# IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

## Issue 2  Part 3 • April 2013

This issue contains several parts.Go to:  Part 1  | Part 2

## Filter Results

Displaying Results 1 - 25 of 33
• ### [Front cover]

Publication Year: 2013, Page(s): C1
| PDF (514 KB)
• ### IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing publication information

Publication Year: 2013, Page(s): C2
| PDF (137 KB)

Publication Year: 2013, Page(s):757 - 758
| PDF (157 KB)
• ### Neighborhood Preserving Orthogonal PNMF Feature Extraction for Hyperspectral Image Classification

Publication Year: 2013, Page(s):759 - 768
Cited by:  Papers (21)
| | PDF (2391 KB) | HTML

In this paper, we propose a manifold geometry based projective nonnegative matrix factorization linear dimensionality reduction method, called neighborhood preserving orthogonal projective nonnegative matrix factorization (NPOPNMF), for feature extraction of hyperspectral image. By adding constraints on projective nonnegative matrix factorization (PNMF) that each data point can be represented as a... View full abstract»

• ### An Approach for Subpixel Anomaly Detection in Hyperspectral Images

Publication Year: 2013, Page(s):769 - 778
Cited by:  Papers (15)
| | PDF (1674 KB) | HTML

Fast detecting difficult targets such as subpixel objects is a fundamental challenge for anomaly detection (AD) in hyperspectral images. In an attempt to solve this problem, this paper presents a novel but simple approach based on selecting a single feature for which the anomaly value is the maximum. The proposed approach applied in the original feature space has been evaluated and compared with r... View full abstract»

• ### Contextual Subpixel Mapping of Hyperspectral Images Making Use of a High Resolution Color Image

Publication Year: 2013, Page(s):779 - 791
Cited by:  Papers (12)
| | PDF (2511 KB) | HTML

This paper describes a hyperspectral image classification method to obtain classification maps at a finer resolution than the image's original resolution. We assume that a complementary color image of high spatial resolution is available. The proposed methodology consists of a soft classification procedure to obtain landcover fractions, followed by a subpixel mapping of these fractions. While the ... View full abstract»

• ### Non-Uniform Random Feature Selection and Kernel Density Scoring With SVM Based Ensemble Classification for Hyperspectral Image Analysis

Publication Year: 2013, Page(s):792 - 800
Cited by:  Papers (7)
| | PDF (1657 KB) | HTML

Traditional statistical classification approaches often fail to yield adequate results with Hyperspectral imagery (HSI) because of the high dimensional nature of the data, multimodal class distribution and limited ground truth samples for training. Over the last decade, Support Vector Machines (SVMs) and Multi-Classifier Systems (MCS) have become popular tools for HSI analysis. Random Feature Sele... View full abstract»

• ### Analysis and Optimizations of Global and Local Versions of the RX Algorithm for Anomaly Detection in Hyperspectral Data

Publication Year: 2013, Page(s):801 - 814
Cited by:  Papers (16)
| | PDF (3832 KB) | HTML

Anomaly detection is an important task for hyperspectral data exploitation. A standard approach for anomaly detection in the literature is the method developed by Reed and Xiaoli, also called RX algorithm. A variation of this algorithm consists of applying the same concept to a local sliding window centered around each image pixel. The computational cost is very high for RX algorithm and it strong... View full abstract»

• ### A Subspace-Based Change Detection Method for Hyperspectral Images

Publication Year: 2013, Page(s):815 - 830
Cited by:  Papers (21)
| | PDF (5269 KB) | HTML

Remote sensing change detection has played an important role in many applications. Most traditional change detection methods deal with single-band or multispectral remote sensing images. Hyperspectral remote sensing images offer more detailed information on spectral changes so as to present promising change detection performance. The challenge is how to take advantage of the spectral information a... View full abstract»

• ### An Improved FCM Algorithm Based on the SVDD for Unsupervised Hyperspectral Data Classification

Publication Year: 2013, Page(s):831 - 839
Cited by:  Papers (10)
| | PDF (1005 KB) | HTML

Unsupervised classification approaches, also known as “clustering algorithms”, can be considered a solution to problems associated with the supervised classification of remotely sensed image data. The most important of these problems with respect to statistical classification algorithms is the lack of enough high quality training data and high dimensionality of hyperspectral data. In... View full abstract»

• ### Assessment of the Radiometric Performance of Chinese HJ-1 Satellite CCD Instruments

Publication Year: 2013, Page(s):840 - 850
Cited by:  Papers (15)
| | PDF (1763 KB) | HTML

Data from the Chinese Huan-Jin (which means “environment”) 1 satellites, HJ-1A and HJ-1B, have been widely used for environmental, disaster monitoring and other applications. However, the radiometric properties of their CCD sensors have not been well assessed. In this study, we evaluated the radiometric performance of the HJ-1A/B CCD sensors by comparing their top-of-atmosphere (TOA)... View full abstract»

• ### Characterization of Rice Paddies by a UAV-Mounted Miniature Hyperspectral Sensor System

Publication Year: 2013, Page(s):851 - 860
Cited by:  Papers (20)
| | PDF (1956 KB) | HTML

A low-cost, small, lightweight hyperspectral sensor system that can be loaded onto small unmanned autonomous vehicle (UAV) platforms has been developed for the acquisition of aerial hyperspectral data. Safe and easy observation is possible under unstable illumination conditions by using lightweight and autonomous cruising. The hyperspectral sensor system, equipped with a 256-band hyperspectral sen... View full abstract»

• ### Crop Stage Classification of Hyperspectral Data Using Unsupervised Techniques

Publication Year: 2013, Page(s):861 - 866
Cited by:  Papers (17)
| | PDF (760 KB) | HTML

The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has be... View full abstract»

• ### Gaussian Process Retrieval of Chlorophyll Content From Imaging Spectroscopy Data

Publication Year: 2013, Page(s):867 - 874
Cited by:  Papers (27)
| | PDF (1385 KB) | HTML

Precise and spatially-explicit knowledge of leaf chlorophyll content (Chl) is crucial to adequately interpret the chlorophyll fluorescence (ChF) signal from space. Accompanying information about the reliability of the Chl estimation becomes more important than ever. Recently, a new statistical method was proposed within the family of nonparametric Bayesian statistics, namely G... View full abstract»

• ### Retrieval of Forest Biomass From ALOS PALSAR Data Using a Lookup Table Method

Publication Year: 2013, Page(s):875 - 886
Cited by:  Papers (11)
| | PDF (4482 KB) | HTML

Mapping of forest biomass over large area and in higher accuracy becomes more and more important for researches on global carbon cycle and climate change. The feasibility and problems of forest biomass estimations based on lookup table (LUT) methods using ALOS PALSAR data are investigated in this study. Using of the forest structures from a forest growth model as inputs to a three dimensional rada... View full abstract»

• ### Impact of Moisture Distribution Within the Sensing Depth on L- and C-Band Emission in Sandy Soils

Publication Year: 2013, Page(s):887 - 899
Cited by:  Papers (6)
| | PDF (2204 KB) | HTML

The performances of the soil moisture retrieval and assimilation algorithms using microwave observations rely on realistic estimates of brightness temperatures (TB) from microwave emission models. This study identifies circumstances when current models fail to reliably relate near-surface soil moisture to an observed TB at L-band; offers a plausible explanation of the physica... View full abstract»

• ### Toward an Operational Bare Soil Moisture Mapping Using TerraSAR-X Data Acquired Over Agricultural Areas

Publication Year: 2013, Page(s):900 - 916
Cited by:  Papers (12)
| | PDF (3416 KB) | HTML

TerraSAR-X data are processed for an “operational” mapping of bare soils moisture in agricultural areas. Empirical relationships between TerraSAR-X signal and soil moisture were established and validated over different North European agricultural study sites. The results show that the mean error on the soil moisture estimation is less than 4% regardless of the TerraSAR-X configuratio... View full abstract»

• ### Geospatial Strategy for Tropical Forest-Wildlife Reserve Biomass Estimation

Publication Year: 2013, Page(s):917 - 923
Cited by:  Papers (13)
| | PDF (1252 KB) | HTML

This study focus on the biomass estimation of Sariska Wildlife Reserve using forest inventory and geospatial approaches to develop a model based on the statistical correlation between biomass measured at plot level and the associated spectral characteristics. The multistage statistical technique with incorporated the satellite data of IRS P-6 LISS III gives a precise estimation of biomass. Forest ... View full abstract»

• ### Stem Volume and Above-Ground Biomass Estimation of Individual Pine Trees From LiDAR Data: Contribution of Full-Waveform Signals

Publication Year: 2013, Page(s):924 - 934
Cited by:  Papers (14)
| | PDF (3400 KB) | HTML

The diameter at breast height (DBH) is the most extensively measured parameter in the field for estimating stem volume and aboveground biomass of individual trees. However, DBH can not be measured from airborne or spaceborne light detection and ranging (LiDAR) data. Consequently, volume and biomass must be estimated from LiDAR data using other tree metrics. The objective of this paper is to examin... View full abstract»

• ### Characterising Reedbeds Using LiDAR Data: Potential and Limitations

Publication Year: 2013, Page(s):935 - 941
Cited by:  Papers (5)
| | PDF (1992 KB) | HTML

Reedbeds are dominated by a small number of plant species, but are extremely valuable habitats for faunal biodiversity. However, reedbeds often exist in small patches distributed across landscapes and for most regions there is a lack of information about their location and condition. This paper investigates the potential of using LiDAR-derived elevation and intensity data to characterise reedbeds.... View full abstract»

• ### Adaptive Sparse Recovery by Parametric Weighted L$_{1}$ Minimization for ISAR Imaging of Uniformly Rotating Targets

Publication Year: 2013, Page(s):942 - 952
Cited by:  Papers (30)
| | PDF (1729 KB) | HTML

It has been shown in the literature that, the inverse synthetic aperture radar (ISAR) echo can be seen as sparse and the ISAR imaging can be implemented by sparse recovery approaches. In this paper, we propose a new parametric weighted L1 minimization algorithm for ISAR imaging based on the parametric sparse representation of ISAR signals. Since the basis matrix used for sparse represen... View full abstract»

• ### InSAR Local Co-Registration Method Assisted by Shape-From-Shading

Publication Year: 2013, Page(s):953 - 959
Cited by:  Papers (11)
| | PDF (4496 KB) | HTML

Interferometric synthetic aperture radar (InSAR) is a useful technology to observe the earth topography. However, a synthetic aperture radar (SAR) interferogram usually includes a lot of rotational points, that is, singular points (SPs). SPs seriously affect the quality of generated digital elevation model (DEM). One of the dominant origins of the SPs is the local distortion in the co-registration... View full abstract»

• ### Spaceborne 3-D SAR Tomography for Analyzing Garbled Urban Scenarios: Single-Look Superresolution Advances and Experiments

Publication Year: 2013, Page(s):960 - 968
Cited by:  Papers (15)
| | PDF (1488 KB) | HTML

Synthetic Aperture Radar Tomography (Tomo-SAR) is an emerging experimental “coherent data combination” mode allowing unprecedented full 3-D imaging of complex urban and infrastructure scenarios with layover (“garbled”) scatterers, exploiting multibaseline interferometric SAR data stacks. Various approaches have been proposed to improve Fourier-based Tomo-SAR elevation b... View full abstract»

• ### Alphabet-Based Multisensory Data Fusion and Classification Using Factor Graphs

Publication Year: 2013, Page(s):969 - 990
Cited by:  Papers (3)
| | PDF (6234 KB) | HTML

The way of multisensory data integration is a crucial step of any data fusion method. Different physical types of sensors (optic, thermal, acoustic, or radar) with different resolutions, and different types of GIS digital data (elevation, vector map) require a proper method for data integration. Incommensurability of the data may not allow to use conventional statistical methods for fusion and pro... View full abstract»

• ### Adaptive Window Size Estimation in Unsupervised Change Detection

Publication Year: 2013, Page(s):991 - 1003
Cited by:  Papers (2)
| | PDF (3014 KB) | HTML

Many problems related to change detection require to compute image features on local windows. Such features usually combine in each pixel locations spectral values (luminance) associated with some spatial properties, such as texture features or more advanced local relationships between pixels. Therefore, as far as local windows are considered, the optimal size selection is a key point for the perf... View full abstract»

## Aims & Scope

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS) addresses current issues and techniques in applied remote and in situ sensing, their integration, and applied modeling and information creation for understanding the Earth.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Dr. Qian (Jenny) Du
Mississippi State University