Faculty of Spatial Information Technology: Faulty of Environmental Science and Technology: Faculties of ECE: Faculty of Civil Engg & Water Resources.Conference Detail for Image and Signal Processing for Remote Sensing. Adaptive sidelobe reduction in SAR and INSAR COSMO- Sky. Med image processing. Paper 1. 00. 04- 4. Time: 5: 4. 5 PM - 7: 3. PM. Author(s): Rino Lorusso, Nunzia Lombardi, Giovanni Milillo, Agenzia Spaziale Italiana (Italy). Pulse responses of SAR along range and azimuth are both sinc functions with high levels of sidelobes. The main lobe and the side lobes of strong scatterers are sometimes clearly visible in the images. Sidelobe reduction is of particular importance when imaging scenes contain objects such as ships and buildings having very large radar cross sections (RCS). Amplitude weighting is usually used to suppress sidelobes of the images at the expense of broadening of mainlobe, loss of resolution and degradation of SAR images. The Spatial Variant Apodization (SVA) is an Adaptive Side. Lobe Reduction (ASLR) technique that provides high effective suppression of sidelobes without broadening mainlobe. In this paper, we apply MSVA to process CSK Strip. Map and Spotlight X- band data. Different test sites have been selected in Italy, Argentina, California and Germany where up to 4. Conferences, workshops > Other events. September 22-23, 2016 2 nd Virtual Geoscience Conference. WELCOME TO THIS TUTORIAL, a training manual for learning the role of space science and technology for using remote sensing to monitor planetary bodies and distant. Hyperspectral remote sensing for oil exploration 1. HYPERSPECTRAL REMOTE SENSING FOR OIL EXPLORATION PRESENTED BY JOSHUA. Remote Sensing and Spatial Analysis Branch, Office of Research and Development, United States Environmental Protection Agency, 109 T.W. Alexander Drive, Research. Experimental results show clearly the resolution improvement (2. MSVA processing is applied compared with Hamming windowing one. Then MSVA technique is applied to INSAR image processing using CSK Strip. Map single look complex (SLC) interferometric tandem- like data pairs acquired in the period July- September 2. East- California during the CSK interferometric mission. The interferometric coherence of image pair obtained via Hamming window and via MSVA are compared. Higher resolution interferometric products have been obtained with no significant variation of mean coherence when using ASLR products with respect to standard hamming windowed one. In future work, we shall examine quantificationally how the accuracy of DEM can be affected by using SVA. Analysis of the electronic crosstalk effect in Terra MODIS long- wave infrared photovoltaic bands using lunar images. Paper 1. 00. 04- 4. Time: 5: 4. 5 PM - 7: 3. PM. Author(s): Truman Wilson, Aisheng Wu, Xu Geng, Zhipeng Wang, Science Systems and Applications, Inc. Xiong, NASA Goddard Space Flight Ctr. CCD matrixes operating under time delay and charge integration mode (TDI- CCD) are used to achieve high sensitivity of instruments. Matrixes are placed chequerwise in the focal plane of camera according to the principle staggered/non- collinear and are combined into three optoelectronic converters (OEC) shifted by 9. These peculiarities are taken into account during on ground level 1 processing of the earth surface images that includes: relative radiometric correction of images, . The method of self- calibration was applied for clarification of internal orientation parameters and mounting angles of camera in relation to star trackers. As a result, parameters of the high- precision georeferencing model on which the algorithm of information processing according to the level 1 is based, have been obtained. Within the analysis a compensation coefficients of distortions caused by different sensitivities of separate CCD matrixes and photodetectors have been determined. It should be noted that the algorithm provides mean square errors of the image matching not more than 0. Strict model georeferencing of images is adjusted according to corresponding points and the SRTM 9. This algorithm is based on extraction of high- frequency components from the panchromatic image and their incorporation into multispectral images. Suarez, Forest Research (United Kingdom). Thermography can be used for monitoring changes in the physiological state of plants. This is due to stress factors influencing emissions in the thermal infrared part of electromagnetic spectrum. However, there has been limited research into the use of thermal remote sensing approaches for tree health monitoring in the UK. This is due to a need for high spatial resolution data, which is usually obtained with low temporal frequency. Newly emerging technologies, such as Unmanned Aerial Vehicles (UAVs), could supplement aerial data acquisition, but sensor development is still in the early stages. Initially, camera calibration was performed in laboratory conditions against a thermally- controlled blackbody radiation source, revealing a significant overestimation of the temperature readings and a non- uniformity across the imagery. These effects have been minimised with a two- point calibration technique. As such, its performance might vary with changes in camera temperature. Laboratory trials, during which camera. Further to that, outdoor ground tests simulating an in- flight movement of air in front of the lens against targets of known emissivity were performed. These were georeferenced by registration to a Li. DAR- derived canopy height model. The tree crown temperature recorded by the UAV- borne infrared camera is compared against estimated infection levels of trees surveyed on ground to determine the influence of timing of acquisition on the signal and the sensitivity to the method to tree disease. An adaptive window approach to the analysis of radar sounder data. Paper 1. 00. 04- 5. Time: 5: 4. 5 PM - 7: 3. PM. Author(s): Mahdi Khodadadzadeh, Lorenzo Bruzzone, Univ. However, the high density of observed stars and the distortion of the optical system often bring about inaccuracy in star locations. So in large FOV observations, many conventional star identification algorithms do not show very good performance. In this paper, we propose a star identification method with a low requirement for observation accuracy and thus suitable for large FOV circumstances. The former is based on the match group algorithm, in addition to which we exploit the information of inclinations for verification. The inclinations of satellite stars are computed by reference to the selected pole stars. Then we obtain a set of identified stars for further recognition. The latter stage involves four steps. First, we derive the relationship between the rectangular coordinates of catalog stars and sensor stars with the identified locations obtained. Second, we transform the sensor coordinates to the catalog coordinates and find the catalog stars at close range as candidates. Third, we calculate the angle of inclination of each unidentified sensor star in relation to the nearest previously identified one, as well as the angular separation between them, to compare with those of the candidates. At last, candidates satisfying the limitations are considered the appropriate correspondences. The experimental results show that in large FOV observations, the proposed method presents better performance in comparison with several typical star identification methods in open literature. Towards real- time change detection in videos on an existing 3d model. Paper 1. 00. 04- 5. Time: 5: 4. 5 PM - 7: 3. PM. Author(s): Boitumelo Ruf, Tobias Schuchert, Fraunhofer- Institut f. Such change detection is generally performed by registration and comparison of two or more images. Climate change, global climate change, global warming, natural hazards, Earth, environment, remote sensing, atmosphere, land processes, oceans, volcanoes, land cover. Understand geological processes and overcome exploration challenges through focused structural interpretation of remote sensing data. Eric Economon, of the Agricultural Research Council in Pretoria, South Africa, is a man of firsts. Eric bought the first ASD instrument sold in South Africa over a. 3.10 Remote Sensing and GIS for Natural Hazards Assessment and Disaster Risk Management. Van Westen Author Vitae. However, existing 3d objects, such as buildings, may lead to parallax artefacts, which can distort the results in the image comparison process, especially for low altitude aerial platforms like small unmanned aerial vehicles (UAVs). Furthermore, considering only intensity information may lead to failures in the detection of changes in the 3d structure of objects. To overcome this problem, we present an approach that uses Structure- from- Motion (Sf. M) to compute depth information, with which a 3d change detection can be performed against a precomputed model. Additionally, by fusing the computed depth measurements with the existing 3d model, the model is updated and refined. Our approach consists of four successive steps: camera pose estimation, depth estimation, depth based change detection and update of the 3d model. First, the camera movement is tracked relative to the given base model. In step two, we use the input frames with the corresponding camera poses to compute dense depth estimations by a multi- view plane- sweep algorithm. We additionally calculate a second set of depth maps, by rendering the precomputed 3d model from the same camera poses. The actual change detection is performed in step three by comparing the two sets of depth maps with each other. To reduce the influence of background noise in the depth estimation, we compare logarithmic depth maps. In the last step, the new depth measurements are fused into the existing model. Redundancies and inconsistencies between the new depth measurements and the model are eliminated, based on visibility conditions and confidence measurements. Our approach is evaluated on synthetic test data with corresponding ground truth as well as on a real image based test sequence. Remote sensing imagery classification using multi- objective gravitational search algorithm. Paper 1. 00. 04- 5. Time: 5: 4. 5 PM - 7: 3. PM. Author(s): Aizhu Zhang, China Univ. Due to performance of this kind of multi- objective optimization based image classification highly depends on the choice of validity measures and optimization problems, two conflicting cluster validity indices are integrated with a novel multi- objective gravitational search algorithm (NMOGSA) to present an automatic multi- objective optimization based RSI classification method in this paper. In this method, texture features includes Gabor filter and Gray Level Co- occurrence Matrix (GLCM) method based textures of RSI, are extracted firstly. Then, the spectral- spatial feature set is constructed by syncretizing the extracted texture features and spectral features of original RSI. Afterwards, cluster of the spectral- spatial feature set is carried out on the basis of the proposed method. To be specific, cluster centers are randomly generated initially. After that, the cluster centers are updated and optimized adaptively employing the NMOGSA, in which the objective functions are built based on Jm and XB cluster validity indices.
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