土壤水分反演特征变量研究综述

	土壤水分反演特征变量研究综述
其他题名	A Review of Researches on Inversion of Eigenvariance of Soil Water
	王俊霞 1; 潘耀忠 2; 朱秀芳 3; 孙章丽 4
	2019
发表期刊	土壤学报
ISSN	0564-3929
卷号	56 期号:1 页码:23-35
摘要	Soil moisture is an integral part of the water, energy and biogeochemical cycle. The information about soil moisture is of great significance to researches on water resources management, agricultural production and climate change. Soil moisture monitoring can be divided into three categories in light of data acquisition method: direct measurement at monitoring sites, simulation and assimilation of soil moisture, and inversion based on remote-sensing data. The remote sensing technology features largescale synchronous observation, covering a range that is not limited by the distribution of ground stations. Then the remote-sensing data based inversion algorithm of soil moisture is an important means of obtaining soil moisture information. However, as soil moisture is strongly influenced by a variety of factors, such as soil properties, surface coverage and meteorological conditions, it is high in spatial heterogeneity. So, it is very difficult to derive large-scales high quality soil moisture data just based on inversion with a single method or single data source. In this paper, factors affecting the inversion of soil moisture were collated, four synthetic multi-featured models for soil moisture inversion were summarized, and existing problems and developmental trends of the inversion processes analyzed. The eigenvariances currently used in soil moisture inversion can be generally sorted into three categories: soil, vegetation and meteorological characteristics. Soil characteristics can be further divided into soil optical reflectance, thermal infrared, microwave brightness and temperature and microwave backlash scattering coefficient, and vegetation characteristics into vegetation optical reflectance and thermal infrared, while meteorological characteristics include rainfall, wind speed, and evapotranspiration and so on. In this paper, synthetic models for multfeatured eigenvariance inversion of soil moisture were summarized, that is, Temperature Vegetation Soil Moisture Dryness Index model (TVMDI), partition statistics model, benchmark value plus variation model, and artificial neural network model. TVMDI is a cubic model based on land surface temperature, vertical vegetation index and soil moisture, and its use enhances correlativity of prediction with measured value. The partition statistics model is to choose an optimal model for each region for inversion, through analyzing types of land cover. The benchmark value plus variation model is to divide the variation of soil moisture during a specified observation period into benchmark value and variation. The former represents the bottom of soil moisture during that period, and the latter depends on precipitation, evapotranspiration and some other meteorological factors, while integrating remote-sensing meteorological information. The artificial neural network model integrate multi-featured eigenvarianes into soil moisture inversion. The analysis of existing problems in and developmental trend of the use of eigenvariance in soil moisture inversion process indicates that the research on adoption of the theory of eigenvariance in soil moisture inversion is insufficient and comprehensive application of the theory is not deep enough, and stresses that coupled application of various ergenvariances may improve accuracy of soil moisture inversion, which is the hot spot of future researches.
其他摘要	土壤水分是水、能量和生物地球化学循环中不可忽略的组成部分,土壤水分信息对水资源管理、农业生产以及气候变化等相关研究有着重要意义。基于遥感数据的土壤水分反演算法是获取土壤水分信息的重要手段,通过对影响土壤水分反演的因素进行梳理,将影响因素抽象为包括土壤特征,植被特征,以及气象特征在内的特征变量,并以此为主线对土壤水分的反演研究进行回顾与梳理。分析了利用不同特征变量反演土壤水分时存在的问题和发展趋势,指出土壤水分反演过程中存在特征变量理论研究不足、综合应用不深的问题,强调耦合使用各类特征变量以提高水分反演精度是未来的研究热点。
关键词	特征变量土壤水分反演遥感 Features variables Soil moisture Inversion Remote sensing
收录类别	CSCD
语种	中文
WOS关键词	Geography
WOS研究方向	Social Sciences
WOS类目	GEOGRAPHY
CSCD记录号	CSCD:6437407
引用统计	被引频次：14[CSCD] [CSCD记录]
文献类型	期刊论文
专题	任务一_子任务一循证社会科学证据集成任务一
作者单位	1.北京师范大学;;北京师范大学地理科学学部遥感科学与工程研究院, 地表过程与资源生态国家重点实验室;;, ;;, 北京;;北京 100875;;100875, 中国 2.北京师范大学;;北京师范大学地理科学学部遥感科学与工程研究院;;北京师范大学, 环境演变与自然灾害教育部重点实验室;;;;地理科学学部遥感科学国家重点实验室, ;;;;, 北京;;北京;;北京 100875;;100875;;100875, 中国 3.北京师范大学;;北京师范大学;;北京师范大学地理科学学部遥感科学与工程研究院, 地表过程与资源生态国家重点实验室;;环境演变与自然灾害教育部重点实验室;;, ;;;;, 北京;;北京;;北京 100875;;100875;;100875, 中国 4.北京师范大学;;北京师范大学地理科学学部遥感科学与工程研究院, 地表过程与资源生态国家重点实验室;;, ;;, 北京;;北京 100875;;100875, 中国
推荐引用方式 GB/T 7714	王俊霞,潘耀忠,朱秀芳,等. 土壤水分反演特征变量研究综述[J]. 土壤学报,2019,56(1):23-35.
APA	王俊霞,潘耀忠,朱秀芳,&孙章丽.(2019).土壤水分反演特征变量研究综述.土壤学报,56(1),23-35.
MLA	王俊霞,et al."土壤水分反演特征变量研究综述".土壤学报 56.1(2019):23-35.