasting. Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, Canada.","DOI":"10.1109\/IJCNN.2016.7727243"},{"key":"ref_32","first-page":"91","article-title":"Comparative analysis of rice yield forecast in Jilin Province based on time series and cross-sectional data","volume":"30","author":"Chen","year":"2018","journal-title":"China Agric. Inf."},{"key":"ref_33","first-page":"26","article-title":"Remote sensing estimation of rice yield based on random forest regression method","volume":"25","author":"Yang","year":"2020","journal-title":"J. China Agric. Univ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"119823","DOI":"10.1016\/j.saa.2021.119823","article-title":"Estimation of soil organic matter content based on CARS algorithm coupled with random forest","volume":"258","author":"Liu","year":"2021","journal-title":"Spectrochim. Acta Part A Mol. Biomol. Spectrosc."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1111\/j.1435-5597.1998.tb00710.x","article-title":"Some practical applications of Moran\u2019s I\u2019s exact conditional distribution","volume":"77","author":"Tiefelsdorf","year":"1998","journal-title":"Pap. Reg. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"234","DOI":"10.2307\/143141","article-title":"A computer movie simulating urban growth in the Detroit region","volume":"46","author":"Tobler","year":"1970","journal-title":"Econ. Geogr."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Ge, Y., Ren, Z., and Fu, Y. (2021). Understanding the Relationship between Dominant Geo-Environmental Factors and Rural Poverty in Guizhou, China. ISPRS Int. J. Geo.-Inf., 10.","DOI":"10.3390\/ijgi10050270"},{"key":"ref_39","first-page":"260","article-title":"Basic farmland delineation based on local spatial autocorrelation of farmland quality at pixel scale","volume":"50","author":"Liu","year":"2019","journal-title":"J. Agric. Mach."},{"key":"ref_40","first-page":"238","article-title":"Evaluation method of flexible network opening parameters based on orthogonal simulation experiment","volume":"29","author":"Bian","year":"2021","journal-title":"Comput. Meas. Control."},{"key":"ref_41","first-page":"112","article-title":"Urban rail transit station classification and passenger flow characteristic analysis based on K-Means clustering algorithm","volume":"4","author":"Xia","year":"2021","journal-title":"Mod. Urban Rail Transit"},{"key":"ref_42","first-page":"559","article-title":"Steady-state Security Assessment Based on K-Means Clustering Algorithm and Phasor Measurement Units","volume":"13","author":"Hemade","year":"2020","journal-title":"Recent Adv. Electr. Electron. Eng. (Former. Recent Pat. Electr. Electron. Eng.)"},{"key":"ref_43","first-page":"72","article-title":"Variance Analysis on Environmental Effect of Yield and Yield Components of Rice Varieties newly bred in Liaoning","volume":"3","author":"Shen","year":"2007","journal-title":"North Rice"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"88","DOI":"10.29252\/jcb.11.32.88","article-title":"Genetic Analysis of Response to Water Deficit Stress in Wheat Yield Traits with Generation Means and Variance Analysis","volume":"11","author":"Asadi","year":"2019","journal-title":"J. Crop Breed."},{"key":"ref_45","first-page":"433","article-title":"A Condition of Nonparametric Regression Estimator Exponential Convergence Rate of Mean Absolute Error","volume":"4","author":"Chen","year":"1987","journal-title":"Acta Math. Sin."},{"key":"ref_46","first-page":"275","article-title":"Selection of typical years for reservoir groups based on the minimum root mean square error criterion","volume":"3","author":"Sun","year":"2011","journal-title":"J. Xi\u2019an Univ. Technol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"012049","DOI":"10.1088\/1757-899X\/324\/1\/012049","article-title":"Analysis of the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE) in Assessing Rounding Model","volume":"324","author":"Wang","year":"2018","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_48","first-page":"1037","article-title":"Comparison of Soil Attribute Spatial Prediction Based on Co-Kriging Interpolation and Geographically Weighted Regression Model","volume":"49","author":"Guo","year":"2012","journal-title":"Acta Pedol. Sin."},{"key":"ref_49","unstructured":"Zhang, J. (2012). Research on Spatial Differentiation of Urban Residential Land Price Based on GWR Model. [Master\u2019s Thesis, Zhejiang University]."},{"key":"ref_50","unstructured":"(2021). 2020 China Statistical Yearbook. Statistical Theory and Practice, China Statistics Press."},{"key":"ref_51","unstructured":"Jiao, J. (2020). Rice Yield Simulation and Model Improvement Dominated by Meteorological Factors under Different Soil Organic Carbon Content. [Master\u2019s Thesis, Chinese Academy of Agricultural Sciences]."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2283","DOI":"10.15244\/pjoes\/125940","article-title":"The Assessment of AquaCrop Model in Predicting Rice Genotypes Grain and Biological Yield under Water Management Conditions","volume":"30","author":"Roushani","year":"2021","journal-title":"Pol. J. Environ. Stud."},{"key":"ref_53","unstructured":"Xiao, M. (2019). Research on the Correlation between Tourism POI and Regional Economy Based on Geographic Weighted Regression, Southwest Jiaotong University."},{"key":"ref_54","first-page":"39","article-title":"Research on port throughput forecast based on improved multilayer perceptron model","volume":"24","author":"Liu","year":"2021","journal-title":"Softw. Eng."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"587","DOI":"10.14311\/NNW.2015.25.029","article-title":"A new multilayer feedforward network based on trimmed mean neuron model","volume":"25","author":"Yocu","year":"2015","journal-title":"Neural Netw. World"},{"key":"ref_56","first-page":"117","article-title":"A review of research on crop yield prediction based on machine learning","volume":"27","author":"Zhang","year":"2021","journal-title":"Anhui Agric. Sci. Bull."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.compag.2018.05.012","article-title":"Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review","volume":"151","author":"Chlingaryan","year":"2018","journal-title":"Comput. Electron. Agric."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.compag.2018.10.024","article-title":"Forecasting yield by integrating agrarian factors and machine learning models: A survey","volume":"155","author":"Elavarasan","year":"2018","journal-title":"Comput. Electron. Agric."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1126\/science.1204531","article-title":"Climate Trends and Global Crop Production since 1980","volume":"333","author":"Lobell","year":"2011","journal-title":"Science"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"6646126","DOI":"10.1155\/2021\/6646126","article-title":"Modeling the Relationship between Rice Yield and Climate Variables Using Statistical and Machine Learning Techniques","volume":"2021","author":"Wickramasinghe","year":"2021","journal-title":"J. Math."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Ostrowski, M., Prosperi, J., and David, J. (2017). Potential Implications of Climate Change on Aegilops Species Distribution: Sympatry of These Crop Wild Relatives with the Major European Crop Triticum aestivum and Conservation Issues. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0153974"},{"key":"ref_62","first-page":"325","article-title":"Spatial distribution of the chemical properties of the soil and of soybean yield in the field","volume":"47","author":"Fernandes","year":"2016","journal-title":"Rev. Cienc. Agron."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.compag.2012.08.001","article-title":"Combining explanatory crop models with geospatial data for regional analyses of crop yield using field-scale modeling units","volume":"89","author":"Resop","year":"2012","journal-title":"Comput. Electron. Agric."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.gloenvcha.2003.10.008","article-title":"Effects of climate change on global food production under SRES emissions and socio-economic scenarios","volume":"14","author":"Parry","year":"2004","journal-title":"Glob. Environ. Chang."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/9\/612\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:00:12Z","timestamp":1760166012000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/9\/612"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,15]]},"references-count":64,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,9]]}},"alternative-id":["ijgi10090612"],"URL":"https:\/\/doi.org\/10.3390\/ijgi10090612","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,15]]}}}