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In this paper, we propose a multiple line extraction method from multimodal data points in high dimensional space. It can sparsely represent multimodal sensor network data by utilizing high correlation among channels in the data. We exploit the idea of Color Lines, which is a model using high correlation among RGB channels in computer vision. It represents real color images as a collection of multiple...
Visible Infrared Imaging Radiometer Suite (VIIRS) land surface albedo (LSA) product is one of the routinely generated VIIRS environmental data records (EDR). A direct estimation approach based on radiative transfer simulation was developed to directly estimate instantaneous LSA value from VIIRS clear-sky top-of-atmosphere (TOA) reflectance. Comprehensive validations and evaluations were performed...
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...
Spectral Unmixing is a challenging and absorbing problem. Unmixning allows us to break down a pixel's composition into its material components. Many avenues of spectral unmixing have been attempted with considerable success. One such avenue is to frame the spectral unmixing problem as an Estimation-Measurement problem and avail the use of the well-known Kalman Filter (KF) technique. Two such recent...
Sparse unmixing of hyperspectral data is an important technique which aims at estimating the fractional abundances of endmembers (pure spectral components). It is well known that enforcing sparseness becomes a necessary process in sparse unmixing methods. To better exploit the sparsity in hyperspectral imagery, a double reweighted sparse unmixing algorithm has been proposed. However, it focusses on...
We propose to use the temporal coherence of a time series to extract using Vertex Component Analysis (VCA) the suitable set of endmembers for each scene. The reconstruction error computed on the two previous scenes for each date is used to constrain the selection of the set of endmembers produced by VCA. Snow cover estimation is considered as application. We tested different approaches for abundance...
High resolution sea ice drift fields, the location and extend of converging and diverging zones as well as ice ridges are most important parameters for ship navigation in ice infested waters. In this paper, we present the prototype of a new processor which is aimed to derive the surface ice parameters on the basis of pairs of space-borne Synthetic Aperture Radar (SAR) data of the same and of different...
Nonlinear spectral unmixing based on the bilinear mixture models has received much attention recently. In this paper, an abundance estimation algorithm based on the geometric characteristics of bilinear mixture models is proposed. By representing the models' bilinear terms as the linear contribution of an extra vertex that concentrates the common nonlinear mixing effect, solving the complex bilinear...
Establishing causal relations between random variables from observational data is perhaps the most important challenge in today's Science. In remote sensing and geosciences this is of special relevance to better understand the Earth's system and the complex and elusive interactions between processes. In this paper we explore a framework to derive cause-effect relations from pairs of variables via...
The synergistic analysis of light detection and ranging (LiDAR) and hyperspectral data is attracting a significant interest in recent years due to the complementary nature of these two sources of remote sensing data. In this paper, we propose a new spectral-spatial classification method able to jointly exploit these two kinds of data. Our work is based on three innovative components: 1) a superpixel...
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...
TanDEM-X forms together with TerraSAR-X the first single-pass polarimetric interferometer in space. This allows for the first time the acquisition and analysis of Single-, Dual-, and Quad-Pol-InSAR data without the disturbing effect of temporal decorrelation globally. For this reason, the exploration of TanDEM-X data for forestry is constantly increasing especially concerning forest height estimation,...
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....
This paper focuses on the spectral unmixing technique for analyzing hyperspectral image (HSI). In this paper, we first prove that the reconstruction errors and the abundance anomalies (AAs, abundances that are negative or greater than one) are effective in measuring the purity of pixels. Then, due to the continuity of the objects in the space, the endmembers are assumed to be located at some noticeable...
This paper investigates the problem of glacier flow estimation using Synthetic Aperture Radar (SAR) image data. Our motivation is to exploit a weighted graph model constructed from characteristic points (i.e. keypoints) to measure the displacement vectors located at their positions. In fact, characteristic points are capable of capturing the image's radiometric and contextual information. Then, by...
Normalized Difference Vegetation Index (NDVI) time series is used to study different land cover dynamics such as change, compare vegetation dynamics between years and analyze intra-annual components. A nonlinear cosine model of the NDVI time series with a constant frequency is used to account for the time-varying nature of the land cover parameters due to seasonality or change. The Extended Kalman...
Target detection experiments with a novel non-parametric detector are carried out exploiting the availability of a new hyperspectral data set featuring a suburban scene with several different targets. Benefiting from its non-parametric nature and from its data adaptivity deriving from the variable-bandwidth approach, the detector is shown to provide promising results for the detection of the targets...
Estimating the characteristics of the snow cover is essential for managing hydroelectric dams and forecasting rises in water level in the spring. For the estimation of the Snow Water Equivalent (SWE) at fine scale and to make connections with the hydrology of small watershed, it is necessary to turn towards active microwave sensors like Synthetic Aperture Radar (SAR). This paper gives an overview...
Based on an empirical model without wind direction input for the retrieval of C-band HH-polarization wind speed, we propose a modified model for wind speed estimation in VV-polarization. The obtained wind speed is then applied for the CMOD5.N to estimate wind directions. The comparisons with the scatterometry-based approach demonstrate that the estimated wind speed by the proposed model is closer...
Starting from a stack of co-registered SAR images in interferometric configuration, SAR tomography performs a reconstruction of the reflectivity of scatterers in 3-D. Several scatterers observed within the same resolution cell of each SAR image can be separated by jointly unmixing the SAR complex amplitude observed throughout the stack. To achieve a reliable tomographic reconstruction, it is necessary...
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