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Geoscience and Remote Sensing Letters, IEEE

Issue 2 • Date March 2012

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Displaying Results 1 - 25 of 40
  • [Front cover]

    Page(s): C1
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  • IEEE Geoscience and Remote Sensing Letters publication information

    Page(s): C2
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  • Table of contents

    Page(s): 149 - 150
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  • Discriminative Feature Selection for Automatic Classification of Volcano-Seismic Signals

    Page(s): 151 - 155
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (399 KB) |  | HTML iconHTML  

    Feature extraction is a critical element in automatic pattern classification. In this letter, we propose different sets of parameters for classification of volcano-seismic signals, and the discriminative feature selection (DFS) method is applied for selecting the minimum number of features containing most of the discriminative information. We have applied DFS to a conventional cepstral-based parameterization (with 39 features) and to an extended set of parameters (including 84 features). Classification experiments using seismograms recorded at Colima Volcano (Mexico) show that, for the most complex classifier and using the cepstral-based parameterization, DFS provided a reduction of the error rate from 24.3% (using 39 features) to 15.5% (ten components). When DFS is applied to the extended parameterization, the error rate decreased from 27.9% (84 features) to 13.8% (14 features). These results show the utility of DFS for identifying the best components from the original feature vector and for exploring new parameterizations for the classification of volcano-seismic signals. View full abstract»

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  • An Unsupervised Evaluation Method for Remotely Sensed Imagery Segmentation

    Page(s): 156 - 160
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (369 KB) |  | HTML iconHTML  

    Image segmentation is a critical step in the analysis of high-spatial-resolution remotely sensed imagery using object-based image analysis. The segmentation quality is extremely important to the subsequent analysis. This letter proposes an improved unsupervised method to evaluate the segmentation quality for remotely sensed imagery. The evaluation criteria take into account global intrasegment homogeneity and intersegment heterogeneity measures, which can be useful for the comparison of segmentation results produced by a single segmentation method. The proposed method is compared with other two mature unsupervised evaluation methods on two segmentation methods: region growing and mean shift. QuickBird images are used for the comparative study. The effectiveness of the proposed method is validated through comparing with the supervised evaluation method Rand Index and visual analysis. View full abstract»

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  • Endmember Extraction Using a Combination of Orthogonal Projection and Genetic Algorithm

    Page(s): 161 - 165
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (248 KB) |  | HTML iconHTML  

    Common endmember extraction algorithms presume that the number of materials present is either known or may be predetermined by using spectral databases or other approaches. In this letter, we propose a new method called genetic orthogonal projection (GOP) for endmember extraction in imaging spectrometry. GOP is based on a fully unsupervised approach and uses convex geometric characteristics as well as a genetic algorithm. We compare GOP with existing endmember extraction algorithms and demonstrate that GOP partially outperforms them, without the need of a priori information. View full abstract»

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  • Four-Component Scattering Power Decomposition With Extended Volume Scattering Model

    Page(s): 166 - 170
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (486 KB) |  | HTML iconHTML  

    In the three- or four-component decompositions, polarimetric scattering properties and corresponding physical scattering models play essential roles for power decomposition. This letter proposes an improved four-component scattering power decomposition method that employs a suitable volume scattering model for single- or double-bounce scattering in the polarimetric synthetic aperture radar image analysis. The cross-polarized HV component is created by both single-bounce object (such as vegetation) and double-bounce structures (such as oriented building blocks). It has been difficult to discriminate these two objects (vegetation against oriented buildings) in the decomposed images since the HV component is assigned to the volume scattering due to vegetation only. We propose to extend the volume scattering model suited for two physical scattering models. It is shown that a vegetation area and an oriented urban building area are well discriminated compared to those resulting from the implementation of the existing four-component scattering power decomposition. View full abstract»

    Open Access
  • Multilevel SIFT Matching for Large-Size VHR Image Registration

    Page(s): 171 - 175
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (659 KB) |  | HTML iconHTML  

    A fast approach is proposed in this letter for large-size very high resolution image registration, which is accomplished based on coarse-to-fine strategy and blockwise scale-invariant feature transform (SIFT) matching. Coarse registration is implemented at low resolution level, which provides a geometric constraint. The constraint makes the blockwise SIFT matching possible and is helpful for getting more matched keypoints at the latter refined procedure. Refined registration is achieved by blockwise SIFT matching and global optimization on the whole matched keypoints based on iterative reweighted least squares. To improve the efficiency, blockwise SIFT matching is implemented in a parallel manner. Experiments demonstrate the effectiveness of the proposed approach. View full abstract»

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  • Numeric Image Features for Detection of Aurora

    Page(s): 176 - 179
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (353 KB) |  | HTML iconHTML  

    The electromagnetic coupling of the solar wind, Earth's magnetic field, and the upper atmosphere allows us to study the near-Earth space phenomena by monitoring the auroral displays in the polar regions. Ground-based networks facilitate spatial and temporal resolutions that are not possible with satellite instruments-they also produce enormous amounts of data to be stored and processed. While automated image analysis methods for auroral research are beginning to emerge, the normal approach is to visually examine images and then manually label and sort the data. We revisit a key question concerning the existence of aurora in an image: Not all images contain auroral light, and the visibility to the upper atmosphere depends on cloud cover. Detection of aurora is a fundamental step to limit further processing to only those images that are of interest. We quantitatively evaluated a selection of numeric image features that have been used in earlier studies and assess a brightness-invariant feature. We achieved error rates around 6%-8% with subsecond execution times. To the best of our knowledge, we are the first to report results in classifying auroral images where the Moon is allowed to be visible. View full abstract»

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  • Surface Emissivity Retrieval From Airborne Hyperspectral Scanner Data: Insights on Atmospheric Correction and Noise Removal

    Page(s): 180 - 184
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (509 KB) |  | HTML iconHTML  

    Airborne multispectral imagers have been used in validation campaigns in order to acquire very high spatial resolution data as a benchmark for current or future satellite data. Imagery acquired with such sensors implies specific data processing in relation to view-angle-dependent atmospheric correction and removal or minimization of stripping-based noise. It is necessary to appropriately perform this processing in order to benefit from reference imageries of surface temperature (T) and emissivity (ε) maps retrieved from thermal infrared data. In particular, ε images generated from T/ε separation algorithms show undesirable noise that jeopardizes their photointerpretation. This letter addresses the following: 1) the removal of view-angle-dependent atmospheric effects by using ratio techniques for deriving atmospheric water vapor content in a pixel-by-pixel basis and atmospheric radiative transfer simulations to construct lookup tables (LUTs) and 2) the removal of image stripping using maximum/minimum noise fraction (MNF) transforms. For this purpose, imagery acquired with the Airborne Hyperspectral Scanner (AHS) sensor has been used. Results show that angular effects in the atmospheric correction can be addressed from AHS-derived water vapor content and LUTs, whereas due to the AHS noise specific characteristics, the MNF transform only removed part of the noise. View full abstract»

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  • Statistical Edge Detection in Urban Areas Exploiting SAR Complex Data

    Page(s): 185 - 189
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (809 KB) |  | HTML iconHTML  

    The aim of building edge detection is to obtain a map of man-made structure edges of the investigated scene. Different detectors have been developed exploiting synthetic aperture radar (SAR) data, based on the use of the reflectivity difference (working with SAR amplitude images) or of the phase difference (working with SAR interferometric images) between neighboring pixels. In this letter, a novel approach using jointly both the amplitudes and the interferometric phase of two complex SAR images is proposed, based on the hypothesis that information related to building edges can be retrieved in the two data domains. The technique is based on stochastic estimation theory, exploiting, in particular, Markov random fields. Compared to classical amplitude-based edge detectors and to phase-based ones, the proposed method shows an improvement in terms of detection accuracy, false alarm rate, and building shape recovery. The algorithm has been tested and analyzed using simulated data and validated on L-band and X-band real data sets. View full abstract»

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  • Application of Subband Spectral Cancellation for SAR Narrow-Band Interference Suppression

    Page(s): 190 - 193
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (480 KB) |  | HTML iconHTML  

    Narrow-band interference (NBI) suppression is an important technique in the low-frequency synthetic aperture radar (SAR). NBI sources either intentional or unintentional can mask the SAR signals and cause image degradation. According to the different characteristics of the spectra between the NBI and the SAR signals, a new method using subband spectral cancellation is applied to suppress the NBI. In contrast to the conventional suppression method performed on the raw data, this letter deals with the focused SAR image. By subtracting different range subband spectra of the SAR image, the NBIs are obtained and cancelled. The proposed method does not need to detect and estimate the parameters of the NBI and is easy to put in practice. Its performance is tested on the real data acquired by an experimental SAR system at P-band. View full abstract»

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  • Area Partitioning for Channel Network Extraction Using Digital Elevation Models and Remote Sensing

    Page(s): 194 - 198
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (682 KB) |  | HTML iconHTML  

    Digital elevation models (DEMs) have been widely used in drainage network extraction; however, DEM-based methods often experience challenges in flat areas, where remote sensing imagery is usually informative. This letter proposes an idea of area partition in drainage network extraction. The entire study area is partitioned based on the number of maximum elevation gradients (MEGs). Areas with multiple MEGs (MMEGs) normally include flat areas and, therefore, can be problematic when using DEM-based methods. Remote sensing information can be used together with DEMs to extract drainage networks in these areas. On the contrary, drainage networks can be well defined solely from DEMs in single MEG areas. In a case study, the area partition strategy has been applied and tested in the Yarlung Tsangpo River basin in the southern region of the Tibetan Plateau. Validated using a manually interpreted channel network from high-resolution data sets, this approach generated a nonbroken channel network covering 98.0% of the reference network. These results show that applying remote sensing information only in MMEG areas performs better than throughout the entire study area. View full abstract»

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  • Signal-to-Noise Ratio Equalization for TOPSAR Mode Using a Nonuniform Steering Rate

    Page(s): 199 - 203
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (640 KB) |  | HTML iconHTML  

    In this letter, an optimized scanning in terrain observation by progressive scan synthetic aperture radar (TOPSAR) mode is studied. A nonuniform steering rate of the radar array antenna in the along-track direction is proposed in order to obtain constant radiometric sensitivity and signal-to-noise ratio. This is achieved owing to the longer integration time of the echoes received at both ends of the antenna azimuth sweep. By optimizing iteratively the array discrete steering rate law, the radiometric impact of the array basic element pattern (subarray pattern) can be accurately compensated. First, simulation results are presented to validate the nonuniform steering TOPSAR. View full abstract»

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  • Superconvergent Velocity Estimator for an Autofocus Coherent MapDrift Technique

    Page(s): 204 - 208
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (343 KB) |  | HTML iconHTML  

    A new precise estimator for use in along-track velocity parameter estimation is presented in this letter. The proposed solution effectively determines flight parameters without using an iterative procedure for the autofocus coherent MapDrift (CMD) algorithm. The CMD technique is a coherent method allowing flight parameters to be determined more precisely than in another well-known autofocus noncoherent parametric technique known as classical MD. The proposed novel superconvergent coherent algorithm enables the fast focusing of synthetic aperture radar images using only one iteration of an autofocus procedure. This method can be successfully used in real-time applications for Earth imaging and the estimation of the parameters of ground moving targets. View full abstract»

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  • C-Band Radiometric Response to Rainfall Events in the Subtropical Chaco Forest

    Page(s): 209 - 213
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (683 KB) |  | HTML iconHTML  

    In this letter, multitemporal signatures collected by Advanced Microwave Scanning Radiometer (AMSR-E) over the dry forest of Chaco, located in North Argentina, are analyzed. The forest has a biomass of about 100 t/ha and a woody volume of about 120 m3/ha. A clear increase of polarization index at C-band is observed after intense rain events in two different locations. Simulations of a discrete model attribute this effect to variations of soil moisture and predict an effect comparable with the measured one. Results indicate that there is a potential to monitor soil moisture variations below dry forests with moderate biomass, also in view of the forthcoming availability of L-band data. View full abstract»

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  • Anisotropic Inpainting of the Hypercube

    Page(s): 214 - 218
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (695 KB) |  | HTML iconHTML  

    Airborne pushbroom sensors produce images by acquiring scenes on a line-per-line basis. Depending on the motions of the aircraft carrying the sensor, the line integration time, and the targeted spatial resolution, missing areas may appear on geocorrected images. Missing pixels in geocorrected images are usually tackled by means of interpolation methods, such as nearest neighbor, but these cause visible artifacts that affect the visual quality of the result and also the performance of processing methods working on geocorrected images. We propose the use of an anisotropic diffusion inpainting method specifically devised for hyperspectral images, show some extreme examples, and discuss its convenience. View full abstract»

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  • An Accurate Phase Unwrapping Algorithm Based on Reliability Sorting and Residue Mask

    Page(s): 219 - 223
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1178 KB) |  | HTML iconHTML  

    An accurate phase unwrapping algorithm is presented for reconstructing the true phase field for deformation interferograms. This algorithm is a combination of reliability sorting and residue mask, while introducing more reliable unwrapping fiducial information. In tests conducted with a pyramidal phase image, a complex simulated interferogram, and a real deformation interferogram, the proposed algorithm successfully unwraps the images with perfect precision. This algorithm is also shown to be superior to the prevailing improved Goldstein's residue-cut algorithm in terms of precision. View full abstract»

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  • Low-Complexity Compression Method for Hyperspectral Images Based on Distributed Source Coding

    Page(s): 224 - 227
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (332 KB) |  | HTML iconHTML  

    In this letter, we propose a low-complexity discrete cosine transform (DCT)-based distributed source coding (DSC) scheme for hyperspectral images. First, the DCT was applied to the hyperspectral images. Then, set-partitioning-based approach was utilized to reorganize DCT coefficients into waveletlike tree structure and extract the sign, refinement, and significance bitplanes. Third, low-density parity-check-based Slepian-Wolf (SW) coder was adopted to implement the DSC strategy. Finally, an auxiliary reconstruction method was employed to improve the reconstruction quality. Experimental results on Airborne Visible/Infrared Imaging Spectrometer data set show that the proposed paradigm significantly outperforms the DSC-based coder in wavelet transform domain (set partitioning in hierarchical tree with SW coding), and its performance is comparable to that of the DSC scheme based on informed quantization at low bit rate. View full abstract»

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  • A Fast Back-Projection Algorithm Based on Cross Correlation for GPR Imaging

    Page(s): 228 - 232
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (467 KB) |  | HTML iconHTML  

    In ground-penetrating radar imaging, the classic back-projection (BP) algorithm has an excellent reputation for imaging in layered mediums with convenience and robustness. However, the classic BP algorithm is time consuming and with a lot of artifacts, which have adverse effects on the following work like detection and recognition. A novel BP algorithm, which is both fast and with good effect of suppressing artifacts, is proposed in this letter. At first, an approved approximation method is used to calculate the position of refraction point with remarkable speed and satisfactory accuracy. Then, a lookup table is used to reduce the redundancy in classic BP algorithm. In order to achieve effective artifact suppression, a cross-correlation-based method is introduced. Experimental results of field data present the superiority of the proposed BP algorithm over its classic counterpart both in operation speed and artifact suppression. View full abstract»

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  • Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records

    Page(s): 233 - 236
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (604 KB) |  | HTML iconHTML  

    An intercalibration between F13 Special Sensor Microwave Imager (SSMI) and F17 Special Sensor Microwave Imager Sounder (SSMIS) sea ice extents and areas for a full year of overlap is undertaken preparatory to extending the 1979-2007 National Aeronautics and Space Administration (NASA) Goddard Space Flight Center NASA Team algorithm time series of global sea ice extents and areas. The 1979-2007 time series was created from Scanning Multichannel Microwave Radiometer (SMMR) and SSMI data. After intercalibration, the yearly mean F17 and F13 difference in northern hemisphere (NH) sea ice extents is - 0.0156%, with a standard deviation (SD) of the differences of 0.6204%, and the yearly mean difference in NH sea ice areas is 0.5433%, with an SD of 0.3519%. For the southern hemisphere, the yearly mean difference in sea ice extents is 0.0304% ±0.4880%, and the mean difference in sea ice areas is 0.1550% ±0.3753%. This F13/F17 intercalibration enables the extension of the 29-year 1979-2007 SMMR/SSMI sea ice time series for as long as there are stable F17 SSMIS brightness temperatures available. View full abstract»

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  • Sensitivity Calculations for Poisson's Equation via the Adjoint Field Method

    Page(s): 237 - 241
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (150 KB) |  | HTML iconHTML  

    Adjoint field methods are both elegant and efficient for calculating sensitivity information required across a wide range of physics-based inverse problems. In this letter, we provide a unified approach to the derivation of such methods for problems whose physics are provided by Poisson's equation. Unlike existing approaches in the literature, we consider in detail and explicitly the role of general boundary conditions in the derivation of the associated adjoint-field-based sensitivities. We highlight the relationship between the adjoint field computations required for both gradient decent and Gauss-Newton approaches to image formation. Our derivation is based on standard results from vector calculus coupled with transparent manipulation of the underlying partial different equations, thereby making the concepts employed in this letter easily adaptable to other systems of interest. View full abstract»

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  • First Demonstration of Agriculture Height Retrieval With PolInSAR Airborne Data

    Page(s): 242 - 246
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1019 KB) |  | HTML iconHTML  

    A set of three quad-pol images acquired at the L-band in interferometric repeat-pass mode by the German Aerospace Center (DLR) with the Experimental SAR (E-SAR) system, in parallel with the AgriSAR2006 campaign, has been used to provide, for the first time with airborne data, a demonstration of the retrieval of vegetation height from agricultural crops by means of polarimetric SAR interferometry (PolInSAR)-based techniques. Despite the low frequency of the data, hence providing a weak response from the vegetation volume in contrast to the ground, accurate estimates of vegetation height at field level have been obtained over winter rape and maize fields. The same procedure does not yield valid estimates for wheat, barley, and sugar beet fields due to a mismatch with the physical model employed in the inversion and to the specific crop condition at the date of acquisition. These results show the value of the information provided by both interferometry and polarimetry for some agriculture monitoring practices. View full abstract»

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  • SAR Target Analysis Based on Multiple-Sublook Decomposition: A Visual Exploration Approach

    Page(s): 247 - 251
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (882 KB) |  | HTML iconHTML  

    The advent of submeter-resolution synthetic aperture radar (SAR) images from satellites such as TerraSAR-X has given a new dimension to SAR image understanding. Even though emphasis is always on discovering automatic means of target characterization, visual exploration of targets and objects is the first step in many applications. While considering the complex-valued SAR images, visual inspection of the targets in an image may provide incomplete and misleading information, as sometimes two entirely different behaving objects look quite similar in SAR images. Thus, a need was felt to develop a methodology to support visual target recognition and analysis. In this letter, we present a method which looks into the complex-valued spectrum of SAR images, thus allowing a detailed physical interpretation of the scattering behavior of objects. The presented method is a joint time-frequency analysis method based on sublook decomposition. With the presented results, we emphasize the use of complex-valued SAR images for target characterization, the use of which is primarily restricted to polarimetric and interferometric applications as of now. View full abstract»

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  • Technical Implementation of SMOS Data in the ECMWF Integrated Forecasting System

    Page(s): 252 - 256
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (727 KB) |  | HTML iconHTML  

    The launch of the Soil Moisture and Ocean Salinity (SMOS) satellite of the European Space Agency opens the way to using a new type of satellite data that are very sensitive to soil moisture for numerical weather prediction. The European Centre for Medium-Range Weather Forecasts (ECMWF) has developed an operational chain which makes it possible to process SMOS data in near real time (NRT) and compare it with a model equivalent. This process has been very challenging. The main reasons are the particular characteristics of the SMOS observation system and the large volume of data. Despite these obstacles, SMOS data are being processed successfully in NRT within the ECMWF Integrated Forecasting System (IFS). The ultimate objective is to assimilate these data in the IFS. It is expected to have an impact on the weather forecast at short and medium ranges. Prior to assimilation experiments, the quality of the data has to be assessed. This can be done through monitoring activities. Monitoring is a routine task performed with all satellite data, and among other things, it makes it possible to localize temporal (or spatial) bias or drifts in the data, thus providing NRT reports to the calibration and validation teams, which can act accordingly. In this letter, the implementation of SMOS data in the ECMWF IFS for monitoring purposes is discussed. The system was developed using a simulated file for the NRT processor, and it was tested using real data from the first year since the launch date. View full abstract»

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Aims & Scope

IEEE Geoscience and Remote Sensing Letters (GRSL) is a monthly publication for short papers (maximum length 5 pages) addressing new ideas and formative concepts in remote sensing as well as important new and timely results and concepts.

 

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Meet Our Editors

Editor-in-Chief
Alejandro C. Frery
Universidade Federal de Alagoas