基于遥感信息的灌溉区墒情预测  

Prediction of Soil Moisture Conditions in Irrigation Areas Based on Remote Sensing Information

作　　者：周彦鹏 苏阳辉 ZHOU Yanpeng;SU Yanghui(Fengjiashan Reservoir Management Bureau,Baoji Shaanxi 721000;Hongqi Electric Power Pumping Station of Jingyang County Water Resources Bureau,Xianyang Shaanxi 713700)

机构地区：[1]陕西省宝鸡市冯家山水库管理局,陕西宝鸡721000 [2]泾阳县水利局红旗电力抽水站,陕西咸阳713700

出　　处：《四川水力发电》2025年第1期164-167,共4页Sichuan Hydropower

摘　　要：通过分析91组包含气温、降雨量、植被覆盖率和土壤湿度的数据,比较了两种模型在墒情预测上的表现。研究结果显示:决策树回归模型能够有效处理数据中的复杂非线性关系,在预测准确性方面表现更佳,特别是在捕捉和解释墒情值与环境因素之间复杂关系方面,决策树模型展现了较高的适应性和准确度。研究为灌溉区墒情的预测提供了新的视角,强调了选择适当的预测模型对于提高预测准确性的重要性。研究成果不仅有助于指导农业灌溉决策,还为未来在智慧农业和可持续发展领域的研究提供了宝贵的参考。By analyzing 91 sets of data including temperature,rainfall,vegetation coverage,and soil moisture,the performance of these two models in predicting soil moisture conditions was compared.The results show that the decision tree regression model is more effective in handling complex nonlinear relationships in the data and shows better performance in terms of prediction accuracy.Especially in capturing and interpreting the complex relationships between soil moisture values and environmental factors,the decision tree regression model demonstrates higher adaptability and accuracy.This study provides a new perspective for predicting soil moisture conditions in irrigation areas,emphasizing the importance of selecting appropriate prediction models to improve prediction accuracy.The results are not only helpful in guiding agricultural irrigation decisions but also provide valuable references for future research in smart agriculture and sustainable development.

关 键 词：遥感技术 灌溉区 墒情预测 数据处理 决策树回归模型 

分 类 号：TP7[自动化与计算机技术—检测技术与自动化装置]