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Automatic recognition of single trees in remote sensing data is an important research topic in the context of sustainable forest management: In many countries, single-tree related parameters are used as a basis for forest inventory, e.g. tree species, mean tree height or timber volume. Until now, the majority of these parameters are collected manually by measurement of sample plots in cost- and time-intensive...
Spectral estimation is considered in the paper as an additional instrument towards a better understanding of the physical phenomena behind the layover scattering decomposition. A super-resolution technique is employed to derive the fringe frequencies characterizing the layover portion. Due to the limited estimation support, only the dominant frequency is found to be reliable information. The non-linear...
Synthetic Aperture Radar Interferometry (InSAR) allows the generation of Digital Elevation Models (DEMs) exploiting the phase difference (interferogram) of SAR data pairs relevant to the same illuminated area and received by slightly different look angles. Within the processing chain leading from the acquired SAR data pair to the final InSAR DEM, it is necessary to calculate a proper phase offset...
This paper deals with the fusion of TanDEM-X raw DEMs in ascending and descending pass over Mumbai test area and enhance its quality. Before applying fusion method, a robust layover and shadow map has been calculated in ITP using TanDEM-X DEM and the corresponding slant range image. The selection of optimum weights for fusion has been based on height error map calculated from interferometric coherence...
This paper presents a new integrated InSAR phase filtering and unwrapping method based on a Markov Random Field model. This approach aims to estimate the noise free unwrapped phase from the observed noisy interferogram. The phase image is modeled using MRF where the correponding energy function is defined. This fuctional contains two parts: the first part is dedicated to the interferogram filtering...
Speckle noise represents one of the main components of the multidimensional SAR signal that limit the complete exploitation of multidimensional SAR data, and polarimetric SAR data in particular. This paper consider the main trends in the characterization and the filtering of the multidimensional Speckle noise component.
Radiative transfer (RT) models were used to simulate reflectance at TM bands and radar beckscattering coefficients at L-bands at acquisition conditions of LANDSAT and PALSAR on the acquisition dates. The forest stands aged from 5 to 250 years simulated from a forest growth model ZELIG at test sites were used to feed the RT models to build a look-up table. A simulated optical and SAR dataset was first...
Tree species composition is an indicator of forest type. It is also a required attribute in forest inventory, biomass and stand volume estimation. Accurate mapping tree species is essential for forest management purposes. In this paper the performances of LiDAR, RapidEye data, and their combination on tree species classification were investigated in a boreal forest. Both Random forest (RF) and support...
Gross primary productivity is an excellent metric of how much forests act as carbon dioxide sinks but currently have up to 40% uncertainty in their global estimates. A large proportion of the uncertainty has been attributed to artifacts in the sun-sensor geometry of monolithic spacecrafts leading to insufficient sampling of the bi-directional reflectance of vegetation. This paper proposes to use small...
The objective of the project reported in this paper was to study land use change over a period of 23 years using Landsat satellite images using a methodology based on territorial transformation. An analysis of land use change was realized from 1997 to 2000 in the municipality of Texcoco in Central Mexico. The analysis unit was determined by landscape, since modifications that have taken place over...
We address a new approach for enhanced microwave remote sensing (RS) imaging via performing the imaging system kernel point spread function (PSF) operator refinement-based multi-scale iterative reconstructive (MSIR) image post-processing, as required for emerging feature enhanced RS missions. The high-resolution (HR) image is first reconstructed from the initial low-resolution (LR) image employing...
An intelligent post-processing computational paradigm based on the use of dynamical filtering techniques modified to enhance the quality of reconstruction of remote sensing signatures based on SPOT-5 imagery is proposed. As a matter of particular study, a robust algorithm is reported for the analysis of the dynamic behavior of geophysical indexes extracted from remotely sensed scenes. Simulations...
The prediction of monthly mean discharge is critical for water resources management. Statistical methods applied on discharge time series are traditionally used for predicting this kind of slow response hydrological events. With this paper we present a Support Vector Regression (SVR) system able to predict monthly mean discharge considering discharge and snow cover extent (250 meters resolution obtained...
This study presents three complementary approaches to determine the volume of water in small lakes (<100ha) by combining satellite altimetry data and high-resolution (HR) images. The first two are empirical and use synchronous ground measurements of the water volume and the satellite data. The results demonstrate that altimetry and imagery can be effectively and accurately used to monitor the temporal...
In this paper, a sensor-driven domain adaptation method is proposed for the classification of remote sensing images. The method aims at classifying an image where ground truth is not available exploiting the reference data acquired on a different but related image. This is done by taking advantage from a sensor-driven strategy that exploits the invariance of the measurements of some sensors on some...
In this paper state-of-the-art and advanced methods for multispectral pansharpening are reviewed and evaluated on two very high resolution datasets acquired by IKONOS-2 (four bands) and WorldView-2 (eight bands). The experimental analysis allows us to highlight the performances of the two main pansharpening approaches (i.e. component substitution and multiresolution analysis).
The paper presents a pansharpening algorithm that finds an optimal linear solution, in the MMSE sense, following a generalized component-substitution approach. It is characterized by nonlocal parameter optimization obtained through K-means clustering. The proposed method, namely C-BDSD, solves the problem of context-adaptive schemes that tune the spatial injection parameters on local statistics: instabilities...
Data from satellite and aerial images are now widely used by everyone. These images contain information from different frequency bands that help to characterize areas of interest. In this paper we study a framework for object detection in aerial image based on discriminatively-trained models trained on multimodal data. Specifically, we investigate a method to merge outputs of large margin classifiers...
In this paper, we propose a novel method to fuse multidate, multiresolution, and multiband remote sensing imagery for multitemporal classification purposes. The proposed method is based on an explicit hierarchical graph-based model that is sufficiently flexible to deal with multisource coregistered time series of images collected at different spatial resolutions. An especially novel element of the...
Daytime flaring detection using Landsat-8 multispectral data was inspired by the Visible Infrared Imaging Radiometer Suite (VIIRS) nightfire detection work. A fast and semi-automated endmember extraction algorithm was employed to detect gas flares in several locations of Alberta. Most of the detected flaring locations matched with the flaring reports, Bing Maps Aerial, and Google Maps images. To our...
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