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Geoscience and Remote Sensing, IEEE Transactions on

Issue 2 • Date Feb. 2009

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Displaying Results 1 - 25 of 34
  • [Front cover]

    Page(s): C1
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    Freely Available from IEEE
  • IEEE Transactions on Geoscience and Remote Sensing publication information

    Page(s): C2
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    Freely Available from IEEE
  • Table of contents

    Page(s): 377 - 378
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  • Foreword to the Special Issue on Retrieval of Bio- and Geophysical Parameters From SAR Data for Land Applications

    Page(s): 379 - 380
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    Freely Available from IEEE
  • List of reviewers

    Page(s): 381
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    Freely Available from IEEE
  • Using a Ground-Based SAR Interferometer and a Terrestrial Laser Scanner to Monitor a Snow-Covered Slope: Results From an Experimental Data Collection in Tyrol (Austria)

    Page(s): 382 - 393
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1747 KB) |  | HTML iconHTML  

    In this paper, we report on an experimental activity aimed at investigating the potential of two terrestrial remote-sensing techniques, namely, ground-based SAR (GB SAR) interferometry and terrestrial laser scanning, in order to retrieve snow-depth (SD) measurements in mountainous regions. Terrestrial laser scanning is a more consolidated technique based on the measurement of the optical (near infrared) reflectivity, and it is affected by the surface of the snow layer: a temporal data sequence allows us to estimate the absolute SD variation. Recent use of SAR interferometry to evaluate snow-mass characteristics is based on relating the measured interferometric phase shift to a change in the snow mass. Interferometric GB SAR measurements and terrestrial laser scanner scans were collected together with pointwise conventional measurements of physical snow parameters during the winters of 2005/2006 and 2006/2007. The experiment was carried out in the Wattener Lizum, a high Alpine area at about 2000-m elevation north of the main ridge of the Austrian Alps in Tyrol. Notwithstanding the difficulty of providing both lengthy data record in dry snow conditions and detailed knowledge of the observed snow characteristics, the obtained results confirmed the presence of a clearly measurable interferometric phase variation in relation to the growing height of the snow layer. A comparison of the SD maps obtained through the two techniques shows differences partly due to the different nature of the two observations. View full abstract»

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  • Glacier Velocity Monitoring by Maximum Likelihood Texture Tracking

    Page(s): 394 - 405
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1497 KB) |  | HTML iconHTML  

    The performance of a tracking algorithm considering remotely sensed data strongly depends on a correct statistical description of the data, i.e., its noise model. The objective of this paper is to introduce a new intensity tracking algorithm for synthetic aperture radar (SAR) data, considering its multiplicative speckle/noise model. The proposed tracking algorithm is discussed regarding the measurement of glacier velocities. Glacier monitoring exhibits complex spatial and temporal dynamics including snowfall, melting, and ice flows at a variety of spatial and temporal scales. Due to these complex characteristics, most traditional methods based on SAR suffer from speckle decorrelation that results in a low signal-to-noise ratio. The proposed tracking technique improves the accuracy of the classical intensity tracking technique by making use of the temporal speckle structure. Even though a new intensity-based matching algorithm is proposed, particularly for incoherent data sets, the analysis of the proposed technique was also performed for correlated data sets. As it is demonstrated, the velocity monitoring can be continuously performed by using the maximum likelihood (ML) texture tracking without any assumption concerning the correlation of the data set. The ML texture tracking approach was tested on ENVISAT-ASAR data acquired during summer 2004 over the Inyltshik glacier in Kyrgyzstan, representing one of the largest alpine glacier systems of the world. It will be demonstrated that the proposed technique is capable of robustly and precisely detecting the surface velocity field and velocity changes in time. View full abstract»

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  • Snowpack Characterization in Mountainous Regions Using C-Band SAR Data and a Meteorological Model

    Page(s): 406 - 418
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2941 KB) |  | HTML iconHTML  

    This paper presents a method to characterize snow cover in mountainous regions using dual-polarization C-band synthetic aperture radar (SAR) data. It is demonstrated that an accurate modeling of the liquid water distribution inside the snowpack, using a multilayer meteorological snow model, is required to characterize snow with precision. A multilayer-snow electromagnetic (EM) backscattering model is developed based on the vector radiative transfer, the strong fluctuation theory, and physical parameters supplied by the meteorological model. However, the limited resolution of the meteorological snow model is insufficient for predicting a refined EM backscattering at a massif scale. An adequate spatial reorganization of these snow profiles, based on a comparison between simulated and measured dual-polarization SAR data, leads to a better estimation of some snowpack parameters. In particular, the monitoring of snow liquid water content is presented improving the capacity of wet snow mapping as compared to a classical SAR-based method. This methodology shows good capacities both for qualitative and quantitative snow assessments, opening the way for a new operational method. View full abstract»

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  • Estimation of the Surface Velocity Field of the Aletsch Glacier Using Multibaseline Airborne SAR Interferometry

    Page(s): 419 - 430
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2086 KB) |  | HTML iconHTML  

    This paper presents a methodology to process airborne interferometric synthetic aperture radar (SAR) data to measure surface velocity fields (SVFs) of temperate glaciers, and applies it to data acquired over the Aletsch glacier. The first part of this paper deals with the main limitation in airborne interferometric SAR to retrieve reliable interferometric products, namely, the existence of the so-called residual motion errors - inaccuracies on the order of a few centimeters in the navigation system. An extended multisquint approach is proposed for their estimation in the case of nonstationary scenes. The second part of this paper expounds an efficient methodology to derive SVFs with airborne systems, where the line-of-sight displacement is estimated using differential interferometry and the along-track component by estimating the azimuth coregistration offsets. The necessary steps to finally obtain the 3-D SVF are also presented, as well as the possibility of combining different acquisition geometries. Airborne interferometric SAR data acquired by the Experimental SAR system of the German aerospace center over the Aletsch glacier, located in the Swiss Alps, are used to evaluate the performance of the proposed approach. The motion of the corner reflectors deployed in the scene is retrieved with an accuracy between 1 and 5 cm/day using L-band data. View full abstract»

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  • Water Level Estimation and Reduction of Hydraulic Model Calibration Uncertainties Using Satellite SAR Images of Floods

    Page(s): 431 - 441
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1100 KB) |  | HTML iconHTML  

    Exploitation of river inundation satellite images, particularly for operational applications, is mostly restricted to flood extent mapping. However, there lies significant potential for improvement in a 3-D characterization of floods (i.e., flood depth maps) and an integration of the remote-sensing-derived (RSD) characteristics in hydraulic models. This paper aims at developing synthetic aperture radar (SAR) image analysis methods that go beyond flood extent mapping to assess the potential of these images in the spatiotemporal characterization of flood events. To meet this aim, two research issues were addressed. The first issue relates to water level estimation. The proposed method, which is an adaptation to SAR images of the method developed for water level estimation using flood aerial photographs, is composed of three steps: (1) extraction of flood extent limits that are relevant for water level estimation; (2) water level estimation by merging relevant limits with a Digital Elevation Model; and (3) constraining of the water level estimates using hydraulic coherence concepts. Applied to an ENVISAT image of an Alzette River flood (2003, Grand Duchy of Luxembourg), this provides plusmn54-cm average vertical uncertainty water levels that were validated using a sample of ground surveyed high water marks. The second issue aims at better constraining hydraulic models using these RSD water levels. To meet this aim, a "traditional" calibration using recorded hydrographs is completed via comparison between simulated and RSD water levels. This integration of the RSD characteristics proves to better constrain the model (i.e., the number of parameter sets providing acceptable results with respect to observations has been reduced). Furthermore, simulations of a flood event of a different return period (2007) using the model calibrated for the 2003 flood event shows the reliability of the latter for flood forecasting. View full abstract»

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  • Potential of Estimating Soil Moisture Under Vegetation Cover by Means of PolSAR

    Page(s): 442 - 454
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2454 KB) |  | HTML iconHTML  

    In this paper, the potential of using polarimetric SAR (PolSAR) acquisitions for the estimation of volumetric soil moisture under agricultural vegetation is investigated. Soil-moisture estimation by means of SAR is a topic that is intensively investigated but yet not solved satisfactorily. The key problem is the presence of vegetation cover which biases soil-moisture estimates. In this paper, we discuss the problem of soil-moisture estimation in the presence of agricultural vegetation by means of L-band PolSAR images. SAR polarimetry allows the decomposition of the scattering signature into canonical scattering components and their quantification. We discuss simple canonical models for surface, dihedral, and vegetation scattering and use them to model and interpret scattering processes. The performance and modifications of the individual scattering components are discussed. The obtained surface and dihedral components are then used to retrieve surface soil moisture. The investigations cover, for the first time, the whole vegetation-growing period for three crop types using SAR data and ground measurements acquired in the frame of the AgriSAR campaign. View full abstract»

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  • Optimization of Soil Hydraulic Model Parameters Using Synthetic Aperture Radar Data: An Integrated Multidisciplinary Approach

    Page(s): 455 - 467
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    It is widely recognized that synthetic aperture radar (SAR) data are a very valuable source of information for the modeling of the interactions between the land surface and the atmosphere. During the last couple of decades, most of the research on the use of SAR data in hydrologic applications has been focused on the retrieval of land and biogeophysical parameters (e.g., soil moisture contents). One relatively unexplored issue consists of the optimization of soil hydraulic model parameters, such as, for example, hydraulic conductivity values, through remote sensing. This is due to the fact that no direct relationships between the remote-sensing observations, more specifically radar backscatter values, and the parameter values can be derived. However, land surface models can provide these relationships. The objective of this paper is to retrieve a number of soil physical model parameters through a combination of remote sensing and land surface modeling. Spatially distributed and multitemporal SAR-based soil moisture maps are the basis of the study. The surface soil moisture values are used in a parameter estimation procedure based on the extended Kalman filter equations. In fact, the land surface model is, thus, used to determine the relationship between the soil physical parameters and the remote-sensing data. An analysis is then performed, relating the retrieved soil parameters to the soil texture data available over the study area. The results of the study show that there is a potential to retrieve soil physical model parameters through a combination of land surface modeling and remote sensing. View full abstract»

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  • Using ENVISAT ASAR Global Mode Data for Surface Soil Moisture Retrieval Over Oklahoma, USA

    Page(s): 468 - 480
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (874 KB) |  | HTML iconHTML  

    The Advanced Synthetic Aperture Radar (ASAR) onboard of the satellite ENVISAT can be operated in global monitoring (GM) mode. ASAR GM mode has delivered the first global multiyear C-band backscatter data set in HH polarization at a spatial resolution of 1 km. This paper investigates if ASAR GM can be used for retrieving soil moisture using a change detection approach over large regions. A method previously developed for the European Remote Sensing (ERS) scatterometer is adapted for use with ASAR GM and tested over Oklahoma, USA. The ASAR-GM-derived relative soil moisture index is compared to 50-km ERS soil moisture data and pointlike in situ measurements from the Oklahoma MESONET. Even though the scale gap from ASAR GM to the in situ measurements is less pronounced than in the case of the ERS scatterometer, the correlation for ASAR against the in situ measurements is, in general, somewhat weaker than for the ERS scatterometer. The analysis suggests that this is mainly due to the much higher noise level of ASAR GM compared to the ERS scatterometer. Therefore, some spatial averaging to 3-10 km is recommended to reduce the noise of the ASAR GM soil moisture images. Nevertheless, the study demonstrates that ASAR GM allows resolving spatial details in the soil moisture patterns not observable in the ERS scatterometer measurements while still retaining the basic capability of the ERS scatterometer to capture temporal trends over large areas. View full abstract»

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  • Tropical-Forest-Parameter Estimation by Means of Pol-InSAR: The INDREX-II Campaign

    Page(s): 481 - 493
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1441 KB) |  | HTML iconHTML  

    This paper addresses the potential and limitations of polarimetric synthetic aperture radar (SAR) interferometry (Pol-InSAR) inversion techniques for quantitative forest-parameter estimation in tropical forests by making use of the unique data set acquired in the frame of the second Indonesian Airborne Radar Experiment (INDREX-II) campaign - including Pol-InSAR, light detection and ranging (LIDAR), and ground measurements - over typical Southeast Asia forest formations. The performance of Pol-InSAR inversion is not only assessed primarily at L- and P-band but also at higher frequencies, namely, X-band. critical performance parameters such as the ldquovisibility of the groundrdquo at L- and P-band as well as temporal decorrelation in short-time repeat-pass interferometry are discussed and quantitatively assessed. Inversion performance is validated against LIDAR and ground measurements over different test sites. View full abstract»

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  • Analysis by Wavelet Frames of Spatial Statistics in SAR Data for Characterizing Structural Properties of Forests

    Page(s): 494 - 507
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1920 KB) |  | HTML iconHTML  

    Spatial statistics (texture) in SAR backscatter data of forested areas bears information on structural and geometric properties that could be useful in mapping forest extent, species type, and stages of regeneration or degradation. Based on a previously published theoretical approach in deriving texture measures from SAR data using wavelet frames, experiments are reported that aim to characterize, from a purely observational point of view, wavelet texture measures' sensitivity with respect to target structural properties and SAR configurations. Suitable analytical tools are introduced to represent dependences in the combined space-scale-polarization domain through signatures that condense information in graphical form. Moreover, class separability, afforded by wavelet texture measures in a supervised classification setting and based on the Fischer linear discriminant analysis, is considered. This paper focuses on two structurally different forest types (tropical rain forest in the Central Africa Congo Floodplain and mixed-species wooded savanna in Queensland, Australia) and uses data from orbital radars, particularly from the Japanese Advanced Land Observing Satellite Phased Arrayed L-band Synthetic Aperture Radar. The analysis indicated that textural information from spatial statistics can provide, in some cases, better class separability in forest mapping with respect to one-point statistics, although spatial resolution in texture products is reduced. However, dependences of texture measures on the polarization state are detected, particularly in forests where a greater diversity of scattering mechanisms occurs. View full abstract»

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  • Application of Target Decomposition Theorems Over Snow-Covered Forested Areas

    Page(s): 508 - 512
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (447 KB) |  | HTML iconHTML  

    This paper compares two well-known polarimetric decomposition theorems, Cloude-Pottier and Freeman-Durden, applied to L- and C-band Airborne Polarimetric Synthetic Aperture Radar (AIRSAR-POLSAR) data acquired during the Cold-Land Processes Field Experiments. Three field campaigns were carried out in February 2002, March 2002, and March 2003 over a snow-covered open terrain, a sparse coniferous forest, and a dense coniferous forest. The analysis evaluates the ability of the two target decomposition methods for the identification and understanding of the main scattering mechanisms. View full abstract»

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  • Automatic Model-Based Estimation of Boreal Forest Stem Volume From Repeat Pass C-band InSAR Coherence

    Page(s): 513 - 516
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (194 KB) |  | HTML iconHTML  

    C-band repeat pass interferometric synthetic aperture radar coherence can provide high-accuracy estimates of boreal forest stem volume in spite of environmental dependence. Typically, the retrieval methods require a data set of in situ measurements for training the model linking coherence to stem volume. The drawback is the need for such data and the incapacity to take into account spatial variations of environmental conditions. Here, we demonstrate a model training method that does not require reference data. For the investigated case, the relative root mean square error of stem volume is 18% or as good as obtained using the traditional training method with in situ data. View full abstract»

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  • Monitoring of the Rice Cropping System in the Mekong Delta Using ENVISAT/ASAR Dual Polarization Data

    Page(s): 517 - 526
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1210 KB) |  | HTML iconHTML  

    The rice cropping system in Asia is undergoing major changes to cope with increasing demography and changing climate, making rice monitoring a critical issue. Past studies have demonstrated the use of C-band synthetic aperture radar (SAR) data to map rice areas. The methods were based on the temporal change of intensity backscattering coefficient of vertically or horizontally co-polarized data (VV or HH). In this paper, we assess the use of the HH/VV polarization ratio derived from Advanced SAR (ASAR) data from ENVISAT data for the production of rice paddy maps. The approach is based on past knowledge on the polarization behavior of rice canopy, i.e., VV backscattering is much lower than HH during a large part of the rice season, due to the attenuation of the wave by the vertical structure of the plants. The methodology is developed for the Mekong Delta, Vietnam, where a complex cropping pattern is found (one to three crops of rice per year). The approach includes a statistical analysis of the HH/VV distributions of rice and non-rice classes at different dates. The analysis results confirm that HH/VV can be used as classifier and point out the need for relevant speckle filtering prior to classification. A classification method is developed and applied to single- and multidate data sets. The methods are tested at one district of the province of An Giang and extended to the whole province. Comparisons of the mapping results to geographic-information-system land-use data and official agricultural statistics show very good agreement. The method will be further applied to the entire Mekong Delta. View full abstract»

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  • Wheat Crop Mapping by Using ASAR AP Data

    Page(s): 527 - 530
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (143 KB) |  | HTML iconHTML  

    The purpose of this paper is to assess the use of C-band HH/VV backscatter ratio for mapping winter wheat. This paper analyzes two temporal series of images acquired in 2006 and 2007 by the Advanced Synthetic Aperture Radar (ASAR) system in alternating polarization (AP) mode, over an agricultural site located in southern Italy. Results on test data show that classification accuracies between 75% and 80% can be achieved by using a single ASAR image, acquired during the peak of the wheat-growing season. To achieve accuracies close to 90%, a spatial averaging at field scale is necessary. View full abstract»

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  • Estimation of the Minimum Number of Tracks for SAR Tomography

    Page(s): 531 - 543
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1011 KB) |  | HTML iconHTML  

    Synthetic aperture radar tomography (SARTom) is the natural extension of SAR interferometry to solve for multiple phase centers within a resolution cell and obtain the 3-D representation of a scene. This paper deals with the determination of the minimum number of tracks required to perform SARTom. Through the prolate spheroidal wave functions, the number of equivalent targets of a volumetric source is derived, and from it, the minimum number of observations required to apply subspace superresolution methods is computed. The minimum tomographic aperture length is also investigated. The results are validated on real data acquired in L-band by the experimental SAR system of the German Aerospace Center. View full abstract»

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  • Performance of Stereoradargrammetric Methods Applied to Spaceborne Monostatic–Bistatic Synthetic Aperture Radar

    Page(s): 544 - 560
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1563 KB) |  | HTML iconHTML  

    This paper aims to investigate the performance of stereoradargrammetric methods applied to spaceborne monostatic-bistatic synthetic aperture radar (SAR) data for digital elevation model (DEM) generation. Stereoradargrammetric techniques for robust DEM generation were successfully experienced on monostatic repeat-pass SIR-A, SIR-B, SIR-C/X-SAR, ERS1/2, JERS-1, and Radarsat data. However, novel configurations achievable by modern spacecraft flying in formation will allow for the attainment of very large baselines between the antennas in a single-pass bistatic geometry so that the height determination accuracy can benefit from both stereo effect and simultaneous acquisition. Five models for relief reconstruction by monostatic-bistatic SAR stereoradargrammetry are presented, and an error budget is assessed for each of them. Results of the sensitivity analysis exhibit metric accuracy, and therefore, the technique could be applied for height reconstruction as a methodology complementary to SAR interferometry. View full abstract»

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  • Correlation Denormalization in Interferometric or Polarimetric Radiometers: A Unified Approach

    Page(s): 561 - 568
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (470 KB) |  | HTML iconHTML  

    This paper presents a general analysis of correlation measurements in an interferometer or a radiometer based on noise injection and/or switching and measurement of normalized correlations (e.g., imaging synthetic aperture or polarimetric radiometers). A compact unifying notation for denormalizing the measured normalized correlations in the presence of noise injection in one or both of the receiving channels is presented. Technological limitations are also assessed by evaluating the effect of associated approximations. Finally, the approach is validated by experimental results of the measurement and calibration of related front-end nonidealities, namely, the finite isolation of the front-end switch. The methods presented in this paper are illustrated by a thorough analysis of the so-called mixed baselines of microwave imaging radiometer using aperture synthesis, which refer to those baselines which are formed between the regular receivers (light-weight cost-efficient front-end) and the reference radiometers. These baselines require special attention, since the reference radiometers are noise-injection radiometers, which inject noise to the measured signal, whereas the regular receivers are total power receivers. View full abstract»

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  • A Satellite Approach to Estimate Land–Atmosphere \hbox {CO}_{2} Exchange for Boreal and Arctic Biomes Using MODIS and AMSR-E

    Page(s): 569 - 587
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1574 KB) |  | HTML iconHTML  

    Northern ecosystems are a major sink for atmospheric CO2 and contain much of the world's soil organic carbon (SOC) that is potentially reactive to near-term climate change. We introduce a simple terrestrial carbon flux (TCF) model driven by satellite remote sensing inputs from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) to estimate surface (<10-cm depth) SOC stocks, daily respiration, and net ecosystem carbon exchange (NEE). Soil temperature and moisture information from AMSR-E provide environmental constraints to soil heterotrophic respiration (R h), while gross primary production (GPP) information from MODIS provides estimates of the total photosynthesis and autotrophic respiration. The model results were evaluated across a North American network of boreal forest, grassland, and tundra monitoring sites using alternative carbon measures derived from tower CO2 flux measurements and BIOME-BGC model simulations. Root-mean-square-error (rmse) differences between TCF model estimates and tower observations were 1.2, 0.7, and 1.2 g middot C middot m-2 middot day-1 for GPP, ecosystem respiration (Rtot) and NEE, while mean residual differences were 43% of the rmse. Similar accuracies were observed for both TCF and BIOME-BGC model simulations relative to tower results. TCF-model-derived SOC was in general agreement with soil inventory data and indicates that the dominant SOC source for Rh has a mean residence time of less than five years, while R h is approximately 43% and 55% of R tot for respective summer and annual fluxes. An error sensitivity analysis determined that meaningful flux estimates could be derived under prevailing climatic conditions at the study locations, given documented error levels in the remote sensing inputs. View full abstract»

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  • Radiometric Calibration of LIDAR Intensity With Commercially Available Reference Targets

    Page(s): 588 - 598
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1159 KB) |  | HTML iconHTML  

    We present a new approach for radiometric calibration of light detection and ranging (LIDAR) intensity data and demonstrate an application of this method to natural targets. The method is based on 1) using commercially available sand and gravel as reference targets and 2) the calibration of these reference targets in the laboratory conditions to know their backscatter properties. We have investigated the target properties crucial for accurate and consistent reflectance calibration and present a set of ideal targets easily available for calibration purposes. The first results from LIDAR-based brightness measurement of grass and sand show that the gravel-based calibration approach works in practice, is cost effective, and produces statistically meaningful results: Comparison of results from two separate airborne laser scanning campaigns shows that the relative calibration produces repeatable reflectance values. View full abstract»

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  • Qualitative Spatial Reasoning for High-Resolution Remote Sensing Image Analysis

    Page(s): 599 - 612
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1592 KB) |  | HTML iconHTML  

    High-resolution (HR) remote-sensing images allow us to access new kinds of information. Classical techniques for image analysis, such as pixel-based classifications or region-based segmentations, do not allow to fully exploit the richness of this kind of images. Indeed, for many applications, we are interested in complex objects which can only be identified and analyzed by studying the relationships between the elementary objects which compose them. In this paper, the use of a spatial reasoning technique called region connection calculus for the analysis of HR remote-sensing images is presented. A graph-based representation of the spatial relationships between the regions of an image is used within a graph-matching procedure in order to implement an object detection algorithm. View full abstract»

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Aims & Scope

 

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.

 

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Antonio J. Plaza
University of Extremadura