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A Robust clustering Method for Multispectral Remote Sensing Image Analysis
English

2014 International Journal of Research and Applications  
Methods of Detection of Multi spectral remote sensing Images are becoming more popular due to the progresses in spatial resolution of satellite imagery.  ...  This paper presents detection of multispectral remotesensing images corrupted by noise using robust clustering method without any training data.  ...  demonstrate that multispectral remote sensing image corrupted with noise analysis can be carried out with to maximum accuracy. a) & (b) Objects in cluster 1 (multi spectral remote sensing Image without  ... 
doi:10.17812/ijra.1.3(19)2014 fatcat:zh3trflohrd4pn2g7d3dvdja6a

SVM based Multispectral Remote Sensing Image Analysis
English

2014 International Journal of Research and Applications  
Methods of Detection of Multi spectral remote sensing Images are becoming more popular due to the progresses in spatial resolution of satellite imagery.  ...  Simulation results are provided to demonstrate the efficacy of the proposed method for detection of Multi spectral remote sensing Images.  ...  Classification of multispectral remotely sensed data is computed with a special attention on uncertainty computation in the land-cover maps.  ... 
doi:10.17812/ijra.1.3(20)2014 fatcat:vvfqcuts2zfn5mlkqfobak3rvi

Classification of the real remotely sensed image covered with clouds

Lijana Stabingienė
2012 Lietuvos matematikos rinkinys  
For example, the remotely sensed images from the territory of Lithuania are very often corrupted by clouds.  ...  Solving such a problem is very important when we have remotely sensed information, which very often is corrupted by clouds.  ...  The remotely sensed image used for classification is naturally corrupted and then the exact correlation range parameter is unknown.  ... 
doi:10.15388/lmr.a.2012.21 fatcat:xlrhdlziyvg5tnwktdn5nfum7m

Computational Intelligence in Remote Sensing: An Editorial

Manuel Graña, Michal Wozniak, Sebastian Rios, Javier de de Lope
2020 Sensors  
Remote sensing data has been a salient field of application of computational intelligence algorithms, both for the exploitation of the data and for the research/development of new data analysis tools.  ...  In this editorial paper we provide the setting of the special issue "Computational Intelligence in Remote Sensing" and an overview of the published papers.  ...  Additional support come from project CybSPEED funded in 2017 call of the H2020 MSCA-RISE with grant 777720, and project KK-2018/00071 of the Elkartek 2018 funding program of the Basque Government.  ... 
doi:10.3390/s20030633 pmid:31979240 pmcid:PMC7038229 fatcat:inwh36whqffs5fy7i5hzrfzmb4

Remote Sensing and Forest Conservation: Challenges of Illegal Logging in Kursumlija Municipality (Serbia) [chapter]

Miomir M. Jovanović, Miško M. Milanović
2017 Forest Ecology and Conservation  
is easy to implement; the objectivity of these methods can significantly help in avoiding corruption and illegal logging.  ...  In short, NDVI is very promising for countries like Serbia (that rarely perform forest inventories): It is relatively cheap and quick, and it can provide forest managers with essential information; it  ...  multispectral remote sensing data [52, 53] .  ... 
doi:10.5772/67666 fatcat:ni2hiad5qjcv5h3xqtbmbbeabm

Missing Information Reconstruction of Remote Sensing Data: A Technical Review

Huanfeng Shen, Xinghua Li, Qing Cheng, Chao Zeng, Gang Yang, Huifang Li, Liangpei Zhang
2015 IEEE Geoscience and Remote Sensing Magazine  
Because of sensor malfunction and poor atmospheric conditions, there is usually a great deal of missing information in optical remote sensing data, which reduces the usage rate and hinders the follow-up  ...  In the past decades, missing information reconstruction of remote sensing data has become an active research field, and a large number of algorithms have been developed.  ...  Abstract-Because of sensor malfunction and poor atmospheric conditions, there is usually a great deal of missing information in optical remote sensing data, which reduces the usage rate and hinders the  ... 
doi:10.1109/mgrs.2015.2441912 fatcat:vrhsm6zggjeedhtivusqshphum

CoSMOS: Performance of kurtosis algorithm for radio frequency interference detection and mitigation

Sidharth Misra, Steen S. Kristensen, Sten S. Sobjaerg, Niels Skou
2007 2007 IEEE International Geoscience and Remote Sensing Symposium  
The impact of RFI on remotely sensed data over land and sea is also presented.  ...  Data is collected using two separate integration times, as a result of which sensitivity of the detection algorithm is measured.  ...  ACKNOWLEDGEMENTS The authors would like to acknowledge their collaboration with the Helsinki University of Technology and ESTEC.  ... 
doi:10.1109/igarss.2007.4423403 dblp:conf/igarss/MisraKSS07 fatcat:djiywma7wrbh7d45fpqctjonmq

Multi-channel data storage format definition for visualization tasks on the example of SPOT-4 images

N Yu Sevastianova, N S Vinogradova
2019 CEUR Workshop Proceedings  
But even with incomplete recovery, this kind of data can be used in the future to solve production problems.  ...  Emergency situations arising from the use of arrays can lead to the fact that the remote sensing data, usually stored in uncompressed form, may become partially damaged.  ...  Different recovering methods for corrupted data are developed last time propose the approaches for recovering different remote sensing data types [5, 6] , i.e. hyperspectral data [7] and SAR data [  ... 
doi:10.18287/1613-0073-2019-2391-302-308 fatcat:2krmjmvnsjbb7ohjzodq3psini

AUTOMATIC ASSESSMENT OF ACQUISITION AND TRANSMISSION LOSSES IN INDIAN REMOTE SENSING SATELLITE DATA

D. Roy, B. Purna Kumari, M. Manju Sarma, N. Aparna, B. Gopal Krishna
2016 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The quality of Remote Sensing data is an important parameter that defines the extent of its usability in various applications.  ...  This data may be corrupted with data losses due to interferences during data transmission, data acquisition and sensor anomalies.  ...  A multithreaded approach was used in order to achieve faster results as it deals with large quantity of full resolution data.  ... 
doi:10.5194/isprs-annals-iii-1-129-2016 fatcat:kltrdibm75hy7ha3x7owjkfkna

AUTOMATIC ASSESSMENT OF ACQUISITION AND TRANSMISSION LOSSES IN INDIAN REMOTE SENSING SATELLITE DATA

D. Roy, B. Purna Kumari, M. Manju Sarma, N. Aparna, B. Gopal Krishna
2016 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The quality of Remote Sensing data is an important parameter that defines the extent of its usability in various applications.  ...  This data may be corrupted with data losses due to interferences during data transmission, data acquisition and sensor anomalies.  ...  A multithreaded approach was used in order to achieve faster results as it deals with large quantity of full resolution data.  ... 
doi:10.5194/isprsannals-iii-1-129-2016 fatcat:fufebzd4vvc4hef37my2eqpnia

Toward Better Planetary Surface Exploration by Orbital Imagery Inpainting

Hiya Roy, Subhajit Chaudhury, Toshihiko Yamasaki, Tatsuaki Hashimoto
2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
: Please replace colons appearing after figure numbers and table numbers with period in all figure and table captions.  ...  This greatly reduces the usability of the captured data for scientific purposes. To alleviate this problem, in this article, we propose a machine learning-based 'no-data' region prediction algorithm.  ...  existing missing data reconstruction techniques on remote sensing imagery.  ... 
doi:10.1109/jstars.2020.3038778 fatcat:cacs7elawrfxjcskxe6c7iuami

Adaptive remote sensing with HF skywave radar

S.J. Anderson
1992 IEE Proceedings F Radar and Signal Processing  
In concert with user-focused remote sensing programs, investigations were undertaken to gain a detailed understanding of issues relating to propagation, system calibration, radar resource management and  ...  Inevitably, as the radar evolved into a facility owned and operated by the Royal Australian Air Force, the remote sensing mission had to compete with surveillance tasks with higher priorities and the quality  ...  Acknowledgments The Jindalee radars are the product of many talented scientists and engineers with whom the present author is proud to have been associated.  ... 
doi:10.1049/ip-f-2.1992.0022 fatcat:ys7fz5jbjrgfrf2qvxpohkvdoe

Remote sensing applications of HF skywave radar: The Australian experience

STUART ANDERSON
2010 Turkish Journal of Electrical Engineering and Computer Sciences  
In concert with user-focused remote sensing programs, investigations were undertaken to gain a detailed understanding of issues relating to propagation, system calibration, radar resource management and  ...  Inevitably, as the radar evolved into a facility owned and operated by the Royal Australian Air Force, the remote sensing mission had to compete with surveillance tasks with higher priorities and the quality  ...  Acknowledgments The Jindalee radars are the product of many talented scientists and engineers with whom the present author is proud to have been associated.  ... 
doi:10.3906/elk-0912-5 fatcat:worygqnyondi3jcohy3fdjv3la

TRANSPARENCY AND ACCOUNTABILITY IN URBAN PUBLIC PROCUREMENT: DESIGN OF A SELF-SOVEREIGN BLOCKCHAIN APP

A. Balan, A. Balan, S. Alboaie, S. Alboaie, S. Alboaie, K. Kourtit, K. Kourtit, K. Kourtit, K. Kourtit, P. Nijkamp, P. Nijkamp, P. Nijkamp (+1 others)
2020 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
It argues that blockchain technology may be an effective vehicle in coping with corruption and 'false playing' in urban public procurement and tendering systems.  ...  It presents the design of new app (Self-Sovereign App or SSApp) to avoid corruptive behavior of agents.  ...  CONCLUDING REMARKS Smart digital cities have to deal with complex big data. Blockchain systems may be instrumental in providing intelligent decision support to public agencies in a city.  ... 
doi:10.5194/isprs-archives-xliv-4-w2-2020-9-2020 doaj:731442ee69cf483eba6a4c809da0ed29 fatcat:tay4folclrhqvbxvw4asixwbba

Comparison of the classification methods for the images modeled by Gaussian random fields

Lijana Stabingienė, Giedrius Stabingis, Kęstutis Dučinskas
2011 Lietuvos matematikos rinkinys  
The remotely sensed image is used for classification (USGS Earth Explorer). Also GRF with different spatial correlation range are generated and added to the original remotely sensed image.  ...  In image classification often occur such situations, when images in some level are corrupted by additive noise. Such noise in image classification can be modeled by Gaussian random fields (GRF).  ...  Atkinson and Lewis [3] reviewed geostatistical techniques for classification of remotely sensed images.  ... 
doi:10.15388/lmr.2011.mt04 fatcat:lsvpjeqlnrbc3agfb6l4jhbju4
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