基于GEE平台潘庄引黄灌区土壤水分监测分析

Analysis on Soil Moisture Monitoring in Panzhuang Yellow River Diversion Irrigation District Based on GEE Platform

摘要:

本研究借助Google Earth Engine(GEE)平台,运用Sentinel-1雷达影像数据与SMAP土壤水分数据构建线性回归模型,对潘庄引黄灌区的土壤水分展开反演分析。研究结果显示:2020年该灌区土壤水分含量在0.12~0.32 cm3/cm3之间波动,呈现出明显的季节性差异:春季土壤相对湿润,冬季较为干旱;在空间分布上也不均衡,西部干旱,东北部湿润。研究也表明,冬小麦成熟期、玉米生长期间以及棉花全生育期均需要进行人工灌溉。该研究成果为精准灌溉提供了数据支撑,同时也展现了遥感技术在农业水分监测领域的巨大潜力。

Abstract:

This study uses the Google Earth Engine (GEE) platform, constructs a linear regression model by integrating Sentinel-1 radar image data and SMAP soil moisture data, and conducts inversion analysis of soil moisture in the Panzhuang Yellow River Diversion Irrigation District. The results show that the soil moisture content in the irrigation district fluctuated between 0.12 and 0.32 cm3/cm3 in 2020, showing obvious seasonal differences: relatively moist in spring and dry in winter; the spatial distribution was also uneven, with arid conditions in the west and moist conditions in the northeast. The study also indicates that artificial irrigation is required during the maturity period of winter wheat, the growth period of corn, and the entire growth period of cotton. The research results provide data support for precision irrigation and demonstrate the great potential of remote sensing technology in the field of agricultural moisture monitoring.