| 1. |
- Ban, Yifang, et al.
(författare)
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Change detection techniques : A review
- 2016
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Ingår i: Remote Sensing and Digital Image Processing. - Cham : Springer. ; , s. 19-43
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Konferensbidrag (refereegranskat)abstract
- With its synoptic view and the repeatability, satellite remote sensing can provide timely, accurate and consistent information about earth’s surface for costeffective monitoring of environmental changes. In this chapter, recent development in change detection techniques using multitemporal remotely sensed images were reviewed. The chapter covers change detection methods for both optical and SAR images. Various aspects of change detection processes were presented including data preprocessing, change image generation and change detection algorithms such as unsupervised and supervised change detection as well as pixel-based and objectbased change detection. The review shows that significant progress has been made in the field of change detection and innovative methods have been developed for change detection using both multitemporal SAR and optical data. Attempts have been made for change detection using multitemporal multisensor/cross-sensor images. The review also identified a number of challenges and opportunities in change detection.
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| 2. |
- Ban, Yifang, et al.
(författare)
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EO4Urban : Sentinel-1A SAR and Sentinel-2A MSI data for global urban services
- 2017
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Ingår i: 2017 Joint Urban Remote Sensing Event, JURSE 2017. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509058082
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Konferensbidrag (refereegranskat)abstract
- The overall objective of this research is to evaluate multitemporal Sentinel-1A SAR and Sentinel-2A MSI data for global urban services using innovative methods and algorithms, namely KTH-Pavia Urban Extractor, a robust algorithm for urban extent extraction and KTH-SEG, a novel object-based classification method for detailed urban land cover mapping. Ten cities around the world in different geographical and environmental conditions were selected as study areas. Large volumes of Sentinel-1A SAR and Sentinel-2A MSI data were acquired during the vegetation season in 2015 and 2016. The urban extraction results showed that urban areas and small towns could be well extracted using multitemporal Sentinel-1 SAR, Sentinel-2A MSI data and their fusion using the Urban Extractors developed within the project. For urban land cover mapping, multitemporal Sentinel-1A SAR data alone yielded an overall classification accuracy of 60% for Stockholm. Sentinel-2A MSI data as well as the fusion of Sentinel-1A SAR and Sentinel-2A MSI data, however, produced much higher classification accuracies, both reached 80%.
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| 3. |
- Ban, Yifang, et al.
(författare)
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EO4Urban : First-year results on Sentinel-1A SAR and Sentinel-2A MSI data for global urban services
- 2016
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Ingår i: European Space Agency, (Special Publication) ESA SP. - 9789292213053
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Konferensbidrag (refereegranskat)abstract
- The overall objective of this research is to evaluate multitemporal Sentinel-1A SAR and Sentinel-2A MSI data for global urban services using innovative methods and algorithms, namely KTH-Pavia Urban Extractor, a robust algorithm for urban extent extraction and KTHSEG, a novel object-based classification method for detailed urban land cover mapping. Ten cities around the world in different geographical and environmental conditions were selected as study areas. Large volume of Sentinel-1A SAR and Sentinel-2A MSI data were acquired during vegetation season in 2015 and 2016. The preliminary urban extraction results showed that urban areas and small towns could be well extracted using multitemporal Sentinel-1A SAR data with the KTH-Pavia Urban Extractor. For urban land cover mapping, multitemporal Sentinel-1A SAR data alone yielded an overall classification accuracy of 60% for Stockholm. Sentinel-2A MSI data as well as the fusion of Sentinel-1A SAR and Sentinel-2A MSI data, however, produced much higher classification accuracies, both reached 80%.
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| 4. |
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| 5. |
- Ban, Yifang, et al.
(författare)
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Fusion of multitemporal spaceborne SAR and optical data for urban mapping and urbanization monitoring
- 2016
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Ingår i: Remote Sensing and Digital Image Processing. - Cham : Springer. - 1567-3200 .- 2215-1842. ; , s. 107-123
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Tidskriftsartikel (refereegranskat)abstract
- The overall objective of this research is to evaluate multitemporal spaceborne SAR and optical data for urban land cover mapping and urbanization monitoring. Multitemporal Sentinel-1A SAR and historical ERS SAR and ENVISAT ASAR data as well as HJ-1B multispectral data were acquired in Beijing, Chendgdu and Nanchang, China where rapid urbanization has taken place. KTHSEG, a novel object-based classification method is adopted for urban land cover mapping while KTH-Pavia Urban Extractor, a robust algorithm is improved for urban extent extraction and urbanization monitoring. The research demonstrates that, for urban land cover classification, the fusion of multitemporal SAR and optical data is superior to SAR or optical data alone. The second best classification result is achieved using fusion of 4-date SAR and one HJ-1B image. The results indicate that carefully selected multitemporal SAR dataset and its fusion with optical data could produce nearly as good classification accuracy as the whole multitemporal dataset. The results also show that KTH-SEG, the edge-aware region growing and merging segmentation algorithm, is effective for classification of SAR, optical and their fusion. KTH-SEG outperforms eCognition, the commonly used commercial software, for image segmentation and classification of linear features. For Urban extent extraction, single-date and multitemporal SAR data including ERS SAR, ENVISAT ASAR and Sentinel-1A SAR achieved very promising results in all study areas using the improved KTH-Pavia Urban Extractor. The results showed that urban areas as well as small towns and villages could be well extracted using multitemporal Sentinel-1A SAR data while major urban areas could be well extracted using a single-date single-polarization SAR image. The results clearly demonstrate that multitemporal SAR data are cost- and time-effective way for monitoring spatiotemporal patterns of urbanization.
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| 6. |
- Ban, Yifang
(författare)
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Multitemporal remote sensing : Current status, trends and challenges
- 2016
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Ingår i: Remote Sensing and Digital Image Processing. - Cham : Springer International Publishing. ; , s. 1-18
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Konferensbidrag (refereegranskat)abstract
- Our planet is facing unprecedented environmental challenges including rapid urbanization, deforestation, pollution, loss of biodiversity, sea-level rising, melting polar ice-caps and climate change. With its synoptic view and the repeatability, remote sensing offers a powerful and effective means to observe and monitor our changing planet at local, regional and global scale. Since the launch of Landsat-1 in 1972, numerous Earth Observation satellites have been launched providing large volumes of multitemporal data acquired by multispectral, hyperspectral, passive microwave, synthetic aperture radar (SAR), and LiDAR sensors. This chapter first presents an overview of the Earth Observation sensors and trends in multitemporal observation capacity. Then the current status, challenges and opportunities of multitemporal remote sensing are discussed. Finally the synopsis of the book is provided covering a wide array of methods and techniques in processing and analysis of multitemporal remotely sensed images as well as a variety of application examples in both land and aquatic environments.
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| 7. |
- Ban, Yifang
(författare)
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Preface
- 2016
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Ingår i: Remote Sensing and Digital Image Processing. - 1567-3200 .- 2215-1842. ; , s. v-vi
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Tidskriftsartikel (refereegranskat)
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| 8. |
- Ban, Yifang, et al.
(författare)
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Spaceborne SAR Data for Global Urban Mapping at 30m Resolution Utilizing a Robust Urban Extractor
- 2015
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Ingår i: ISPRS journal of photogrammetry and remote sensing (Print). - : Elsevier BV. - 0924-2716 .- 1872-8235. ; 103
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Tidskriftsartikel (refereegranskat)abstract
- With more than half of the world population now living in cities and 1.4 billion more people expected to move into cities by 2030, urban areas pose significant challenges on local, regional and global environment. Timely and accurate information on spatial distributions and temporal changes of urban areas are therefore needed to support sustainable development and environmental change research. The objective of this research is to evaluate spaceborne SAR data for improved global urban mapping using a robust processing chain, the KTH-Pavia Urban Extractor. The proposed processing chain includes urban extraction based on spatial indices and Grey Level Co-occurrence Matrix (GLCM) textures, an existing method and several improvements i.e., SAR data preprocessing, enhancement, and post-processing. ENVISAT Advanced Synthetic Aperture Radar (ASAR) C-VV data at 30m resolution were selected over 10 global cities and a rural area from six continents to demonstrated robustness of the improved method. The results show that the KTH-Pavia Urban Extractor is effective in extracting urban areas and small towns from ENVISAT ASAR data and built-up areas can be mapped at 30m resolution with very good accuracy using only one or two SAR images. These findings indicate that operational global urban mapping is possible with spaceborne SAR data, especially with the launch of Sentinel-1 that provides SAR data with global coverage, operational reliability and quick data delivery.
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| 9. |
- Bo, Mao, et al.
(författare)
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Real-time visualization of 3D city models at street-level based on visual saliency
- 2015
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Ingår i: Science China: Earth Sciences. - : Springer Science and Business Media LLC. - 1674-7313 .- 1869-1897. ; 58:3, s. 448-461
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Tidskriftsartikel (refereegranskat)abstract
- Street-level visualization is an important application of 3D city models. Challenges to street-level visualization include the cluttering of buildings due to fine detail and visualization performance. In this paper, a novel method is proposed for street-level visualization based on visual saliency evaluation. The basic idea of the method is to preserve these salient buildings in a scene while removing those that are non-salient. The method can be divided into pre-processing procedures and real-time visualization. The first step in pre-processing is to convert 3D building models at higher Levels of Detail (LoDs) into LoD1 models with simplified ground plans. Then, a number of index viewpoints are created along the streets; these indices refer to both the position and the direction of each street site. A visual saliency value is computed for each building, with respect to the index site, based on a visual difference between the original model and the generalized model. We calculate and evaluate three methods for visual saliency: local difference, global difference and minimum projection area. The real-time visualization process begins by mapping the observer to its closest indices. The street view is then generated based on the building information stored in those indexes. A user study shows that the local visual saliency method performs better than do the global visual saliency, area and image-based methods and that the framework proposed in this paper may improve the performance of 3D visualization.
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| 10. |
- Cartalis, C., et al.
(författare)
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Earth observation in support of science and applications development in the field "land and Environment" : Synthesis results from the ESA-most dragon cooperation Programme
- 2015
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Ingår i: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. ; , s. 1075-1081
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Konferensbidrag (refereegranskat)abstract
- Dragon is a cooperation Programme between the European Space Agency (ESA) and the Ministry of Science and Technology (MOST) of the P.R. China. The Programme, initiated in 2004, focuses on the exploitation of ESA, Third Party Missions (TPM) and Chinese Earth Observation (EO) data for geo-science and applications development in land, ocean and atmospheric applications. In particular, the Programme brings together joint Sino- European teams to investigate 50 thematic projects. In this paper, the results of the research projects1 in the thematic field "Land and Environment" will be briefly presented, whereas emphasis will be given in the assessment of the usefulness of the results for an integrated assessment of the state of the environment in the respective study areas. Furthermore new knowledge gained in such fields as desertification assessment, drought and epidemics' monitoring, forest modeling, cropwatch monitoring, climate change vulnerability (including climate change adaptation and mitigation plans), urbanization monitoring and land use/cover change assessment and monitoring, will be presented. Such knowledge will be also linked to the capacities of Earth Observation systems (and of the respective EO data) to support the temporal, spatial and spectral requirements of the research studies. The potential of DRAGON to support such targets as "technology and knowledge transfer at the bilateral level", "common EO database for exploitation" and "data sharing and open access data policy" will be also presented. Finally special consideration will be given in highlighting the replication potential of the techniques as developed in the course of the projects, as well as on the importance of the scientific results for environmental policy drafting and decision making.
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