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A new perspective for multitemporal SAR data analysis
2014
2014 IEEE Geoscience and Remote Sensing Symposium
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In this paper we present the Multitemporal Adaptive Processing (MAP3) framework for the definition of a new family of multitemporal, user-oriented products whose information level lays between those of ...
CONCLUSIONS Multitemporal SAR analysis is a powerful and attractive technique for environmental monitoring and planning. ...
In this paper we present the Multitemporal Adaptive Processing (MAP3) [1] framework for the definition of a new family of multitemporal, user-oriented products we called Level 1α because they conceptually ...
doi:10.1109/igarss.2014.6947541
dblp:conf/igarss/AmitranoMIRR14
fatcat:qdwhchevinhllm2yfkxnbjy6l4
The Time Variable in Data Fusion: A Change Detection Perspective
2015
IEEE Geoscience and Remote Sensing Magazine
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From the perspective of change detection and detection of land-cover transitions, multitemporal image analysis techniques can be divided into two main groups: i) those based on the fusion of the multitemporal ...
The 2 analysis is conducted by considering images acquired by optical and SAR systems at medium, high and very high spatial resolution. ...
for data distribution of archive data that makes it possible a retrospective analysis on large scale (e.g., the Landsat Thematic Mapper archive), and iii) the new policies for the distribution of new satellites ...
doi:10.1109/mgrs.2015.2443494
fatcat:2g4efbg4bjeq7f7jzsnx7tw2qy
Improving Urban Change Detection From Multitemporal SAR Images Using PCA-NLM
2013
IEEE Transactions on Geoscience and Remote Sensing
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new technique for object-based change image generation. ...
Multitemporal SAR images acquired by ERS-2 SAR and ENVISAT ASAR sensors were used for pixel-based change detection. ...
The second research (Paper V) proposed a new technique for change image generation. A new representation of the change data is provided. ...
doi:10.1109/tgrs.2013.2245900
fatcat:2eoewpshe5ahxn5gwegyekraee
The Role of Time-Series L-Band SAR and GEDI in Mapping Sub-Tropical Above-Ground Biomass
2021
Frontiers in Earth Science
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Using a multitemporal AGB retrieval strategy, the accuracy improves by 15% (55 Mg/ha RMSE) for all field plots and by 21% (39 Mg/ha RMSE) for forests with AGB less than 100 Mg/ha. ...
The analysis shows that any ten multitemporal acquisitions spanning 5 years are sufficient for improving AGB retrieval accuracy over the considered test site. ...
the lidar data set, the German Aerospace Agency (DLR) for 12 m TanDEM-X DEM under science phase AO Project No. ...
doi:10.3389/feart.2021.752254
fatcat:fllxoelennci3hiwi7h223kwji
Multiscale and Multitemporal Road Detection from High Resolution SAR Images Using Attention Mechanism
2021
Remote Sensing
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In this paper, we propose a multiscale and multitemporal network (MSMTHRNet) for road detection from SAR imagery, which contains the temporal consistency enhancement module (TCEM) and multiscale fusion ...
They ignore the temporal characteristic of road objects such as the temporal consistency for the road objects in the multitemporal SAR images that cover the same area and are taken at adjacent times, causing ...
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interests. ...
doi:10.3390/rs13163149
fatcat:mferm5gb7veyfjd7lfudoyscbq
The Sentinel-1 mission for the improvement of the scientific understanding and the operational monitoring of the seismic cycle
2012
Remote Sensing of Environment
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We examine the achievements and the main limitations of present SAR systems for the measurement and analysis of crustal deformation, and envision the foreseeable advances that the Sentinel-1 data will ...
Indeed, satellite SAR sensors can acquire new data over the same area of interest, using the same acquisition geometry, many times a year, thus allowing a comparison of the phase maps at different times ...
The SIGRIS pilot project has been funded by the Italian Space Agency in the framework of the national space plan, to promote the operational use of Earth Observation data for Seismic Risk Management. ...
doi:10.1016/j.rse.2011.09.029
fatcat:fzultjqb2jhwpjaf4v5q52nxy4
Sentinel-1 InSAR Coherence for LandCover Mapping: A comparison of multiple feature-based classifiers
2020
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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From his research projects have started many New Space and Earth Observation start-up companies in Finland. ...
His research interests include microwave remote sensing, especially SAR Interferometry and SAR polarimetry, and nanosatellite technology. ...
Ventura for organizing the efficient access to the Sentinel-1 SLC data and L. Cattani for his efforts of setting up the Jupyter-hub environment. ...
doi:10.1109/jstars.2019.2958847
fatcat:kuyt72vdozgezleymh7hn3yxu4
Special Section Guest Editorial: Feature and Deep Learning in Remote Sensing Applications
2018
Journal of Applied Remote Sensing
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Most papers exploited electro-optical data, but there were some SAR, hyperspectral, and multitemporal ...
processing; two papers utilizing spectral-spatial processing for hyperspectral image analysis; three papers on object tracking and recognition; one paper studying how deep networks need to be for remote ...
The following papers utilized deep CNNs to extract higher-quality features for classification and change detection in SAR imagery analysis. ...
doi:10.1117/1.jrs.11.042601
fatcat:pq3xg2sggfdtljjs3hrmp7tzdm
Adaptive Multitemporal SAR Image Filtering Based on the Change Detection Matrix
2014
IEEE Geoscience and Remote Sensing Letters
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ACKNOWLEDGMENT The authors would like to thank the German Aerospace Center (DLR) for providing the TerraSAR-X time series used in the experiments under the project MTH0232. ...
With multi-temporal data, both spatial and temporal information can be exploited and this can improve results for filtering SAR data and then, other applications. ...
CONCLUSIONS In this letter, a new method for temporal adaptive filtering of SAR image time series is presented. The proposed estimator is based on the determination of changed and unchanged pixels. ...
doi:10.1109/lgrs.2014.2311663
fatcat:hzusktr3erepfmxcuzl6ntj6um
A robust nonlinear scale space change detection approach for SAR images
2013
Image and Signal Processing for Remote Sensing XIX
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In this paper, we propose a change detection approach based on nonlinear scale space analysis of change images for robust detection of various changes incurred by natural phenomena and/or human activities ...
in Synthetic Aperture Radar (SAR) images using Maximally Stable Extremal Regions (MSERs). ...
For instance, Mercier et al. 3 presented a methodology quantifying the probability density function evolution of the multitemporal SAR images between the acquisition times to spot abrupt ground changes ...
doi:10.1117/12.2030189
fatcat:ah3fav3wxved5lplnxfwcygspe
Development of a global 30 m impervious surface map using multisource and multitemporal remote sensing datasets with the Google Earth Engine platform
2020
Earth System Science Data
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% and 0.780 for FROM-GLC, 90.3 % and 0.794 for GHSL, 88.4 % and 0.753 for GlobeLand30, and 88.0 % and 0.745 for HBASE using all 15 regional validation data. ...
In this study, we aimed to generate an accurate global impervious surface map at a resolution of 30 m for 2015 by combining Landsat 8 Operational Land Image (OLI) optical images, Sentinel-1 SAR images ...
performance to single-polarimetric SAR data for impervious mapping. ...
doi:10.5194/essd-12-1625-2020
fatcat:45htn3rkx5gmfb7ys2e5iwpja4
FLOOD DETECTION IN TIME SERIES OF OPTICAL AND SAR IMAGES
2020
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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These last decades, Earth Observation brought a number of new perspectives from geosciences to human activity monitoring. ...
To help the community go forward, we introduce a new dataset composed of co-registered optical and SAR images time series for the detection of flood events and new neural network approaches to leverage ...
So, multitemporal analysis is the key for the detection of abnormal events such as natural disasters and even their prediction ahead of time. ...
doi:10.5194/isprs-archives-xliii-b2-2020-1343-2020
fatcat:q4zlzo6wlndczhmmxj75yrfwzi
MULTISENGE: A MULTIMODAL AND MULTITEMPORAL BENCHMARK DATASET FOR LAND USE/LAND COVER REMOTE SENSING APPLICATIONS
2022
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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This paper presents MultiSenGE that is a new large scale multimodal and multitemporal benchmark dataset covering one of the biggest administrative region located in the Eastern part of France. ...
With all patches georeferenced at a 10 meters spatial resolution covering the whole Grand-Est Region, MultiSenGE provides an opportunity for environmental benchmark dataset will help to advance data-driven ...
ACKNOWLEDGEMENTS We thanks the Spatial Data Infrastructure GeoGrandEst provided the reference data used in this study and the Theia Services and Data Infrastructure for the Sentinel-2A imagery. ...
doi:10.5194/isprs-annals-v-3-2022-635-2022
fatcat:fkl5klwh4befxpugpctozsjmgq
Monitoring the Recovery after 2016 Hurricane Matthew in Haiti via Markovian Multitemporal Region-Based Modeling
2021
Remote Sensing
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This is accomplished via a novel change detection method that has been formulated, in a data fusion perspective, in terms of multitemporal supervised classification. ...
The availability of very high resolution images provided by last-generation satellite synthetic aperture radar (SAR) and optical sensors makes this analysis promising from an application perspective and ...
Nevertheless, SAR data can be very useful for the discrimination of a subset of such classes, such as urban areas and water bodies. ...
doi:10.3390/rs13173509
fatcat:drmmajenifcz5ltgtebqtfhike
Multimodal Classification of Remote Sensing Images: A Review and Future Directions
2015
Proceedings of the IEEE
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Multiple and heterogeneous image sources can be available for the same geographical region: multispectral, hyperspectral, radar, multitemporal and multiangular images can nowadays be acquired over a given ...
Then, we illustrate the different approaches in seven challenging remote sensing applications: 1) multiresolution fusion for multispectral image classification; 2) image downscaling as a form of multitemporal ...
ACKNOWLEDGEMENTS The authors would like to thank DigitalGlobe Inc. for the optical data on Rio and Haiti, and the Italian Space Agency for the SAR data on Haiti. ...
doi:10.1109/jproc.2015.2449668
fatcat:gaficd2bcrbshcrds3a2wfa25a
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