Variable source areas, soil moisture and active microwave observations at Zwalmbeek and Coët-Dan

This chapter focuses on recent research to identify variable source areas from surface soil moisture dynamics observed at the catchment scale by means of active microwave images from satellites. It is hypothesized that variable source areas can be mapped if we can quantify the temporal variability of the surface soil moisture content. It is difficult to determine the soil moisture content from single synthetic aperture radar images because soil moisture, surface roughness, topography and vegetation all have a great effect on radar backscatter. However, seasonal soil moisture fluctuations can be studied by using multitemporal radar images. Two multitemporal image processing techniques are presented to map variable source areas. The first method computes the temporal standard deviation of radar backscatter. This leads to the definition of the so-called saturation potential index, which compares well with observed saturated areas. The second method makes use of a principal component analysis to separate the dominant effects, like topography, land use and soil moisture, on total radar backscatter. Again this leads to reliable mapping of the spatial patterns of variable source areas. Two humid catchments, the Zwalmbeek in Belgium and the Coët-Dan in France, are used in this study

Soil moisture mapping from ASAR imagery for the Flumendosa and Meuse river basins

SP-461 (CD)Soil moisture monitoring and the characterization of the spatial and temporal variability of this hydrologic parameter at scales from small catchments to large river basins continues to receive much attention, reflecting its critical role in subsurface – land surface – atmosphere interactions and its importance to drought analysis, crop yield forecasting, irrigation planning, flood protection, and forest fire prevention. We will describe the objectives and methodologies of an Envisat project that will aim to produce maps of seasonal soil moisture patterns at the regional scale based on ASAR imagery. The work will be carried out for two river basins that have significantly different climatic, geologic, and land use characteristics: the Flumendosa basin in Sardinia (Italy) and the larger Meuse basin that drains a good part of Belgium and the Netherlands as well as portions of France, Germany, and Luxembourg. High resolution ASAR data will be acquired over selected catchment scale test sites within each of these study regions, whereas medium resolution images will be acquired over the entire river basin (or extended region in the case of the smaller basin). A statistical analysis of the information from the processed images at these two different scales will be used to develop an aggregation methodology to generate large scale soil moisture maps. Data assimilation techniques will also be developed for dynamically integrating the high resolution satellite data into catchment scale hydrological simulation models. The work being planned will be placed in the context of recent efforts at validating and applying SAR soil moisture data, which we will briefly review

Image fusion techniqes for remote sensing applications

Image fusion refers to the acquisition, processing and synergistic combination of information provided by various sensors or by the same sensor in many measuring contexts. The aim of this survey paper is to describe three typical applications of data fusion in remote sensing. The first study case considers the problem of the Synthetic Aperture Radar (SAR) Interferometry, where a pair of antennas are used to obtain an elevation map of the observed scene; the second one refers to the fusion of multisensor and multitemporal (Landsat Thematic Mapper and SAR) images of the same site acquired at different times, by using neural networks; the third one presents a processor to fuse multifrequency, multipolarization and mutiresolution SAR images, based on wavelet transform and multiscale Kalman filter. Each study case presents also results achieved by the proposed techniques applied to real data

Polarimetric Synthetic Aperture Radar (SAR) Application for Geological Mapping and Resource Exploration in the Canadian Arctic

The role of remote sensing in geological mapping has been rapidly growing by providing predictive maps in advance of field surveys. Remote predictive maps with broad spatial coverage have been produced for northern Canada and the Canadian Arctic which are typically very difficult to access. Multi and hyperspectral airborne and spaceborne sensors are widely used for geological mapping as spectral characteristics are able to constrain the minerals and rocks that are present in a target region. Rock surfaces in the Canadian Arctic are altered by extensive glacial activity and freeze-thaw weathering, and form different surface roughnesses depending on rock type. Different physical surface properties, such as surface roughness and soil moisture, can be revealed by distinct radar backscattering signatures at different polarizations. This thesis aims to provide a multidisciplinary approach for remote predictive mapping that integrates the lithological and physical surface properties of target rocks. This work investigates the physical surface properties of geological units in the Tunnunik and Haughton impact structures in the Canadian Arctic characterized by polarimetric synthetic aperture radar (SAR). It relates the radar scattering mechanisms of target surfaces to their lithological compositions from multispectral analysis for remote predictive geological mapping in the Canadian Arctic. This work quantitatively estimates the surface roughness relative to the transmitted radar wavelength and volumetric soil moisture by radar scattering model inversion. The SAR polarization signatures of different geological units were also characterized, which showed a significant correlation with their surface roughness. This work presents a modified radar scattering model for weathered rock surfaces. More broadly, it presents an integrative remote predictive mapping algorithm by combining multispectral and polarimetric SAR parameters

NASA geology program bibliography

A bibliography of scientific papers, articles, and books based on research supported by the NASA Geology Program is given. The citations cover the period 1980 to 1990. An author index is included

Summaries of the Sixth Annual JPL Airborne Earth Science Workshop

The Sixth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on March 4-8, 1996, was divided into two smaller workshops:(1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, and The Airborne Synthetic Aperture Radar (AIRSAR) workshop. This current paper, Volume 2 of the Summaries of the Sixth Annual JPL Airborne Earth Science Workshop, presents the summaries for The Airborne Synthetic Aperture Radar (AIRSAR) workshop

High resolution polarimetric imaging of biophysical objects using synthetic aperture radar.

A synthetic aperture microwave near-field system is used to image biophysical objects in order to investigate the nature of radar-target interaction. Two different imaging algorithms for focusing data collected over a two-dimensional planar aperture are investigated. The first of these is the single frequency backward propagation technique which is mathematically simple to implement and provides a high degree of resolution. Secondly, a multifrequency development of the backward propagation algorithm is presented and derived from two separate perspectives. This latter algorithm, known as the auto-focusing algorithm, requires no information about the range of the target from the aperture. Full characterisation by simulation of both algorithms is carried out and different filtering techniques are investigated. The backward propagation algorithm is applied to the polarimetric imaging of three different leafless trees and a sugar beet plant at the X-band frequency of 10GHz. The images so produced demonstrate that the backscattered signal is dependent on the orientation of individual tree elements with respect to the polarisation. Furthermore, multiple scattering terms can be identified within the structure of the tree. The auto-focusing algorithm is applied to the polarimetric imaging of two trees at 10GHz and repeat measurements are made over several months. As with the single frequency measurements, the backscattered signal is dependent on the orientation of individual tree elements relative to the polarisation. The relative contributions from the leaves and branches of the trees to the backscattered signal are assessed and found to be seasonally dependent. Measurements are also carried out to investigate the variation of backscatter from a beech tree with varying incidence angle. It is demonstrated that at small angles of incidence, the leaves are the dominant source of backscatter but at large incidence angles, the branches and trunk of the tree have the greatest contrbution

Detecting depolarized targets using a new geometrical perturbation filter

Target detectors using polarimetry are often focused on single targets, since these can be characterized in a simpler and deterministic way. The algorithm proposed in this paper is aimed at the more difficult problem of partial target detection (i.e. targets with arbitrary degree of polarization). The authors have already proposed a single target detector employing filters based on a geometrical perturbation. In order to enhance the algorithm to the detection of partial targets, a new vector formalism is introduced. The latter is similar to the one exploited for single targets but suitable for complete characterization of partial targets. A new feature vector is generated starting from the covariance matrix, and exploited for the perturbation method. Validation against L-band fully polarimetric airborne E-SAR, and satellite ALOS-PALSAR data and X-band dual polarimetric TerraSAR-X data is provided with significant agreement with the expected results. Additionally, a comparison with the supervised Wishart classifier is presented revealing improvements

ANALYSIS OF STRUCTURAL PARAMETERS OF FOREST TYPOLOGIES USING L-BAND SAR DATA

O objetivo principal desse trabalho é investigar a relação entre o retroespalhamento (σ°) de dados SAR polarimétricos de banda L, em diferentes ângulos de incidência (coletado pelo sensor aerotransportado R99-B/SIPAM) e os parâmetros estruturais de sítios de floresta primária e sucessão  secundária. A área selecionada para esse estudo está localizada na região da Floresta Nacional do Tapajós (Estado do Pará, Brasil) e áreas circunvizinhas. É utilizada a  técnica de decomposição de alvos de Freeman-Durden na avaliação dos mecanismos básicos de espalhamento, para verificar a contribuições das componentes fisionômico-estruturais dos alvos florestais na resposta-radar de banda L. Como conclusão, é possível verificar que a variável “altura das árvores” teve  melhor relação com os valores de retroespalhamento, quando comparado com outras variáveis biofísicas, especialmente quando o modelo também incluiu variações do ângulo de incidência na direção em range. A técnica de decomposição de Freeman-Durden indicou que a componente volumétrica de espalhamento tem uma forte influência na resposta embanda L para florestas tropicais primárias  e secundárias,em ângulos de incidência entre 52 e 70 graus, devido principalmente ao elevado ângulo de incidência e, consequentemente a baixa profundidade de penetração vertical da onda incidente.