期刊论文

Prediction of soil moisture content based on coupled hyperspectral data

中文

华中师范大学学报(自然科学版)

1000-1190

2017

51

1

123-129

10.19603/j.cnki.1000-1190.2017.01.018

41401232:国家自然科学基金 41271534:国家自然科学基金 CCNU15A05006:中央高校基本科研业务费专项

本校为第一机构

在田间利用高光谱技术监测土壤含水率（Soil Moisture Content,SMC）成为精准农业研究的热点之一,但农田原状光谱受到土壤表层属性如表面粗糙度、质地、微聚体和其它环境因素的影响,且小尺度区域SMC空间差异较小,增加了SMC光谱信息的提取难度,导致SMC的估算精度较低;基于实验室内经过筛制备的土壤样品的光谱数据建模,虽然模型精度较高,但人为改变土壤结构和紧实度的预处理方式无法表征农田SMC的实际状况.因此,该文尝试提出一种耦合土样原状光谱数据和标准光谱数据估算农田SMC的新方法.通过获取江汉平原潮土土样的原状光谱反射率（Rund）和烘干光谱反射率（Rdry）;基于Rdry确定研究区同一土壤类型...

It becomes a hot spot in precision agricultural research to monitor soil moisture content （SMC） situation by using hyperspectral data in the field. However, the soil undisturbed spectral reflectance is affected by the soil surface properties such as surface roughness, texture and microcapsules as well as other environmental factors, and SMC spatial variation is not significant in small-sale region, making it more difficult to extract spectral information about SMC, which leading to the lower SMC estimation accuracy. In addition, the model bas...