基于地理加权回归的吉林省微波土壤水分降尺度研究  

Microwave Soil Moisture Downscaling Study of Jilin Province Based on Geographically Weighted Regression

作　　者：宋每慧 辛景峰[1,2] 黄诗峰[1,2] 陈鑫雨 SONG Mei-hui;XIN Jing-feng;HUANG Shi-feng;CHEN Xin-yu(China Institute of Water Resources and Hydropower Research,Beijing 100038,China;Research Center on Flood&Drought Disaster Reduction of the Ministry of Water Resources,Beijing 100038,China)

机构地区：[1]中国水利水电科学研究院,北京100038 [2]水利部防洪抗旱减灾工程技术研究中心,北京100038

出　　处：《水电能源科学》2024年第2期23-25,4,共4页Water Resources and Power

基　　金：高分辨率对地观测系统重大专项(08-Y30F02-9001-20/22);江西省重点研发计划(20212BBG71008);江西省水利科技项目(202124ZDKT16)。

摘　　要：微波遥感是土壤水分监测的重要手段,但微波遥感土壤水分产品的空间分辨率较低,难以满足区域尺度的应用需求。使用地理加权回归模型,以1 km MODIS产品的遥感地表温度(LST)和归一化植被指数(NDVI)作为辅助数据,将空间分辨率为9 km的SMAP被动微波土壤水分数据降尺度为1 km,利用吉林省地面实测土壤水分数据,对降尺度后的SMAP数据进行了精度验证。结果表明,该降尺度方法在吉林省适用性较好,降尺度结果与SMAP数据在空间分布上保持了较高的一致性,小幅度提高了SMAP数据的精度,显著提高了SMAP数据的空间细节和纹理特征。At present,microwave remote sensing is an essential method for soil moisture monitoring.But the spatial resolution of soil moisture products from microwave remote sensing is so low that it is difficult to meet the application needs of regional scale.With the aim of downscaling SMAP passive microwave soil moisture from spatial resolution of 9 km to 1 km,remote sensing land surface temperature and normalized difference vegetation index of MODIS products were used as auxiliary data by a downscaling method based on geographically weighted regression model in Jilin Province.The downscaled SMAP passive microwave soil moisture data were compared with the in situ soil moisture data at ground moisture stations.The results show that the downscaling method is suitable for Jilin Province.The downscaling results retain a high consistency with the original soil moisture data,improve the accuracy of SMAP data slightly,and significantly improve the spatial details and texture characteristics of soil moisture.

关 键 词：降尺度 地理加权回归模型 土壤水分 SMAP 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置] S152.7[自动化与计算机技术—控制科学与工程]