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GROUND OBJECT RECOGNITION USING COMBINED HIGH RESOLUTION AIRBORNE IMAGES AND DSM

Q. Zhan, Y. Liang, C. Wei, Y. Xiao
2012 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
A novel method called Sparse Representation is introduced to extract ground objects from airborne images.  ...  A refinement procedure based on elevation histogram is carried on to improve the coarse classification due to misclassification of trees/vegetation and buildings/road.  ...  The Vaihingen data set was provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) [Cramer, 2010] : http://www.ifp.uni-stuttgart.de/dgpf/DKEP-Allg.html  ... 
doi:10.5194/isprsarchives-xxxix-b3-573-2012 fatcat:zp2sulvstvdaldoguq5bs3vpzy

THE POTENTIAL OF BUILDING DETECTION FROM SAR AND LIDAR USING DEEP LEARNING

Z. Nordin, H. Z. M. Shafri, A. F. Abdullah, S. J. Hashim
2019 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Thus, this paper reviews current techniques and future trends of multi-sources Remote Sensing for building extraction.  ...  mapping approach offers practicality and significant cost savings for the nation minimizing the need for ground control points on the ground in addition to providing high-resolution, day-and-night, cloud  ...  ., & Rastiveis, (2017) conducted the research on an automatic urban objects extraction using airborne Remote Sensing data to process and efficiently interpret the vast amount of airborne imagery and LIDAR  ... 
doi:10.5194/isprs-archives-xlii-4-w16-489-2019 fatcat:xhlrmiru5reo5fbqkhafxucl6a

Pattern Recognition in Remote Sensing

Selim Aksoy, Nicolas H. Younan, Lorenzo Bruzzone
2010 Pattern Recognition Letters  
The paper by Valero et al. presents a new method for extracting roads in very high resolution remotely sensed images based on advanced directional morphological operators called path openings and path  ...  The paper by Bovolo et al. presents a novel method for change detection based on change vector analysis and support vector data description technique.  ... 
doi:10.1016/j.patrec.2010.04.014 fatcat:jwx6imthxjfg7aakkeu4fpjtlu

CNN-BASED FEATURE-LEVEL FUSION OF VERY HIGH RESOLUTION AERIAL IMAGERY AND LIDAR DATA

S. Daneshtalab, H. Rastiveis, B. Hosseiny
2019 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
In this paper, a CNN-based feature-level framework is proposed to integrate LiDAR data and aerial imagery for object classification in urban area.  ...  In our method, after generating low-level descriptors and fusing them in a feature-level fusion by layer-stacking, the proposed framework employs a novel CNN to extract the spectral-spatial features for  ...  ACKNOWLEDGEMENTS The authors would like to thank the National Center for Airborne Laser Mapping and the Hyperspectral Image Analysis Laboratory at the University of Houston for acquiring and providing  ... 
doi:10.5194/isprs-archives-xlii-4-w18-279-2019 fatcat:w3hzfgmrdnc63m7kvs2zcpm5fq

2020 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13

2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., +, JSTARS 2020 941-949 A Self-Supervised Learning Framework for Road Centerline Extraction From High-Resolution Remote Sensing Images.  ...  ., +, JSTARS 2020 3958-3974 A Self-Supervised Learning Framework for Road Centerline Extraction From High-Resolution Remote Sensing Images.  ...  A New Deep-Learning-Based Approach for Earthquake-Triggered Landslide Detection From Single-Temporal RapidEye Satellite Imagery. Yi, Y., +, JSTARS 2020  ... 
doi:10.1109/jstars.2021.3050695 fatcat:ycd5qt66xrgqfewcr6ygsqcl2y

The Combined Use of Airborne Remote Sensing Techniques within a GIS Environment for the Seismic Vulnerability Assessment of Urban Areas: An Operational Application

Antonio Costanzo, Antonio Montuori, Juan Silva, Malvina Silvestri, Massimo Musacchio, Fawzi Doumaz, Salvatore Stramondo, Maria Buongiorno
2016 Remote Sensing  
of urban areas, especially considering the actual lack of widely and freely available high-resolution space-borne remote sensing imagery.  ...  On these bases, the joint use of airborne remotely-sensed measurements and GIS tools could be very useful for multi-risk assessment purposes.  ...  The authors wish to thank all reviewers for their comments on the paper, as these have allowed the improvement of the work. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs8020146 fatcat:qt33iyr4wfaabdmeqypctxdnly

Fusion of Optical and Thermal Imagery and LiDAR Data for Application to 3-D Urban Environment and Structure Monitoring [chapter]

Anna Brook, Marijke Vandewal, Eyal Ben-Dor
2012 Remote Sensing - Advanced Techniques and Platforms  
The 3-D urban application is based on an integrated data set: spectral models, ground camera and airborne images, and LiDAR data.  ...  Then the road model is established, based on the continuous network of points which are used to extract information such as centerline, edge and width of the road (Akel et al. 2003; Hinz & Baumgartner  ...  Fusion of Optical and Thermal Imagery and LiDAR Data for Application to 3-D Urban Environment and Structure Monitoring, Remote Sensing -Advanced Techniques and Platforms, Dr.  ... 
doi:10.5772/36066 fatcat:3outhr4aqfehfnna3afdlni6mi

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., and Drake, V.A., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674  ...  and Hanssen, R.F., Incorporating Temporary Coherent Li, X., Yeo, T.S., Yang, Y., Chi, C., Zuo, F., Hu, X., and Pi, Y., Refo-cusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight SAR Imaging  ...  ., +, TGRS Jan. 2019 406-415 A Novel Two-Step Registration Method for Remote Sensing Images Based on Deep and Local Features.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

AutoGeoLabel: Automated Label Generation for Geospatial Machine Learning [article]

Conrad M Albrecht, Fernando Marianno, Levente J Klein
2022 arXiv   pre-print
We evaluate a big data processing pipeline to auto-generate labels for remote sensing data. It is based on rasterized statistical features extracted from surveys such as e.g. LiDAR measurements.  ...  The general method proposed here is platform independent, and it can be adapted to generate labels for other satellite modalities in order to enable machine learning on overhead imagery for land use classification  ...  Based on an airborne LiDAR survey for New York City, we demonstrated and explored a novel approach to use simple statistical features of remote sensing data in order to create data classes.  ... 
arXiv:2202.00067v1 fatcat:ytf3422ggbfctbeqaxgz3gby3e

2014 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 7

2014 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., and Foerster, S  ...  ., +, JSTARS July 2014 2942-2956 Image resolution A New Region Growing-Based Method for Road Network Extraction and Its Application on Different Resolution SAR Images.  ...  ., +, JSTARS Oct. 2014 4199-4217 A New Region Growing-Based Method for Road Network Extraction and Its Application on Different Resolution SAR Images.  ... 
doi:10.1109/jstars.2015.2397347 fatcat:ib3tjwsjsnd6ri6kkklq5ov37a

Three-Dimensional Urban Land Cover Classification by Prior-Level Fusion of LiDAR Point Cloud and Optical Imagery

Yanming Chen, Xiaoqiang Liu, Yijia Xiao, Qiqi Zhao, Sida Wan
2021 Remote Sensing  
However, few studies have focused on the fusion of LiDAR point clouds and optical imagery for three-dimensional land cover classification, especially using a deep learning framework.  ...  Our proposed prior-fusion strategy has higher overall accuracy (82.47%) on data from the International Society for Photogrammetry and Remote Sensing, compared with the baseline (74.62%), point-level (79.86%  ...  Acknowledgments: The Vaihingen data set was accessed on 9 May 2018 from the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) [44] : http://www.ifp.uni-stuttgart. de/dgpf/DKEPAllg.html  ... 
doi:10.3390/rs13234928 fatcat:aiz6kel3jvbdjknj2atz56xjjq

Multisource and Multitemporal Data Fusion in Remote Sensing [article]

Pedram Ghamisi, Behnood Rasti, Naoto Yokoya, Qunming Wang, Bernhard Hofle, Lorenzo Bruzzone, Francesca Bovolo, Mingmin Chi, Katharina Anders, Richard Gloaguen, Peter M. Atkinson, Jon Atli Benediktsson
2018 arXiv   pre-print
for researchers at different levels (i.e., students, researchers, and senior researchers) willing to conduct novel investigations on this challenging topic by supplying sufficient detail and references  ...  processing of remotely sensed data.  ...  They developed a method to fuse airborne LiDAR and multispectral imagery with two main consecutive steps: 1) Point cloud segmentation (region growing) and classification (mean shift) using 3D LiDAR and  ... 
arXiv:1812.08287v1 fatcat:hmojxdoaybc6vjeto5s3x7b6z4

FOREST ROADIDENTIFICATION AND EXTRACTIONOF THROUGH ADVANCED LOG MATCHING TECHNIQUES

W. Zhang, B. Hu, L. Quist
2017 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The algorithm utilized Laplacian of Gaussian (LoG) filter and slope calculation on high resolution multispectral imagery and LiDAR data respectively to extract both primary road and secondary road segments  ...  A novel algorithm for forest road identification and extraction was developed.  ...  for providing the very high resolution aerial imagery.  ... 
doi:10.5194/isprs-archives-xlii-3-w3-201-2017 fatcat:azlw4aoq6fco7isyari3nhmdam

Road Feature Extraction from High Resolution Aerial Images Upon Rural Regions Based on Multi-Resolution Image Analysis and Gabor Filters [chapter]

Hang Jin, Marc Miska, Edward Chung, Maoxun Li, Yanming Feng
2012 Remote Sensing - Advanced Techniques and Platforms  
., 2001) , a fully automated road extraction strategy based on Kohonen's self-organizing map (SOM) is proposed to detect road information in high-resolution multi-spectral aerial imagery.  ...  Traditional methods for acquiring road information include i) ground surveying and ii) delineating roads from remotely sensed imagery (Zhang & Couloigner, 2004) .  ...  Road feature extraction for rural and urban areas from high spatial resolution remotely sensed imagery is discussed separately in this section.  ... 
doi:10.5772/45893 fatcat:rgsrzd7mmvbmpbugdg2rbbuhoe

Remote Sensing Satellite Image Processing Techniques for Image Classification: A Comprehensive Survey

Sowmya D., P. Deepa, Venugopal K.
2017 International Journal of Computer Applications  
In remote sensing, the image processing techniques can be categories in to four main processing stages: Image preprocessing, Enhancement, Transformation and Classification.  ...  This paper is a brief survey of advance technological aspects of Digital Image Processing which are applied to remote sensing images obtained from various satellite sensors.  ...  Dutta et al., [9] Categorize vegetation canopy based on leaves area per density( LAD) in dense forest using airborne LIDAR remote sensing imagery and hyper spectral imagery based on Pit-Free Canopy Height  ... 
doi:10.5120/ijca2017913306 fatcat:2bzxqgiy2nfkldftt5wgj4v4e4
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