메뉴 건너뛰기




Volumn 10, Issue 2, 2018, Pages

A CNN-based fusion method for feature extraction from sentinel data

Author keywords

Coregistration; Deep learning; Multi sensor fusion; Multitemporal images; Normalized difference vegetation index (NDVI); Pansharpening

Indexed keywords

DATA FUSION; DEEP LEARNING; NEURAL NETWORKS; RADAR; RADAR IMAGING; REMOTE SENSING; VEGETATION;

EID: 85042529724     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs10020236     Document Type: Article
Times cited : (146)

References (63)
  • 1
    • 0023139077 scopus 로고    scopus 로고
    • Multipolarization SAR data for surface feature delineation and forest vegetation characterization
    • Wu, S.T.; Sader, S.A. Multipolarization SAR data for surface feature delineation and forest vegetation characterization. IEEE Trans. Geosci. Remote Sens. 1987, GE-25, 67-76
    • IEEE Trans Geosci. Remote Sens , vol.1987 , pp. 67-76
    • Wu, S.T.1    Sader, S.A.2
  • 2
    • 0034693650 scopus 로고    scopus 로고
    • Soil moisture evaluation using multi-temporal synthetic aperture radar (SAR) in semiarid rangeland
    • Moran, M.S.; Hymer, D.C.; Qi, J.; Sano, E.E. Soil moisture evaluation using multi-temporal synthetic aperture radar (SAR) in semiarid rangeland. Agric. For. Meteorol. 2000, 105, 69-80
    • (2000) Agric. For. Meteorol , vol.105 , pp. 69-80
    • Moran, M.S.1    Hymer, D.C.2    Qi, J.3    Sano, E.E.4
  • 3
    • 33847018947 scopus 로고    scopus 로고
    • Synthetic Aperture Radar (L band) and Optical Vegetation Indices for Discriminating the Brazilian Savanna Physiognomies: A Comparative Analysis
    • Sano, E.E.; Ferreira, L.G.; Huete, A.R. Synthetic Aperture Radar (L band) and Optical Vegetation Indices for Discriminating the Brazilian Savanna Physiognomies: A Comparative Analysis. Earth Interact. 2005, 9, 1-15
    • (2005) Earth Interact , vol.9 , pp. 1-15
    • Sano, E.E.1    Ferreira, L.G.2    Huete, A.R.3
  • 4
    • 84940675717 scopus 로고    scopus 로고
    • Coupling SAR C-Band and Optical Data for Soil Moisture and Leaf Area Index Retrieval Over Irrigated Grasslands
    • Baghdadi, N.N.; Hajj, M.E.; Zribi, M.; Fayad, I. Coupling SAR C-Band and Optical Data for Soil Moisture and Leaf Area Index Retrieval Over Irrigated Grasslands. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2016, 9, 1229-1243
    • (2016) IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens , vol.9 , pp. 1229-1243
    • Baghdadi, N.N.1    Hajj, M.E.2    Zribi, M.3    Fayad, I.4
  • 5
    • 0032030026 scopus 로고    scopus 로고
    • Review article Multisensor image fusion in remote sensing: Concepts, methods and applications
    • Pohl, C.; Genderen, J.L.V. Review article Multisensor image fusion in remote sensing: Concepts, methods and applications. Int. J. Remote Sens. 1998, 19, 823-854
    • (1998) Int. J. Remote Sens , vol.19 , pp. 823-854
    • Pohl, C.1    Genderen, J.L.V.2
  • 9
    • 85014871642 scopus 로고    scopus 로고
    • Multispectral and Hyperspectral Image Fusion Using a 3-D-Convolutional Neural Network
    • Palsson, F.; Sveinsson, J.R.; Ulfarsson, M.O. Multispectral and Hyperspectral Image Fusion Using a 3-D-Convolutional Neural Network. IEEE Geosci. Remote Sens. Lett. 2017, 14, 639-643
    • (2017) IEEE Geosci. Remote Sens. Lett , vol.14 , pp. 639-643
    • Palsson, F.1    Sveinsson, J.R.2    Ulfarsson, M.O.3
  • 11
    • 84884817758 scopus 로고    scopus 로고
    • Feature Level Fusion of Multi-Temporal ALOS PALSAR and Landsat Data for Mapping and Monitoring of Tropical Deforestation and Forest Degradation
    • Reiche, J.; Souza, C.M.; Hoekman, D.H.; Verbesselt, J.; Persaud, H.; Herold, M. Feature Level Fusion of Multi-Temporal ALOS PALSAR and Landsat Data for Mapping and Monitoring of Tropical Deforestation and Forest Degradation. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2013, 6, 2159-2173
    • (2013) IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens , vol.6 , pp. 2159-2173
    • Reiche, J.1    Souza, C.M.2    Hoekman, D.H.3    Verbesselt, J.4    Persaud, H.5    Herold, M.6
  • 13
    • 84997638197 scopus 로고    scopus 로고
    • Deep-STEP: A Deep Learning Approach for Spatiotemporal Prediction of Remote Sensing Data
    • Das, M.; Ghosh, S.K. Deep-STEP: A Deep Learning Approach for Spatiotemporal Prediction of Remote Sensing Data. IEEE Geosci. Remote Sens. Lett. 2016, 13, 1984-1988
    • (2016) IEEE Geosci. Remote Sens. Lett , vol.13 , pp. 1984-1988
    • Das, M.1    Ghosh, S.K.2
  • 14
    • 85010703205 scopus 로고    scopus 로고
    • GA-SVM Algorithm for Improving Land-Cover Classification Using SAR and Optical Remote Sensing Data
    • Sukawattanavijit, C.; Chen, J.; Zhang, H. GA-SVM Algorithm for Improving Land-Cover Classification Using SAR and Optical Remote Sensing Data. IEEE Geosci. Remote Sens. Lett. 2017, 14, 284-288
    • (2017) IEEE Geosci. Remote Sens. Lett , vol.14 , pp. 284-288
    • Sukawattanavijit, C.1    Chen, J.2    Zhang, H.3
  • 15
  • 16
    • 85038228468 scopus 로고    scopus 로고
    • Fusion of Sentinel-1A and Sentinel-2A data for land cover mapping: a case study in the lower Magdalena region, Colombia
    • Clerici, N.; Calderón, C.A.V.; Posada, J.M. Fusion of Sentinel-1A and Sentinel-2A data for land cover mapping: a case study in the lower Magdalena region, Colombia. J. Maps 2017, 13, 718-726
    • (2017) J. Maps , vol.13 , pp. 718-726
    • Clerici, N.1    Calderón, C.A.V.2    Posada, J.M.3
  • 19
    • 84982187372 scopus 로고    scopus 로고
    • FT-Raman and NIR spectroscopy data fusion strategy for multivariate qualitative analysis of food fraud
    • Márquez, C.; López, M.I.; Ruisánchez, I.; Callao, M.P. FT-Raman and NIR spectroscopy data fusion strategy for multivariate qualitative analysis of food fraud. Talanta 2016, 161, 80-86
    • (2016) Talanta , vol.161 , pp. 80-86
    • Márquez, C.1    López, M.I.2    Ruisánchez, I.3    Callao, M.P.4
  • 20
    • 45849101525 scopus 로고    scopus 로고
    • Classifying Multilevel Imagery From SAR and Optical Sensors by Decision Fusion
    • Waske, B.; Van der Linden, S. Classifying Multilevel Imagery From SAR and Optical Sensors by Decision Fusion. IEEE Trans. Geosci. Remote Sens. 2008, 46, 1457-1466
    • (2008) IEEE Trans. Geosci. Remote Sens , vol.46 , pp. 1457-1466
    • Waske, B.1    Van der Linden, S.2
  • 21
    • 84930012284 scopus 로고    scopus 로고
    • A Bayesian approach to combine Landsat and ALOS PALSAR time series for near real-time deforestation detection
    • Reiche, J.; De Bruin, S.; Hoekman, D.; Verbesselt, J.; Herold, M. A Bayesian approach to combine Landsat and ALOS PALSAR time series for near real-time deforestation detection. Remote Sens. 2015, 7, 4973-4996
    • (2015) Remote Sens , vol.7 , pp. 4973-4996
    • Reiche, J.1    De Bruin, S.2    Hoekman, D.3    Verbesselt, J.4    Herold, M.5
  • 22
    • 84867335433 scopus 로고    scopus 로고
    • Information fusion techniques for change detection from multi-temporal remote sensing images
    • Du, P.; Liu, S.; Xia, J.; Zhao, Y. Information fusion techniques for change detection from multi-temporal remote sensing images. Inf. Fusion 2013, 14, 19-27
    • (2013) Inf. Fusion , vol.14 , pp. 19-27
    • Du, P.1    Liu, S.2    Xia, J.3    Zhao, Y.4
  • 25
    • 84923195443 scopus 로고    scopus 로고
    • Marker controlled watershed based segmentation of multi-resolution remote sensing images
    • Gaetano, R.; Masi, G.; Poggi, G.; Verdoliva, L.; Scarpa, G. Marker controlled watershed based segmentation of multi-resolution remote sensing images. IEEE Trans. Geosci. Remote Sens. 2015, 53, 1987-3004
    • (2015) IEEE Trans. Geosci. Remote Sens , vol.53 , pp. 1987-3004
    • Gaetano, R.1    Masi, G.2    Poggi, G.3    Verdoliva, L.4    Scarpa, G.5
  • 26
    • 84971671499 scopus 로고    scopus 로고
    • Water Bodies' Mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band
    • Du, Y.; Zhang, Y.; Ling, F.; Wang, Q.; Li, W.; Li, X. Water Bodies' Mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band. Remote Sens. 2016, 8, 354
    • (2016) Remote Sens , vol.8 , pp. 354
    • Du, Y.1    Zhang, Y.2    Ling, F.3    Wang, Q.4    Li, W.5    Li, X.6
  • 28
    • 85041368549 scopus 로고    scopus 로고
    • A Theoretical Framework for Change Detection Based on a Compound Multiclass Statistical Model of the Difference Image
    • Zanetti, M.; Bruzzone, L. A Theoretical Framework for Change Detection Based on a Compound Multiclass Statistical Model of the Difference Image. IEEE Trans. Geosci. Remote Sens. 2018, 56, 1129-1143
    • (2018) IEEE Trans. Geosci. Remote Sens , vol.56 , pp. 1129-1143
    • Zanetti, M.1    Bruzzone, L.2
  • 29
    • 85034738466 scopus 로고    scopus 로고
    • A Novel Method of Unsupervised Change Detection Using Multi-Temporal PolSAR Images
    • Liu, W.; Yang, J.; Zhao, J.; Yang, L. A Novel Method of Unsupervised Change Detection Using Multi-Temporal PolSAR Images. Remote Sens. 2017, 9, 1135
    • (2017) Remote Sens , vol.9 , pp. 1135
    • Liu, W.1    Yang, J.2    Zhao, J.3    Yang, L.4
  • 30
    • 85013001633 scopus 로고    scopus 로고
    • Segmentation-Based Fine Registration of Very High Resolution Multitemporal Images
    • Han, Y.; Bovolo, F.; Bruzzone, L. Segmentation-Based Fine Registration of Very High Resolution Multitemporal Images. IEEE Trans. Geosci. Remote Sens. 2017, 55, 2884-2897
    • (2017) IEEE Trans. Geosci. Remote Sens , vol.55 , pp. 2884-2897
    • Han, Y.1    Bovolo, F.2    Bruzzone, L.3
  • 31
    • 85021814635 scopus 로고    scopus 로고
    • Multitemporal SAR Image Despeckling Based on Block-Matching and Collaborative Filtering
    • Chierchia, G.; Gheche, M.E.; Scarpa, G.; Verdoliva, L. Multitemporal SAR Image Despeckling Based on Block-Matching and Collaborative Filtering. IEEE Trans. Geosci. Remote Sens. 2017, 55, 5467-5480
    • (2017) IEEE Trans. Geosci. Remote Sens , vol.55 , pp. 5467-5480
    • Chierchia, G.1    Gheche, M.E.2    Scarpa, G.3    Verdoliva, L.4
  • 33
    • 84880060882 scopus 로고    scopus 로고
    • Leaf Area Index Estimation of Boreal and Subarctic Forests Using VV/HH ENVISAT/ASAR Data of Various Swaths
    • Manninen, T.; Stenberg, P.; Rautiainen, M.; Voipio, P. Leaf Area Index Estimation of Boreal and Subarctic Forests Using VV/HH ENVISAT/ASAR Data of Various Swaths. IEEE Trans. Geosci. Remote Sens. 2013, 51, 3899-3909
    • (2013) IEEE Trans. Geosci. Remote Sens , vol.51 , pp. 3899-3909
    • Manninen, T.1    Stenberg, P.2    Rautiainen, M.3    Voipio, P.4
  • 34
    • 84905750183 scopus 로고    scopus 로고
    • Radiometric quality and performance of TIMESAT for smoothing moderate resolution imaging spectroradiometer enhanced vegetation index time series from western Bahia State, Brazil
    • Borges, E.F.; Sano, E.E.; Medrado, E. Radiometric quality and performance of TIMESAT for smoothing moderate resolution imaging spectroradiometer enhanced vegetation index time series from western Bahia State, Brazil. J. Appl. Remote Sens. 2014, 8, doi:10.1117/1.JRS.8.083580
    • (2014) J. Appl. Remote Sens , vol.8
    • Borges, E.F.1    Sano, E.E.2    Medrado, E.3
  • 35
    • 85027938675 scopus 로고    scopus 로고
    • Impacts of Feature Normalization on Optical and SAR Data Fusion for Land Use/Land Cover Classification
    • Zhang, H.; Lin, H.; Li, Y. Impacts of Feature Normalization on Optical and SAR Data Fusion for Land Use/Land Cover Classification. IEEE Geosci. Remote Sens. Lett. 2015, 12, 1061-1065
    • (2015) IEEE Geosci. Remote Sens. Lett , vol.12 , pp. 1061-1065
    • Zhang, H.1    Lin, H.2    Li, Y.3
  • 36
    • 84926163182 scopus 로고    scopus 로고
    • Pixel-and feature-level fusion of hyperspectral and lidar data for urban land-use classification
    • Man, Q.; Dong, P.; Guo, H. Pixel-and feature-level fusion of hyperspectral and lidar data for urban land-use classification. Int. J. Remote Sens. 2015, 36, 1618-1644
    • (2015) Int. J. Remote Sens , vol.36 , pp. 1618-1644
    • Man, Q.1    Dong, P.2    Guo, H.3
  • 38
    • 33845645571 scopus 로고    scopus 로고
    • ERS-2 SAR and IRS-1C LISS III data fusion: A PCA approach to improve remote sensing based geological interpretation
    • Pal, S.K.; Majumdar, T.J.; Bhattacharya, A.K. ERS-2 SAR and IRS-1C LISS III data fusion: A PCA approach to improve remote sensing based geological interpretation. ISPRS J. Photogramm. Remote Sens. 2007, 61, 281-297
    • (2007) ISPRS J. Photogramm. Remote Sens , vol.61 , pp. 281-297
    • Pal, S.K.1    Majumdar, T.J.2    Bhattacharya, A.K.3
  • 39
    • 1042266200 scopus 로고    scopus 로고
    • Soil moisture retrieval using the passive/active L-and S-band radar/radiometer
    • Bolten, J.D.; Lakshmi, V.; Njoku, E.G. Soil moisture retrieval using the passive/active L-and S-band radar/radiometer. IEEE Trans. Geosci. Remote Sens. 2003, 41, 2792-2801
    • (2003) IEEE Trans. Geosci. Remote Sens , vol.41 , pp. 2792-2801
    • Bolten, J.D.1    Lakshmi, V.2    Njoku, E.G.3
  • 42
    • 85019677672 scopus 로고    scopus 로고
    • Testing a Modified PCA-Based Sharpening Approach for Image Fusion
    • Jelének, J.; Kopačková, V.; Koucká, L.; Mišurec, J. Testing a Modified PCA-Based Sharpening Approach for Image Fusion. Remote Sens. 2016, 8, 794
    • (2016) Remote Sens , vol.8 , pp. 794
    • Jelének, J.1    Kopačková, V.2    Koucká, L.3    Mišurec, J.4
  • 45
    • 85025175733 scopus 로고    scopus 로고
    • Sentinel-1A SAR and sentinel-2A MSI data fusion for urban ecosystem service mapping
    • Haas, J.; Ban, Y. Sentinel-1A SAR and sentinel-2A MSI data fusion for urban ecosystem service mapping. Remote Sens. Appl. Soc. Environ. 2017, 8, 41-53
    • (2017) Remote Sens. Appl. Soc. Environ , vol.8 , pp. 41-53
    • Haas, J.1    Ban, Y.2
  • 46
    • 84942518161 scopus 로고    scopus 로고
    • Assessment of an Operational System for Crop Type Map Production Using High Temporal and Spatial Resolution Satellite Optical Imagery
    • Inglada, J.; Arias, M.; Tardy, B.; Hagolle, O.; Valero, S.; Morin, D.; Dedieu, G.; Sepulcre, G.; Bontemps, S.; Defourny, P.; et al. Assessment of an Operational System for Crop Type Map Production Using High Temporal and Spatial Resolution Satellite Optical Imagery. Remote Sens. 2015, 7, 12356-12379
    • (2015) Remote Sens , vol.7 , pp. 12356-12379
    • Inglada, J.1    Arias, M.2    Tardy, B.3    Hagolle, O.4    Valero, S.5    Morin, D.6    Dedieu, G.7    Sepulcre, G.8    Bontemps, S.9    Defourny, P.10
  • 48
    • 85042527890 scopus 로고    scopus 로고
    • (accessed on 13 December 2017)
    • THEIA Home Page. Available online: http://www.theia-land.fr (accessed on 13 December 2017)
    • THEIA Home Page
  • 49
    • 84926382691 scopus 로고    scopus 로고
    • A Multi-Temporal and Multi-Spectral Method to Estimate Aerosol Optical Thickness over Land, for the Atmospheric Correction of FormoSat-2, LandSat, VENmS and Sentinel-2 Images
    • Hagolle, O.; Huc, M.; Villa Pascual, D.; Dedieu, G. A Multi-Temporal and Multi-Spectral Method to Estimate Aerosol Optical Thickness over Land, for the Atmospheric Correction of FormoSat-2, LandSat, VENmS and Sentinel-2 Images. Remote Sens. 2015, 7, 2668-2691
    • (2015) Remote Sens , vol.7 , pp. 2668-2691
    • Hagolle, O.1    Huc, M.2    Villa Pascual, D.3    Dedieu, G.4
  • 50
    • 85021724055 scopus 로고    scopus 로고
    • Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
    • Zhang, K.; Zuo, W.; Chen, Y.; Meng, D.; Zhang, L. Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising. IEEE Trans. Image Process. 2017, 26, 3142-3155
    • (2017) IEEE Trans. Image Process , vol.26 , pp. 3142-3155
    • Zhang, K.1    Zuo, W.2    Chen, Y.3    Meng, D.4    Zhang, L.5
  • 54
    • 85038568173 scopus 로고    scopus 로고
    • Deep convolutional neural networks for building extraction from orthoimages and dense image matching point clouds
    • Maltezos, E.; Doulamis, N.; Doulamis, A.; Ioannidis, C. Deep convolutional neural networks for building extraction from orthoimages and dense image matching point clouds. J. Appl. Remote Sens. 2017, 11, doi:10.1117/1.JRS.11.042620
    • (2017) J. Appl. Remote Sens , vol.11
    • Maltezos, E.1    Doulamis, N.2    Doulamis, A.3    Ioannidis, C.4
  • 56
    • 85021951898 scopus 로고    scopus 로고
    • Deep Fully Convolutional Network-Based Spatial Distribution Prediction for Hyperspectral Image Classification
    • Jiao, L.; Liang, M.; Chen, H.; Yang, S.; Liu, H.; Cao, X. Deep Fully Convolutional Network-Based Spatial Distribution Prediction for Hyperspectral Image Classification. IEEE Trans. Geosci. Remote Sens. 2017, 55, 5585-5599
    • (2017) IEEE Trans. Geosci. Remote Sens , vol.55 , pp. 5585-5599
    • Jiao, L.1    Liang, M.2    Chen, H.3    Yang, S.4    Liu, H.5    Cao, X.6
  • 57
    • 85041506038 scopus 로고    scopus 로고
    • Deep Convolutional Neural Networks for the Classification of Snapshot Mosaic Hyperspectral Imagery
    • Fotiadou, K.; Tsagkatakis, G.; Tsakalides, P. Deep Convolutional Neural Networks for the Classification of Snapshot Mosaic Hyperspectral Imagery. Electron. Imaging 2017, 2017, 185-190
    • (2017) Electron. Imaging , vol.2017 , pp. 185-190
    • Fotiadou, K.1    Tsagkatakis, G.2    Tsakalides, P.3
  • 61
    • 85042532733 scopus 로고    scopus 로고
    • (accessed on 13 December 2017)
    • Orfeo Toolbox: Temporal Gap-Filling. Available online: http://tully.ups-tlse.fr/jordi/temporalgapfilling (accessed on 13 December 2017)
    • Orfeo Toolbox: Temporal Gap-Filling
  • 62
    • 84874650786 scopus 로고    scopus 로고
    • Support Vector Regression-Based Downscaling for Intercalibration of Multiresolution Satellite Images
    • Zhang, H.; Huang, B. Support Vector Regression-Based Downscaling for Intercalibration of Multiresolution Satellite Images. IEEE Trans. Geosci. Remote Sens. 2013, 51, 1114-1123
    • (2013) IEEE Trans. Geosci. Remote Sens , vol.51 , pp. 1114-1123
    • Zhang, H.1    Huang, B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.