scholarly journals Geometric Quality Assessment of Bundle Block Adjusted Mulit- Sensor Satellite Imageries

2014 ◽  
Vol XL-8 ◽  
pp. 1115-1120
Author(s):  
S. Ghosh ◽  
P. S. Bhawani Kumar ◽  
P. V. Radhadevi ◽  
V. Srinivas ◽  
J. Saibaba ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Indian Subcontinent ◽  
Accuracy Assessment ◽  
Automatic Generation ◽  
Mountainous Area ◽  
Observation Data ◽  
Geometric Continuity ◽  
Multiple Sources ◽  
Large Area ◽  
Rational Polynomial

The integration of multi-sensor earth observation data belonging to same area has become one of the most important input for resource mapping and management. Geometric error and fidelity between adjacent scenes affects large-area digital mosaic if the images/ scenes are processed independently. A block triangulation approach "Bundle Block Adjustment (BBA)" system has been developed at ADRIN for combined processing of multi-sensor, multi-resolution satellite imagery to achieve better geometric continuity. In this paper we present the evaluation results of BBA software along with performance assessment and operational use of products thus generated. <br><br> The application evaluation deals with functional aspects of block-adjustment of satellite imagery consisting of data from multiple sources, i.e. AWiFs, LISS-3, LISS-4 and Cartosat-1 in various combinations as single block. It has provision for automatic generation of GCPs and tie-points using image metafile/ Rational Polynomial Coefficient's (RPC’s) and ortho/ merged/ mosaicked products generation. The study is carried out with datasets covering different terrain types (ranging from high mountainous area, moderately undulating terrain, coastal plain, agriculture fields, urban area and water-body) across Indian subcontinent with varying block sizes and spatial reference systems. Geometric accuracy assessment is carried out to figure out error propagation at scene based ortho/ merged products as well as block level. The experimental results confirm that pixel tagging, geometric fidelity and feature continuity across adjacent scenes as well as for multiple sensors reduced to a great extent, due to the high redundancy. The results demonstrate that it is one of the most affective geometric corrections for generating large area digital mosaic over High mountainous terrain using high resolution good swath satellite imagery, like Cartosat-1, with minimum human intervention.

scholarly journals A New Combined Adjustment Model for Geolocation Accuracy Improvement of Multiple Sources Optical and SAR Imagery

2021 ◽  
Vol 13 (3) ◽  
pp. 491
Author(s):  
Niangang Jiao ◽  
Feng Wang ◽  
Hongjian You
Keyword(s):  
Remote Sensing Data ◽  
Observation Data ◽  
Multiple Sources ◽  
Accuracy Improvement ◽  
Geometric Calibration ◽  
Proposed Model ◽  
Calibration Methods ◽  
Earth Observation Data ◽  
Sar Imagery ◽  
Geolocation Accuracy

Numerous earth observation data obtained from different platforms have been widely used in various fields, and geometric calibration is a fundamental step for these applications. Traditional calibration methods are developed based on the rational function model (RFM), which is produced by image vendors as a substitution of the rigorous sensor model (RSM). Generally, the fitting accuracy of the RFM is much higher than 1 pixel, whereas the result decreases to several pixels in mountainous areas, especially for Synthetic Aperture Radar (SAR) imagery. Therefore, this paper proposes a new combined adjustment for geolocation accuracy improvement of multiple sources satellite SAR and optical imagery. Tie points are extracted based on a robust image matching algorithm, and relationships between the parameters of the range-doppler (RD) model and the RFM are developed by transformed into the same Geodetic Coordinate systems. At the same time, a heterogeneous weight strategy is designed for better convergence. Experimental results indicate that our proposed model can achieve much higher geolocation accuracy with approximately 2.60 pixels in the X direction and 3.50 pixels in the Y direction. Compared with traditional methods developed based on RFM, our proposed model provides a new way for synergistic use of multiple sources remote sensing data.

scholarly journals 9-year spatial and temporal evolution of desert dust aerosols over South-East Asia as revealed by CALIOP

2017 ◽  
Author(s):  
Emmanouil Proestakis ◽  
Vassilis Amiridis ◽  
Eleni Marinou ◽  
Aristeidis K. Georgoulias ◽  
Stavros Solomos ◽  
...  
Keyword(s):  
East Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Indian Subcontinent ◽  
Dust Aerosol ◽  
Observation Data ◽  
South East Asia ◽  
Desert Dust ◽  
Dust Aerosols ◽  
Se Asia

Abstract. We present a 3-D climatology of the desert dust distribution over South-East Asia derived using CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) data. To distinguish desert dust from total aerosol load we apply a methodology developed in the framework of EARLINET (European Aerosol Research Lidar Network), the particle linear depolarization ratio and updated lidar ratio values suitable for Asian dust, on multiyear CALIPSO observations (01/2007–12/2015). The resulting dust product provides information on the horizontal and vertical distribution of dust aerosols over SE (South-East) Asia along with the seasonal transition of dust transport pathways. Persistent high D_AOD (Dust Aerosol Optical Depth) values, of the order of 0.6, are present over the arid and semi-arid desert regions. Dust aerosol transport (range, height and intensity) is subject to high seasonality, with highest values observed during spring for northern China (Taklimakan/Gobi deserts) and during summer over the Indian subcontinent (Thar Desert). Additionally we decompose the CALIPSO AOD (Aerosol Optical Depth) into dust and non-dust aerosol components to reveal the non-dust AOD over the highly industrialized and densely populated regions of SE Asia, where the non-dust aerosols yield AOD values of the order of 0.5. Furthermore, the CALIPSO-based short-term AOD and D_AOD time series and trends between 01/2007 and 12/2015 are calculated over SE Asia and over selected sub-regions. Positive trends are observed over northwest and east China and the Indian subcontinent, whereas over southeast China are mostly negative. The calculated AOD trends agree well with the trends derived from Aqua/MODIS (Moderate Resolution Imaging Spectroradiometer), although significant differences are observed over specific regions.

scholarly journals Evaluation of hadronic emission in starburst galaxies and star-forming galaxies

2021 ◽  
Vol 21 (10) ◽  
pp. 263
Author(s):  
Yun-Chuan Xiang ◽  
Ze-Jun Jiang ◽  
Yun-Yong Tang
Keyword(s):  
Supernova Remnants ◽  
Milky Way ◽  
Starburst Galaxies ◽  
Model Parameters ◽  
Zone Model ◽  
Observation Data ◽  
Large Area ◽  
Star Forming ◽  
Ngc 1068 ◽  
The One

Abstract In this work, we reanalyzed 11 years of spectral data from the Fermi Large Area Telescope (Fermi-LAT) of currently observed starburst galaxies (SBGs) and star-forming galaxies (SFGs). We used a one-zone model provided by NAIMA and the hadronic origin to explain the GeV observation data of the SBGs and SFGs. We found that a protonic distribution of a power-law form with an exponential cutoff can explain the spectra of most SBGs and SFGs. However, it cannot explain the spectral hardening components of NGC 1068 and NGC 4945 in the GeV energy band. Therefore, we considered the two-zone model to well explain these phenomena. We summarized the features of two model parameters, including the spectral index, cutoff energy, and proton energy budget. Similar to the evolution of supernova remnants (SNRs) in the Milky Way, we estimated the protonic acceleration limitation inside the SBGs to be the order of 102 TeV using the one-zone model; this is close to those of SNRs in the Milky Way.

A multi-resolution satellite imagery approach for large area mapping of ericaceous shrubs in Northern Quebec, Canada

2009 ◽  
Vol 11 (5) ◽  
pp. 334-343 ◽  
Author(s):  
Olivier R. van Lier ◽  
Richard A. Fournier ◽  
Robert L. Bradley ◽  
Nelson Thiffault
Keyword(s):  
Satellite Imagery ◽  
Large Area ◽  
Ericaceous Shrubs

Estimation of Normal Rice Yield Considering Heading Stage Based on Observation Data and Satellite Imagery

2021 ◽  
Author(s):  
Yuki Sofue ◽  
Chiharu Hongo ◽  
Naohiro Manago ◽  
Gunardi Sigit ◽  
Koki Homma ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Rice Yield ◽  
Observation Data ◽  
Heading Stage

Study on Industrial Waste Sites Monitoring Based on Remote Sensing Technology

2011 ◽  
Vol 201-203 ◽  
pp. 2607-2610
Author(s):  
Wen Hui Zhao ◽  
She Liu
Keyword(s):  
Industrial Waste ◽  
Large Scale ◽  
Rapid Development ◽  
Dynamic Environment ◽  
High Spectral Resolution ◽  
Ground Vegetation ◽  
High Time Resolution ◽  
Mountainous Area ◽  
Observation Data ◽  
Wide Range

Large scale of the industrial waste is not timely disposed of due to economic rapid development. It is the main reason why environmental pollution problem is getting more and more serious and we should monitor the pollution of industrial waste. A MODIS (Moderate Resolution Imaging Spectroradiometer) senor is used for long-time and dynamic environment monitor because it has advantages of high time resolution and high spectral resolution characteristics etc. SPOT satellite data is used to analyze the ground vegetation for its higher ground resolution and rich product data bases. The influence of industrial waste on environment is analyzed and the result of research is verifyed with the information of local meteorological agent and observation data of site. This method can be used for monitoring wide-range industrial waste and have good performance of monitoring and early warning industrial waste sites which are in mountainous area.

GIS based analysis and accuracy assessment of low-resolution satellite imagery for coastline monitoring

2020 ◽  
Author(s):  
Dionysios Apostolopoulos ◽  
Konstantinos G. Nikolakopoulos ◽  
Vassilios Boumpoulis ◽  
Nikolaos Depountis
Keyword(s):  
Satellite Imagery ◽  
Accuracy Assessment ◽  
Low Resolution

scholarly journals Geometric Accuracy Assessment of Deimos-2 Panchromatic Stereo Pairs: Sensor Orientation and Digital Surface Model Production

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7234
Author(s):  
Manuel A. Aguilar ◽  
Rafael Jiménez-Lao ◽  
Abderrahim Nemmaoui ◽  
Fernando J. Aguilar
Keyword(s):  
Urban Areas ◽  
Satellite Images ◽  
Accuracy Assessment ◽  
Bare Soil ◽  
Surface Model ◽  
Stereo Pair ◽  
Rational Polynomial ◽  
Sensor Orientation ◽  
Vertical Accuracy ◽  
Land Covers

Accurate elevation data, which can be extracted from very high-resolution (VHR) satellite images, are vital for many engineering and land planning applications. In this way, the main goal of this work is to evaluate the capabilities of VHR Deimos-2 panchromatic stereo pairs to obtain digital surface models (DSM) over different land covers (bare soil, urban and agricultural greenhouse areas). As a step prior to extracting the DSM, different orientation models based on refined rational polynomial coefficients (RPC) and a variable number of very accurate ground control points (GCPs) were tested. The best sensor orientation model for Deimos-2 L1B satellite images was the RPC model refined by a first-order polynomial adjustment (RPC1) supported on 12 accurate and evenly spatially distributed GCPs. Regarding the Deimos-2 based DSM, its completeness and vertical accuracy were compared with those obtained from a WorldView-2 panchromatic stereo pair by using exactly the same methodology and semiglobal matching (SGM) algorithm. The Deimos-2 showed worse completeness values (about 6% worse) and vertical accuracy results (RMSEZ 42.4% worse) than those computed from WorldView-2 imagery over the three land covers tested, although only urban areas yielded statistically significant differences (p < 0.05).

scholarly journals Error correction of depth images for multiview time-of-flight vision sensors

2020 ◽  
Vol 17 (4) ◽  
pp. 172988142094237
Author(s):  
Yu He ◽  
Shengyong Chen
Keyword(s):  
Error Correction ◽  
Vision System ◽  
Three Dimensional ◽  
Time Of Flight ◽  
Robot Vision ◽  
Optimization Method ◽  
Automatic Generation ◽  
Depth Image ◽  
Observation Data ◽  
Tof Camera

The developing time-of-flight (TOF) camera is an attractive device for the robot vision system to capture real-time three-dimensional (3D) images, but the sensor suffers from the limit of low resolution and precision of images. This article proposes an approach to automatic generation of an imaging model in the 3D space for error correction. Through observation data, an initial coarse model of the depth image can be obtained for each TOF camera. Then, its accuracy is improved by an optimization method. Experiments are carried out using three TOF cameras. Results show that the accuracy is dramatically improved by the spatial correction model.

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