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Forest height is a key measurement for determining aboveground carbon in forests and forest biomass. DLR's TANDEM-X mission provides paired scenes that can be used for forest height measurement. We have demonstrated this in [1,2,3] for scenes with some moderate topography. This paper discusses issues for estimating forest canopy heights in mountainous terrain. Multiple dates and baselines of TanDEM-X...
This study aims to evaluate the potential of coherent change detection using multi-temporal polarimetric interferometric SAR data. One of the limitations in damage area extraction is that the decorrelation caused by the disaster is commonly coupled with the natural changes. Also, the interpretation of the coherence is troublesome and requires the coherence model. The approach used in this study is...
Hyperspectral unmixing frameworks are ultimately designed to understand and quantify the actual distribution of endmembers in a given scene. Assessing the percentage of each material is typically cumbersome, especially in images characterized by complex combinations of spectral signatures. In this work, we present a nonlinear programming scheme that aims at providing direct estimation of the endmembers...
Unsupervised manifold learning has become accepted as an important tool for reducing dimensionality of a data set by finding its meaningful low dimensional representation lying on an unknown nonlinear subspace. Most manifold learning methods only embed an existing data set, but do not provide an explicit mapping function for novel out-of-sample data, thereby potentially resulting in an ineffective...
The accurate assessment of chlorophyll-a concentration in turbid coastal waters by means of remote sensing is quite challenging. In this study, a semi-analytical approach is used to analyze the mathematical relationship between chlorophyll-a concentration and remote sensing reflectance. Through evaluation by field measurements, it is shown that our model produces 31.4% uncertainty in quantifying chlorophyll-a...
Synthetic aperture radar (SAR) data are becoming more and more accessible and have been widely used in many applications. To effectively and efficiently represent multiple SAR images, we propose the mixture of Itakura-Saito (IS) divergence for non-negative matrix factorization (NMF) to perform the dimension reduction. Our proposed method incorporates the unit-mean Gamma mixture model into the NMF...
Ship category recognition is one of the remote sensing applications that requires designing accurate image representation and classification models. Training these models is usually a data hungry process, that requires a lot of labeled data which are usually scarce and expensive. As unlabeled data are more abundant and relatively cheaper, transductive methods exploiting these data are highly preferred...
This study investigated the efficacy of fusing simulated Global Ecosystem Dynamics Investigation (GEDI) lidar data with TanDEM-X (TDX) single-polarized InSAR data for the estimation of forest structure over a coniferous Forest — Teakettle Experimental Forest (TEF). Simulated GEDI canopy heights were used to constrain the unknown parameter of a widely-used SAR scattering model — Random Volume over...
In this paper, we present a method for fusing different frequency synthetic aperture radar (SAR) images for improving the accuracy of land subsidence estimation using differential interferometric SAR (DInSAR) technique. Our study area, Kansai International Airport, Osaka, Japan, consists of two landfilled islands, and the subsidence velocity of an island is much larger than that of the other one....
We applied the Numerical Maxwell Model in 3 Dimensions (NMM3D) to radar scattering from ocean surfaces at L band. The formulation is based on the PMCHWT surface integral equation which uses separate Green's functions for air and ocean permittivities. The Sparse Matrix Canonical Grid (SMCG) is used to compute Method of Moments (MoM) solutions in conjunction with Rao-Wilton-Glisson (RWG) basis functions...
A simple target scattering model is developed integrating the shape factor and geometric randomness that are less influenced by the SAR configuration, dielectric properties of crop, and the underlying soil conditions, to describe the shape and statistical distribution of the targets, respectively. 47 fully polarimetric RADARSAT-2 images in FQ1W, FQ6W, FQ10W, FQ15W and FQ19W modes with different incidence...
While there is growing interest in implementing future NASA Earth Science missions as Distributed Spacecraft Missions (DSMs), there are currently very few tools available to help in the design of DSMs. The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. Our Trade-space Analysis Tool...
Traditionally, Radiative Transfer (RT) formulation has been used to simulate scattering from snow layer with the incorporation of phase matrix of scatterers in the formulation. Typically, spherical scatterers were assumed to represent the ice particles embedded inside the air medium and Mie phase matrix was applied. However, the real scatterers in the actual snow are generally more irregular than...
Approximate radiative transfer model solutions have been developed by Hapke [1][2]. Important geophysical parameters such as density and grain size distribution play an important role in parameterizing these solutions, however the radiative transfer solutions are typically nonlinear functions of these important parameters. We have developed a method which isolates single scattering properties of the...
In this work, the problem of developing algorithms that automatically infer information about small-scale solar photovoltaic (PV) arrays in high resolution aerial imagery is considered. Such algorithms potentially offer a faster and cheaper solution to collecting small-scale PV information, such as their location and capacity. Existing work on this topic has focused on the automatic identification...
SAR image segmentation is the pre-process for SAR image application. This paper presents a new SAR image segmentation algorithm combining both the the bias field and Markov random field(MRF) characteristic with fuzzy clustering model(FCM) called BMFCM. The MRF characteristic of an image includes the spatial information of the image and the bias filed estimation is introduced to deal with the grey...
This paper presents a new method for extracting urban roadside trees automatically from mobile laser scanning point clouds. This method mainly includes three steps. First, ground point clouds are removed by voxel-based upward growing method. Second, Euclidean distance segment method is used to cluster non-ground point clouds into certain individual objects. Then crown seeds of the initial layer is...
In this article, we compare three change detection methods for hyperspectral imagery and establish their sensitivity to registration mismatch. We further present metrics that enable this comparison and seek to rank the methods.
In this paper the Two-Scale Model has been used to derive the theoretical Normalized Radar Cross Section (NRCS) for sea clutter in the L-band, taking into account also the circular polarization of GPS signals. Using this theoretical model and the theoretical formula for NRCS, authors aim to investigate the possibility to extend target detection through GPS signals in backscattering configuration by...
An adaptive speckle reduction algorithm for Polarimetric SAR (PolSAR) data, based on the combination of Gaussian Markov Random Field (GMRF) and Wavelet Edge Detection (WED) is proposed in this paper. The algorithm has three major steps: (a) first-time speckle reduction based on the GMRF model, (b) detail preservation using a WED approach, and (c) second-time speckle reduction using a least square...
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