多角度遥感估算稀疏团粒分布型土壤表面粗糙度方法初探

表面粗糙度是影响土壤在微波波段发射和散射辐射的主要因素之一,也是微波遥感研究与应用的重要参量。由于微波后向散射还受介电特性、穿透深度等因素的影响,在微波遥感应用中往往难以单独考虑介质表面粗糙度,给参数估算与反演带来了一定困难。在可见光、近红外波段,粗糙度作为土壤表面重要的结构参数之一,直接影响着土壤的二向反射分布特征。因此,本文尝试利用光学多角度观测信息,反演土壤表面粗糙度。基于地表二向反射几何光学模型,假设裸土像元由随机分布于平坦表面的土壤团粒组成,将团粒近似为半椭球体,建立裸露土壤表面二向反射模型,模拟不同粗糙度条件下土壤表面像元的二向反射分布特征。进一步尝试采用多角度观测数据反演模型,估算土壤团粒的几何结构参数,进而计算土壤表面均方根高度,作为表面粗糙度的衡量指标。地面实测多角度数据的初步验证结果表明,多角度光学遥感估算土壤表面粗糙度的方法是可行的。     

GNSS-R土壤水分遥感的适宜性分析

利用GNSS-R(Global Navigation Satellite System-Reflectometry)技术探测土壤水分是近年来一个新兴的研究方向。目前GNSS-R遥感观测中反射信号的接收与处理方式包括单天线与多天线两种模式,面向实际应用需求,GNSS-R遥感正在实现从最初的地基观测向空基、星载观测的转变。在推进GNSS-R土壤水分遥感技术业务化应用的过程中,必须首先进行适宜性分析,确定该技术探测的地理位置、空间分辨率与探测深度,然而目前对此尚未有系统、全面、定量的论述。本文针对适宜性分析中的3个关键因子分别进行理论分析与公式推导,明确相关概念的定义,并实现定量化描述,最终通过实际应用分析进一步诠释其应用价值。对于单天线模式地基观测,以美国板块边界观测计划PBO(Plate Boundary Observatory)土壤水分产品为例,分析镜面反射点的相对位置、第一级Fresnel反射椭圆簇的面积与时间序列土壤水分所代表的探测深度;对于多天线模式,以郑州上街区农田空基观测试验为例,得到基于航迹的栅格土壤水分空间分布并探讨其探测深度。本文能够为未来两种观测模式下地基、空基和星载GNSS-R遥感观测、北斗反射信号遥感,以及GNSS-R在农业、水文、生态等领域的实际应用提供理论指导。     

裸露地表微波热采样深度统计模型

被动微波遥感反演土壤水分对应的土壤深度是土壤水分产品真实性检验和应用中必须确定的问题。本研究利用理论模型对影响土壤热采样深度的参数进行了分析。在此基础上,通过回归分析的方法发展了一个估算被动微波遥感土壤热采样深度的统计模型,并通过微波辐射测量实验对模型进行了验证。研究证明,理论模型模拟裸露地表发射率平均误差为0.032,基于理论模型发展的热采样深度统计模型的误差在0.5 cm左右。该统计模型可以通过土壤含水量、温度、质地和观测频率4个较容易获取的参数计算土壤微波辐射的热采样深度,为被动微波遥感土壤水分产品的真实性检验工作中地面土壤水分测量以及土壤水分遥感产品的应用提供参考。     

中国西部地区基于经验模型的土壤水分反演

地表土壤水分含量的时空分布信息是十分重要的,常常作为水文模型、气候模型、生态模型的输入参数,同时,也是干旱预报、农作物估产等工作的重要指标。被动微波遥感是监测土壤含水量最有效的手段之一。相比红外与可见光,它具有波长长,穿透能力强的优势。相比主动微波雷达,被动微波辐射计具有监测面积大、周期短,受粗糙度影响小,对土壤水分更为敏感,算法更为成熟的优势。目前,已研究出许多反演土壤水分的方法.本课题的主要内容是借助AMSR-E土壤水分影像数据、MODIS归一化植被指数(NDVI)影像数据和MODIS分类影像数据,利用ENVI软件进行遥感图像数据处理,运用统计分析方法建立NDVI与土壤水分的经验模型,研究中国西部地区稀疏植被覆盖区土壤水分的反演。     

The Utility of Day‐and‐Night Observation and Cloud‐Penetration Capability of ERS‐1 SAR Data for Detection of Wetlands

Abstract

The sensitivity of microwave sensors to changes in the complex dielectric constant of soil/water mix with change in water content has been used in several studies for soil moisture estimation and in the detection of wetlands. In the study, reported here, an attempt has been made to delineate various categories of wetlands, namely ‘bils’ (acquaculture ponds), lakes/ponds, creeks, and mangroves through visual interpretation of ERS‐1 SAR images acquired on 29th April, 1993 over part of Sundarban delta, abutting Bay of Bengal. An overall accuracy of 91.2% with respect to delineation of wetlands has been achieved. Further, the cloud penetration and day‐and‐night observation capability of ERS‐1 SAR, though well known, is also illustrated.     

联合热红外与微波的作物辐射方向性模型研究

热红外遥感提供地表表层辐射信息为主,被动微波遥感可更好地提供植被和土壤背景垂直结构的辐射信息。结合热红外与被动微波遥感的优势协同反演植被和土壤组分温度是提高组分温度反演精度的一种思路。本文在对热红外辐射传输模型和微波辐射模型进行比较的基础上,构建均匀作物的统一场景,将统一场景的参数分为直接参数和间接参数。基于统一场景,修改微波辐射模型的场景结构及叶倾角分布,并增加组分温度参数以计算辐射亮温,最终构建热红外与微波辐射联合模拟模型(UEasmmes模型)。针对均匀玉米作物,利用UEasmmes模型进行联合模拟,分析了组分温度、组分发射率、叶面积指数LAI及叶倾角分布LAD对热红外与微波的方向性亮温DBT的敏感性响应差异。分析结果表明:协同热红外与被动微波遥感反演植被和土壤组分温度是可行的,但对于如何克服组分发射率、LAI及LAD对植被有效发射率的影响而导致的微波辐射亮温变化以及实现热红外表皮温度与微波等效温度之间的转化仍是需要深入研究和探讨的问题。     

Simulation Study of a Robust Algorithm for Soil Moisture and Surface Roughness Estimation Using L‐Band Radar Backscatter

Abstract

Various inversion algorithms have been developed to obtain estimates of soil moisture and surface roughness parameters from multifrequency, multiangle, and multipolarization radar reflectances. Since the penetration depth for radar signals increases with wavelength, an inversion algorithm using widely separated frequencies does not yield comparable probing depths. Furthermore, existing algorithms assume a linear relationship between the radar backscatter coefficient (in dB) and soil parameters, such as the volumetric soil moisture, soil surface roughness and surface slope. This assumption is valid only over a narrow range of soil parameters, thereby restricting its operational use under realistic conditions. Our research specifically explored the use of inversion algorithms based on L‐Band radar reflectances at 1 GHz and 2 GHz frequencies in order to retain relatively consistent probing depths. In order to extend the range of applicability, a non‐linear exponential‐type relationship was developed between radar reflectance at a specified frequency, polarization and incidence angle combination, and soil parameters of interest, viz., soil moisture, surface roughness, and surface slope. An over‐constrained inversion algorithm using a six‐parameter combination was found to yield relatively accurate estimates of soil parameters over a wide range of soil conditions even in the presence of system error.     

Total information content as an index of soil moisture

Accurate estimation of soil moisture through remote sensing technique has been a challenge till date. In optical and thermal remote sensing, there is no index developed to detect the changes in soil moisture levels. In microwave region, soil roughness and other target parameters equally affect the technique for soil moisture estimation. Therefore, a computational technique in C language based on Shannon’s Information Theory (Shannon, 1948) has been developed to calculate total information content from multispectral radiometer data. The total information content is a compressed single value, which quantifies the information content of soil spectral reflectance in the electromagnetic spectrum range (400–1100 nm) under study. This technique was tested over a wide range of soil moisture levels. The study revealed that as compared to other techniques total information content index is very sensitive to change in moisture content of soil. This technique could not only quantify the soil moisture content in optical and near infra red region, but also led to a simplified one dimensional separability and clustering analysis.     

土壤湿度微波遥感监测研究进展

土壤湿度是农业生产的重要影响因子,获取土壤湿度信息以制定人工干预调节措施是稳固生产的重要保证,实时、有效地监测土壤墒情显得尤为重要。利用遥感数据反演土壤湿度有多种方法,微波遥感法被认为是目前最佳的监测方法。本文总结了被动、主动微波土壤湿度遥感监测的主要模型、方法及其优缺点和适用范围,分析了雷达遥感监测土壤湿度的最优参数选取等,展望了微波遥感监测土壤湿度的应用前景,以期为土壤湿度微波遥感监测研究提供参考和借鉴。     

Qualitative and quantitative analysis of snow parameters using passive microwave remote sensing

Snow cover is an important variable for climatic and hydrologic models due to its effect on surface albedo, energy, and mass balance. Satellite observations successfully provide a global and comprehensive hemispheric-scale record of the short-term, as well as inter-seasonal variations in snow cover. Passive microwave sensors provide an excellent method to monitor temporal and spatial variations in large-scale snow cover parameters, overcoming problems of cloud cover. Using microwave remote sensing data, snow parameters (snow surface temperature, snow water equivalence, scattering index, emissivity, snow depth) have been retrieved to integrate with the snow cover simulation model developed by SASE for avalanche risk assessment on regional basis. Multispectral and multitemporal brightness temperature data obtained from the Special Sensor Microwave Imager (SSM/I), flown onboard the DMSP satellites, for the period November 2000 to April 2001 and from November 2001 to February 2002 have been analysed. A comparative data set on snow measurements and meteorological observations of a region covering large area of Pir-Panjal and the Greater Himalayan range, available on near real time basis from SASE field observatories were also used. Model calculations were carried out to study the effects of atmospheric transmission on the microwave radiation emitted from the snow covered and snow free ground and atmosphere. The sensitivity of combinations of the SSM/I channels at 19, 37 and 85 GHz, in both horizontal and vertical polarizations, in respect to snow depth, surface temperature of the snowpack have been carried out. Decision rule based algorithms are developed to identify snow cover and non-snow area.     

A Study on the Delineation of Coral Reefs in Andaman and Lakshadweep Islands Using RISAT-1 Data

Coral reefs are one of the most diverse of all marine ecosystems and are often referred to as the “rainforests of the sea”. Though they cover less than one per cent of Earth’s surface, they are home to one quarter of all ocean species by providing food and shelter to them. Optical remote sensing has been widely employed for mapping and monitoring coral reefs. But the application of microwave remote sensing has been an alternate domain in this area. This study explores the possibility of utilizing synthetic aperture radar (SAR) data of Radar Imaging Satellite-I, India’s first indigenous microwave satellite to delineate the coral reefs in Andaman and Lakshadweep Islands in the Indian Ocean. The dual polarized data, after reducing the speckle has been classified to delineate the coral reefs in the vicinity of both islands. SAR has a performance comparable with passive optical sensors under favourable conditions of imaging, viz. optimum tidal current and surface winds. The study results are compared with the international coral reef reference map and are found to be highly promising, with an overall accuracy of 98.3% and a Kappa coefficient of 0.944 for fringing reefs in Andaman region. For the atolls in Lakshadweep region, the overall accuracy is found to be 92.99% and the Kappa coefficient is estimated at 0.7377. This study tries to explore a different horizon for microwave remote sensing in coral reef studies. It is seen that, optical and microwave remote sensing can provide a mutually supporting platform in coral reef delineation, in terms of imaging depth as well as climatic conditions.     

A study on the effect of the soil texture on passive microwave remote sensing

Consideration of soil moisture in terms of percentage of field capacity of the soils for the minimization of textural dependence of microwave emission of soils has been studied by several investigators using experimental data (air borne, field and laboratory experiments) and also theoretical procedures. Their conslusions seem to be not in agreement with each other, thus giving way for further investigations into the problem. To derive information on the choice of parameter through which the textural dependence of microwave emission can be minimized, three test sites have been selected with different soil textures and emission characteristics of these soils are calculated using theoretical approaches. The results of the analysis indicate that the minimal textural dependence is seen on microwave emission when the soil moisture is expressed in terms of volumetric moisture content (m_v) reduced by the amount of transition moisture (W_t).     

含水含盐土壤的微波介电特性分析研究

用微波网络分析仪测量了实验室制备的各种不同含水量,含盐量的土壤样品的复介电常数,研究了介电常数的实部和虚部与频率、盐度、含水量的关系。研究表明:频率、盐度对土壤介电常数实部的影响很小;对于某一特定土壤,其介电常数的实部由土壤的含水量决定;在较低频率范围内（f<2GHz）,虚部随着频率的增大而迅速下降,高频部分则趋向于一定值,波长较长的波段,如P波段或L波段对土壤含盐程度具有更高的敏感性,含盐量对虚部在较低频范围（f<5GHz）影响很大。同时,采集了内蒙古吉兰泰盐湖区的土壤样品,并测量了其复介电常数,与同步过顶的RADARSAT图像进行了相关分析。分析结果表明雷达图像记录的后向散射强度与含盐土壤复介电常数实部的相关系数为0.23,与虚部的相关系数为0.66,即雷达图像观测的含盐含水士壤的后向散射强度与土壤的含盐量相关性较高。这为利用微波遥感进行土壤盐碱化程度监测,提供了可能和实验依据。     

Influence of surface and vegetation characteristics on C-band radar measurements for soil moisture content

Soil moisture estimation using microwave remote sensing faces challenges of the segregation of influences mainly from roughness and vegetation. Under static surface conditions, it was found that Radarsat C-band SAR shows reasonably good correlation and sensitivity with changing soil moisture. Dynamic surface and vegetation conditions are supposed to result in a substantial reduction in radar sensitivity to soil moisture. A C-band scatterometer system (5.2 GHz) with a multi-polarization and multi-angular configuration was used 12 times to sense the soil moisture over a tall vegetated grass field. A score of vegetation and soil parameters were recorded on every occasion of the experiment. Three radar backscattering models Viz., Integral Equation Model (IEM), an empirical model and a volume scattering model, have been used to predict the backscattering phenomena. The volume scattering model, using the Distorted Born Approximation, is found to predict the backscattering phenomena reasonably well. But the surface scattering models are expectedly found to be inadequate for the purpose. The temporal variation of soil moisture does show good empirical relationship with the observed radar backscattering. But as the vegetation biomass increases, the radar shows higher sensitivity to the vegetation parameters compared to surface characteristics. A sensitivity analysis of the volume scattering model for all the parameters also reveals that the radar is more sensitive to plant parameters under high biomass conditions, particularly vegetation water content, but the sensitivity to surface characteristics, particularly to soil moisture, is also appreciable.     

Extinction Behavior of Soil at 26.5 to 110 GHz

Soil electromagnetic properties at the microwave frequencies have been extensively documented in the literature. However, similar information at the higher millimeter frequencies is not available. A laboratory experiment was conducted to investigate the extinction behavior of wet and dry soil at millimeter wavelengths (26.5–110 GHz). For dry soil, the extinction coefficient increased from 0.02 to 0.6 $hbox{cm}^{-1}$ as the frequency increased from 26.5 to 110 GHz. The presence of even a small amount of water in the soil (5% by weight) reduced the penetration of millimeter wave signals into soil by a factor of ten.      

Landscape ecological planning in a Basaltic terrain, central India, using Remote sensing and GIS techniques

In the present study, detailed field survey in conjunction with remotely sensed (IRS-1D, LISS-III) data is of immense help in terrain analysis and landscape ecological planning at watershed level. Geomorphologically summit crust, table top summits, isolated mounds. plateau spurs, narrow slopes, plateau side drainage floors, narrow valleys and main valley floor were delineated. The soil depth ranges from extremely shallow in isolated mounds to very deep soils in the lower sectors. Very good, good, moderate, poor and very poor groundwater prospect zones were delineated. By the integrated analysis of slope, geomorphology. soil depth, land use/land cover and groundwater prospect layers in GIS. 29 landscape ecological units were identified. Each landscape ecological unit refers to a natural geographic entity having distinctive properties of slope, geomorphology. soil depth, land use/ land cover and groundwater prospects. The landscape ecological stress zone mapping of the study area has been carried out based on the analysis and reclassification of tandscape ecological units. The units having minimum ecological impact in terms of slope, geomorphology, soil depth and land use/land cover were delineated under very low stress landscape ecological zones. The units having maximum ecological stress in the form of very high slopes, isolated mounds, table top summits and summit crust, extremely shallow soils, waste lands and very poor groundwater prospects were delineated into very high stress landscape ecological zones. The integrated analysis of remotely sensed data and collateral data in GIS environment is of immense help in evaluation of landscape ecological units and landscape ecological stress zones. The delineated landscape ecological stress zones in the watershed have been recommended for landscape ecological planning for better utilization of natural resources without harming the natural geo-ecosystem of the area.     

用模型和车载微波辐射仪研究多频率多角度下玉米的散射和衰减特性

在使用被动微波技术反演土壤水分的过程中,为去除植被的影响,通常采用适用于低频的τ-ω模型。为准确评估较高频率下植被的散射和衰减特性,以玉米为例,采用基于光线跟踪原理的双矩阵(Matrix-Doubling)微波辐射模型,研究不同高度的作物在C(6.925GHz)、X(10.65GHz)和Ku(18.7GHz)波段下的单散射反照率和传输率。模型模拟的亮度温度跟车载微波辐射仪的野外实测数据接近。为验证模拟的玉米自身微波辐射,在玉米地上铺设了一层铝箔屏蔽地表的辐射。通过给验证后的模型输入不同的参数,建立一个亮度温度数据库,以模拟自然状态下不同高度玉米的亮度温度。然后把模型模拟的结果,跟相同环境下τ-ω模型得到的结果按最小二乘法进行匹配,从而获得不同高度的玉米在C、X和Ku波段上等效的单散射反照率和传输率。     

资源型城市长时间序列土壤含水量变化分析——以锡林浩特市为例

大规模的煤炭开采活动将对生态环境产生扰动,而土壤含水量是受扰动的生态参数之一,且具有重要意义。现有的土壤含水量产品分辨率较低,不适用于区域尺度的研究,而高精度的微波反演由于数据的局限性无法进行长时间序列的研究。本文以我国的重要产煤基地锡林浩特市为研究区,以2004—2020年的AMSR-E与AMSR-2土壤含水量产品及同期的Landsat遥感影像为主要数据源,采用随机森林方法对AMSR-E/2土壤含水量产品进行降尺度处理,通过标准差椭圆等方法对研究区土壤含水量的变化特征进行分析。结果表明：①被动微波土壤含水量降尺度方法可实现对资源型城市的土壤含水量进行长时间序列、高空间分辨率的监测;②无论在矿区还是非矿区,降水均是影响土壤含水量变化的主导因素;③研究区土壤含水量的整体分布在空间上由西北向东南呈现逐渐升高的变化特征,且此分布格局在长时间尺度上保持稳定;④煤炭开采活动对土壤含水量产生扰动,且不同开采阶段的影响具有不同特征。研究结果可为资源型城市生态环境的评价与保护提供科学依据。     

山区地形对被动微波遥感影响的研究进展

随着土壤湿度与海水盐度卫星( SMOS)发射计划的顺利开展和AMSR -E(Advanced Microwave Scanning Radiometer- Earth Observing System)业务化运行服务之后,人类用星载微波辐射计监测土壤水分是空间技术上的又一次飞跃,但土壤水分的反演精度受到微波辐射计低空间...     

根河地区冻融监测和降尺度算法的验证分析

高分辨率地表冻融监测对研究根河地区碳氮循环、水土流失和土壤冻融侵蚀非常重要。本文采用Kou等(2017)提出的被动微波亮温降尺度方法和1 km空间分辨率的温度数据,将0.25°空间分辨率的被动微波亮温降尺度至0.01°空间分辨率。利用通过模型模拟与实验数据发展得到的冻融判别式算法DFA_Zhao(Discriminant Function Algorithm)和改进的冻融判别式算法DFA_Kou(Improved Discriminant Function Algorithm),基于降尺度前后的被动微波亮温监测根河地区的地表冻融。以根河地区2013年7月—2015年12月的地下0—5 cm深度的实测土壤温度检验这两种冻融判识算法的分类精度。结果显示,降尺度前后两种冻融判识算法整体判对率差异在6.72%内;DFA_Zhao算法融化判对率的均值比DFA_Kou算法高10%,DFA_Kou算法冻结判对率均值比DFA_Zhao算法高1%。两种冻融判别式算法的冻结判对率均在90%以上,升轨期的融化判对率均在80%以上,但两算法降轨期的融化判对率较低,在40%—82%之间。同时,还进一步讨论并分析了两种冻融判别式算法和被动微波亮温降尺度方法可能存在的问题,指出了可能的改进方向。