Derivation of surface soil moisture from ENVISAT ASAR wide swath and image mode data in agricultural areas

Water and energy fluxes at the interface between the land surface and atmosphere are strongly dependent on surface soil moisture content, which is highly variable in space and time. It has been shown in numerous studies that microwave remote sensing can provide spatially distributed patterns of surface soil moisture. In order to use remote-sensing-derived soil moisture information for practical applications as, for example, flood forecasting and water balance modeling in mesoscale areas, frequent large-area coverage is a prerequisite. New sensor generations such as ENVISAT Advanced Synthetic Aperture Radar (ASAR) or RADARSAT allow for image acquisitions in different imaging modes and geometries. Imaging modes with the capability of large-area coverage, such as the Wide Swath Mode of ENVISAT ASAR, are of special interest for practical applications in this context. This paper presents a semiempirical soil moisture inversion scheme for ENVISAT ASAR data. Different land cover types as well as mixed-image pixels are taken into account in the soil moisture retrieval process. The inversion results are validated against in situ measurements, and a sensitivity analysis of the model is conducted.     

On current limits of soil moisture retrieval from ERS-SAR data

Assesses the feasibility of retrieving soil moisture content over smooth bare-soil fields using European Remote Sensing synthetic aperture radar (ERS-SAR) data. The roughness conditions considered in this study correspond to those observed in agricultural fields at the time of sowing. Within this context, the retrieval possibilities of a single-parameter ERS-SAR configuration is assessed using appropriately trained neural networks. Three sources of error affecting soil moisture retrieval (inversion, measurement, and model errors) are identified, and their relative influence on retrieval performance is assessed using synthetic datasets as well as a large pan-European database of ground and ERS-1 and ERS-2 measurements. The results from this study indicate that no more than two soil moisture classes can reliably be distinguished using the ERS configuration, even for the restricted roughness range considered.     

基于多时相Sentinel-1 SAR数据的喀斯特石漠化区地表土壤水分反演研究

土壤水分是地球表层水循环、能量循环和生物地球化学循环中的重要组成部分,是研究喀斯特石漠化地区生态系统的关键参数。基于多时相的Sentinel-1 SAR数据与Alpha 近似模型构建土壤水分观测方程组,反演喀斯特石漠化地区地表土壤水分并对其时空变化特征及误差影响因素展开分析。研究发现观测周期内区域土壤水分总体变化趋势与降雨量变化趋势高度一致,石漠化地区土壤水分高值与空间异质性程度明显高于非石漠化地区。精度验证结果显示土壤水分反演结果的均方根误差为0.059 cm³/cm³,平均误差为0.026 cm³/cm³,该方法在区域地表土壤水分反演中表现出一定的适用性,分析认为地表土壤因周边的复杂生境条件产生的混合像元问题是导致反演误差的主要影响因素。研究可为利用短时间周期重复遥感观测方法获取复杂山区环境下的土壤水分提供参考,为喀斯特石漠化地区生态系统修复和生态产业发展提供支撑。     

Image reconstruction from real scattering data using an iterativescheme with incorporated a priori information

The two-dimensional inverse electromagnetic-scattering problem of reconstructing the material properties of inhomogeneous lossy dielectric cylindrical objects is considered. The material properties are reconstructed from measured far-field scattering data, provided by the USAF Rome Laboratory Electromagnetic Measurement Facility in Ipswich. The targets in the Ipswich data set include perfectly electrically conducting (PEC) targets, penetrable (PEN) targets, and hybrid targets. A new method, which incorporates a priori information about the material properties, is proposed to solve the nonlinear inverse-scattering problem     

A multifrequency algorithm for the retrieval of soil moisture on alarge scale using microwave data from SMMR and SSM/I satellites

The sensitivity of microwave emission at different frequencies to soil moisture in bare and vegetated soils has been investigated using experimental data. Since the best frequency for the measurement of soil moisture (L-band) is absent in current satellite sensors, it is necessary to seek alternative solutions. An algorithm is proposed for the retrieval of soil moisture based on the sensitivity to moisture of both the brightness temperature and the polarization index at C-band, one that is able to correct for the effect of vegetation by means of the polarization index at X-band. The algorithm has been tested by using experimental data collected with airborne microwave radiometers on agricultural areas and validated by using the data sets of special sensor microwave/imager (SMM/I) and scanning multichannel microwave radiometer (SMMR). These research activities are planned in view of coming new satellites: AQUA (NASA) and ADEOS-II (NASDA), which will be launched by the end of 2001. These will have new generation microwave radiometers (AMSR-E and AMSR) onboard, which show much better characteristics with respect to the previous sensors, in particular an enhanced spatial resolution     

Using a pair of phased antennas to improve UHF reception/transmission in tunnels

UHF propagation inside tunnels improves considerably if a pair of phased antennas is used as a fixed antenna system, instead of a single antenna. In this article, we have analyzed the causes of signal deterioration in a tunnel due to slow fading and fast fading. We obtained simple relations for their calculation, which are valid for a rectangular tunnel. We then demonstrated that the pair of phased antennas can reduce fast fading. The measurements performed on pilot projects in actual tunnels confirmed that the pair of phased antennas is capable of reducing fast fading, which is usually the real limiting factor for transmission in tunnels.     

Using the node's experience from previous transmissions to improve the communication in an indoor localization system

Although originally the wireless sensor networks (WSN) were designed for transmitting environmental parameters with a low data rate, there is a growing need to use these networks for applications that require high throughput, such as real time localization systems (RTLS).     

Using labeled data to evaluate change detectors in a multivariate streaming environment

We consider the problem of detecting changes in a multivariate data stream. A change detector is defined by a detection algorithm and an alarm threshold. A detection algorithm maps the stream of input vectors into a univariate detection stream. The detector signals a change when the detection stream exceeds the chosen alarm threshold. We consider two aspects of the problem: (1) setting the alarm threshold and (2) measuring/comparing the performance of detection algorithms. We assume we are given a segment of the stream where changes of interest are marked. We present evidence that, without such marked training data, it might not be possible to accurately estimate the false alarm rate for a given alarm threshold. Commonly used approaches assume the data stream consists of independent observations, an implausible assumption given the time series nature of the data. Lack of independence can lead to estimates that are badly biased. Marked training data can also be used for realistic comparison of detection algorithms. We define a version of the receiver operating characteristic curve adapted to the change detection problem and propose a block bootstrap for comparing such curves. We illustrate the proposed methodology using multivariate data derived from an image stream.     

Using mobile robots to harvest data from sensor fields - [wireless communications in networked robotics]

We explore synergies among mobile robots and wireless sensor networks in environmental monitoring through a system in which robotic data mules collect measurements gathered by sensing nodes. A proof-of-concept implementation demonstrates that this approach significantly increases the lifetime of the system by conserving energy that the sensing nodes otherwise would use for communication.