| 1. |
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| 2. |
- 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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| 3. |
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| 4. |
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| 5. |
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| 6. |
- 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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| 7. |
- 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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| 8. |
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| 9. |
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| 10. |
- 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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| 11. |
- Ban, Yifang, et al.
(författare)
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Fusion of Quickbird MS and RADARSAT SAR data for urban land-cover mapping : object-based and knowledge-based approach
- 2010
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Ingår i: International Journal of Remote Sensing. - : Taylor & Francis. - 0143-1161 .- 1366-5901. ; 31:6, s. 1391-1410
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this research is to evaluate Quickbird multi-spectral (MS) data, multi-temporal RADARSAT Fine-Beam C-HH synthetic aperture radar (SAR) data and fusion of Quickbird MS and RADARSAT SAR for urban land-use/land-cover mapping. One scene of Quickbird multi-spectral imagery was acquired on 18 July 2002 and five-date RADARSAT fine-beam SAR images were acquired during May to August 2002. Quickbird MS images and RADARSAT SAR data were classified using an object-based and rule-based approach. The results demonstrated that the object-based and knowledge-based approach was effective in extracting urban land-cover classes. For identifying 16 land-cover classes, object-based and rule-based classification of Quickbird MS data yielded an overall classification accuracy of 87.9% (kappa: 0.868). For identifying 11 land-cover classes, object-based and rule-based classification of RADARSAT SAR data yielded an overall accuracy: 86.6% (kappa: 0.852). Decision level fusion of Quickbird classification and RADARSAT SAR classification was able to take advantage of the best classifications of both optical and SAR data, thus significantly improving the classification accuracies of several land-cover classes (25% for pasture, 19% for soybeans, 17% for rapeseeds) even though the overall classification accuracy of 16 land-cover classes increased only slightly to 89.5% (kappa: 0.885).
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| 12. |
- Ban, Yifang, et al.
(författare)
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Fusion of RADARSAT fine-beam SAR and QuickBird data for land-cover mapping and change detection
- 2007
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Ingår i: Geoinformatics 2007Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 9780819469120 ; , s. H7522-H7522
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Konferensbidrag (refereegranskat)abstract
- The objective of this research is to evaluate multitemporal RADARSAT Fine-Beam C-HH SAR data, QuickBird MS data, and fusion of SAR and MS for urban land-cover mapping and change detection One scene of QuickBird imagery was acquired on July 18, 2002 and five-date RADARSAT fine-beam SAR images were acquired during May to August in 2002. Landsat TM imagery from 1988 was used for change detection. QucikBird images were classified using an object-based and rule-based approach. RADARSAR SAR texture images were classified using a hybrid approach. The results demonstrated that, for identifying 19 land-cover classes, object-based and rule-based classification of Quickbird data yielded an overall classification accuracy of 86.7% (kappa 0.857). For identifying I I land-cover classes, ANN classification of the combined Mean, Standard Deviation and Correlation texture images yielded an overall accuracy: 71.4%, (Kappa: 0.69). The hybrid classification of RADARSAT fine-beam SAR data improved the ANN classification accuracy to 83.56% (kappa: 0.803). Decision level fusion of RADARSAT SAR and QuickBird data improved the classification accuracy of several land cover classes. The post-classification change detection was able to identify the areas of significant change, for example, major new roads, new low-density and high-density, builtup areas and golf courses, even though the change detection results contained large amount of noise due to classification errors of individual images. QuickBrid classification result was able add detailed change information to the major changes identified.
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| 13. |
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| 14. |
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| 15. |
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| 16. |
- Ban, Yifang
(författare)
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Multitemporal ERS-1 SAR and Landsat TM data for agricultural crop classification : comparison and synergy
- 2003
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Ingår i: Canadian journal of remote sensing. - : Informa UK Limited. - 0703-8992 .- 1712-7971. ; 29:4, s. 518-526
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this research was to evaluate the synergistic effects of multitemporal European remote sensing satellite 1 (ERS-1) synthetic aperture radar (SAR) and Landsat thematic mapper (TM) data for crop classification using a per-field artificial neural network (ANN) approach. Eight crop types and conditions were identified: winter wheat, corn (good growth), corn (poor growth), soybeans (good growth), soybeans (poor growth), barley/oats, alfalfa, and pasture. With the per-field approach using a feed-forward ANN, the overall classification accuracy of three-date early- to mid-season SAR data improved almost 20%, and the best classification of a single-date (5 August) SAR image improved the overall accuracy by about 26%, in comparison to a per-pixel maximum-likelihood classifier (MLC). Both single-date and multitemporal SAR data demonstrated their abilities to discriminate certain crops in the early and mid-season; however, these overall classification accuracies (<60%) were not sufficiently high for operational crop inventory and analysis, as the single-parameter, high-incidence-angle ERS-1 SAR system does not provide sufficient differences for eight crop types and conditions. The synergy of TM3, TM4, and TM5 images acquired on 6 August and SAR data acquired on 5 August yielded the best per-field ANN classification of 96.8% (kappa coefficient = 0.96). It represents an 8.3% improvement over TM3, TM4, and TM5 classification alone and a 5% improvement over the per-pixel classification of TM and 5 August SAR data. These results clearly demonstrated that the synergy of TM and SAR data is superior to that of a single sensor and the ANN is more robust than MLC for per-field classification. The second-best classification accuracy of 95.9% was achieved using the combination of TM3, TM4, TM5, and 24 July SAR data. The combination of TM3, TM4, and TM5 images and three-date SAR data, however, only yielded an overall classification accuracy of 93.89% (kappa = 0.93), and the combination of TM3, TM4, TM5, and 15 June SAR data decreased the classification accuracy slightly (88.08%; kappa = 0.86) from that of TM alone. These results indicate that the synergy of satellite SAR and Landsat TM data can produce much better classification accuracy than that of Landsat TM alone only when careful consideration is given to the temporal compatibility of SAR and visible and infrared data.
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| 17. |
- Ban, Yifang, et al.
(författare)
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Multitemporal ERS-1 SAR data for crop classification: a sequential-masking approach
- 1999
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Ingår i: Canadian journal of remote sensing. - : Informa UK Limited. - 0703-8992 .- 1712-7971. ; 1999:25, s. 438-447
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Tidskriftsartikel (refereegranskat)abstract
- Based on photo-interpretation procedures, the technique of sequential masking can be used to differentiate image features using a series of multitemporal images. In this study, a set of nine ERS-1 SAR images is analyzed using this technique to determine the earliest dates for identifying different crop types in an agricultural area of southern Ontario, Canada. SAR temporal backscatter profiles of crops were generated from calibrated radar imagery. Based on these temporal backscatter profiles, per-field classifications using the sequential-masking technique were performed on the early- and mid-season multitemporal SAR data. It was found that using only three images, acquired on May 31, June 16 and July 5, it is possible to differentiate winter wheat, alfalfa/hay, barley/oats, soybeans and corn with an overall validation accuracy of 88.5% and a Kappa coefficient of 0.85.
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| 18. |
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| 19. |
- 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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| 20. |
- Ban, Yifang, et al.
(författare)
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Multitemporal Spaceborne SAR Data for Urban Change Detection in China
- 2012
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Ingår i: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. - 1939-1404 .- 2151-1535. ; 5:4, s. 1087-1094
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this research is to examine effective methods for urban change detection using multitemporal spaceborne SAR data in two rapid expanding cities in China. One scene of ERS-2 SAR C-VV image was acquired in Beijing in 1998 and in shanghai in 1999 respectively and one scene of ENVISAT ASAR C-VV image was acquired in near-anniversary dates in 2008 in Beijing and Shanghai. To compare the SAR images from different dates, a modified ratio operator that takes into account both positive and negative changes was developed to derive a change image. A generalized version of Kittler-Illingworth minimum-error thresholding algorithm was then tested to automatically classify the change image into two classes, change and no change. Various probability density functions such as Log normal, Generalized Gaussian, Nakagami ratio, and Weibull ratio were investigated to model the distribution of the change and no change classes. The results showed that Kittler-Illingworth algorithm applied to the modified ratio image is very effective in detecting temporal changes in urban areas using SAR images. Log normal and Nakagami density models achieved the best results. The Kappa coefficients of these methods were of 0.82 and 0.71 for Beijing and Shanghai respectively while the false alarm rates were 2.7% and 4.75%. The findings indicated that the change accuracies obtained using Kittler-Illingworth algorithm vary depending on how the assumed conditional class density function fits the histograms of change and no change classes.
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| 21. |
- Ban, Yifang, et al.
(författare)
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Multitemporal Spaceborne SAR data for urbanization monitoring in China : Preliminary Result
- 2010
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Ingår i: Proceedings, ESA/MOST Dragon 2 Program Midterm Symposium. - 9789292212483
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The objective of this research is to investigate multitemporal spaceborne SAR data for urbanization monitoring in China. A generalized version of Kittler- Illingworth minimum-error thresholding algorithm, that takes into account the non-Gaussian distribution of SAR images, was tested to automatically classify the change variable derived from SAR multitemporal images into two classes, change and no change. A modified ratio operator was examined for identifying both positive and negative changes by comparing the multitemporal SAR images on a pixel-by-pixel basis. Various probability density functions such as Log normal, Generalized Gaussian, Nakagami ratio, and Weibull ratio models were tested to model the distribution of the change and no change classes. The preliminary results showed that this unsupervised change detection algorithm is very effective in detecting temporal changes in urban areas using multitemporal SAR images. The initial findings indicated that change detection accuracy varies depending on how the assumed conditional class density function fits the histograms of change and no change classes.
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| 22. |
- Ban, Yifang, et al.
(författare)
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Near Real-Time Wildfire Progression Monitoring with Sentinel-1 SAR Time Series and Deep Learning
- 2020
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, the world witnessed many devastating wildfires that resulted in destructive human and environmental impacts across the globe. Emergency response and rapid response for mitigation calls for effective approaches for near real-time wildfire monitoring. Capable of penetrating clouds and smoke, and imaging day and night, Synthetic Aperture Radar (SAR) can play a critical role in wildfire monitoring. In this communication, we investigated and demonstrated the potential of Sentinel-1 SAR time series with a deep learning framework for near real-time wildfire progression monitoring. The deep learning framework, based on a Convolutional Neural Network (CNN), is developed to detect burnt areas automatically using every new SAR image acquired during the wildfires and by exploiting all available pre-fire SAR time series to characterize the temporal backscatter variations. The results show that Sentinel-1 SAR backscatter can detect wildfires and capture their temporal progression as demonstrated for three large and impactful wildfires: the 2017 Elephant Hill Fire in British Columbia, Canada, the 2018 Camp Fire in California, USA, and the 2019 Chuckegg Creek Fire in northern Alberta, Canada. Compared to the traditional log-ratio operator, CNN-based deep learning framework can better distinguish burnt areas with higher accuracy. These findings demonstrate that spaceborne SAR time series with deep learning can play a significant role for near real-time wildfire monitoring when the data becomes available at daily and hourly intervals with the launches of RADARSAT Constellation Missions in 2019, and SAR CubeSat constellations.
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| 23. |
- Ban, Yifang, et al.
(författare)
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Object-Based Fusion of Multitemporal Multiangle ENVISAT ASAR and HJ-1B Multispectral Data for Urban Land-Cover Mapping
- 2013
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Ingår i: IEEE Transactions on Geoscience and Remote Sensing. - 0196-2892 .- 1558-0644. ; 51:4, s. 1998-2006
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Tidskriftsartikel (refereegranskat)abstract
- The objectives of this research are to develop robust methods for segmentation of multitemporal synthetic aperture radar (SAR) and optical data and to investigate the fusion of multitemporal ENVISAT advanced synthetic aperture radar (ASAR) and Chinese HJ-1B multispectral data for detailed urban land-cover mapping. Eight-date multiangle ENVISAT ASAR images and one-date HJ-1B charge-coupled device image acquired over Beijing in 2009 are selected for this research. The edge-aware region growing and merging (EARGM) algorithm is developed for segmentation of SAR and optical data. Edge detection using a Sobel filter is applied on SAR and optical data individually, and a majority voting approach is used to integrate all edge images. The edges are then used in a segmentation process to ensure that segments do not grow over edges. The segmentation is influenced by minimum and maximum segment sizes as well as the two homogeneity criteria, namely, a measure of color and a measure of texture. The classification is performed using support vector machines. The results show that our EARGM algorithm produces better segmentation than eCognition, particularly for built-up classes and linear features. The best classification result (80%) is achieved using the fusion of eight-date ENVISAT ASAR and HJ-1B data. This represents 5%, 11%, and 14% improvements over eCognition, HJ-1B, and ASAR classifications, respectively. The second best classification is achieved using fusion of four-date ENVISAT ASAR and HJ-1B data (78%). The result indicates that fewer multitemporal SAR images can achieve similar classification accuracy if multitemporal multiangle dual-look-direction SAR data are carefully selected.
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| 24. |
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| 25. |
- Ban, Yifang, et al.
(författare)
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Orbital effects on ERS-1 SAR temporal backscatter profiles of agricultural crops
- 1998
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Ingår i: International Journal of Remote Sensing. - : Informa UK Limited. - 0143-1161 .- 1366-5901. ; 19:17, s. 3465-3470
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Tidskriftsartikel (refereegranskat)abstract
- Multi-temporal radar backscatter characteristics of crops and their underlying soils were analysed for an agricultural area in south-western Ontario, Canada using nine dates of ERS-1 SAR imagery acquired during the 1993 growing season. From the calibrated data, SAR temporal backscatter profiles were generated for each crop type. The results indicate that small changes in incidence-angle can have strong impacts on radar backscatter. Thus, attention must be given to local incidence-angle effects when using ERS-1 SAR data,especially when comparing backscatter coefficients of the same area from different scenes or different areas within the same scene.
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| 26. |
- 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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| 27. |
- Ban, Yifang, et al.
(författare)
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RADARSAT-2 Polarimetric SAR Data for Urban Land Cover Classification : A Multitemporal Dual-Orbit Approach
- 2011
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Konferensbidrag (refereegranskat)abstract
- This research investigates multitemporal dual-orbit RADARSAT-2 polarimetric SAR data for urban land cover classification using an object-based support vector machine (SVM). Six-date RADARSAT-2 high-resolution SAR data in both ascending and descending orbits were acquired in the rural-urban fringe of the Greater Toronto Area during the summer of 2008. The major landuse/land-cover classes include high-density residential area, low-density residential area, industrial and commercial area, construction site, park, golf course, forest, pasture, water and two types of agricultural crops. The results show that multitemporal SAR data improve urban land cover classification and the best classification result is achieved using data from all six-dates. However, similar accuracies could be achieved using only three-date data from both ascending and descending orbits with relatively longer temporal span. Combinations of SAR data with relatively short temporal span are observed to yield lower classification accuracy. Similarly, combinations of SAR data from either ascending or descending orbit alone yield lower accuracy than the combinations of ascending and descending data. The results indicate that the combination of both the ascending and descending spaceborne SAR data with appropriate temporal span are suitable for urban land cover mapping.
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| 28. |
- Ban, Yifang, et al.
(författare)
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RADARSAT Fine-Beam SAR Data for Land-Cover Mapping and Change Detection in the Rural-Urban Fringe of the Greater Toronto Area
- 2007
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Ingår i: Proceedings, Urban Remote Sensing Joint Event, 2007.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This research investigates the capability of the multitemporal RADARSAT Fine-Beam C-HH SAR imagery for landuse/land-cover mapping and change detection in therural-urban fringe of the Greater Toronto Area (GTA). Five-date RADARSAT fine-beamSAR images were acquired during May to August in 2002. One scene of Landsat TM imagery was acquired in 1988 for change detection. The major landuse/land-coverclasses were high-density built-up areas, low-density built-up areas, roads, forests, parks, golf courses, water and three types of agricultural lands. These ten classes were chosen to characterize the complex landuse/land-cover types in the rural-urban fringe of the GTA. The results demonstrated that, for identifying landuse/land-cover classes, five-date raw SAR imagery yielded very poor result due to speckles. Much better results were achieved with combined Mean, Standard Deviation and Correlation texture images using artificial neural networks (ANN) and with raw images using object-based classification. The change detection procedure was able to identify the areas of significant changes, for example, major new roads, new low-density and high-density built up areas and golf courses, even though the overall accuracy of the change detection was rather low.
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| 29. |
- Ban, Yifang, et al.
(författare)
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RADARSAT SAR data for landuse/land-cover classification in the rural-urban fringe of the greater Toronto area
- 2005
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Ingår i: Proceedings 2005.
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Konferensbidrag (refereegranskat)abstract
- This research investigates the capability of the multitemporal RADARSAT Fine-Beam C-HH SAR imagery for extracting landuse/land-cover information in the rural-urban fringe of the Greater Toronto Area (GTA) using various image processing techniques and classification algorithms. Five-date RADARSAT fine-beam SAR images were acquired during May to August in 2002. The major landuse/land-cover classes were high-density built-up areas, low-density built-up areas, roads, forests, parks, golf courses, water and three types of agricultural lands. These ten classes were chosen to characterize the complex landuse/land-cover types in the rural-urban fringe of the GTA. The results demonstrated that, for identifying landuse/land-cover classes, five-date raw SAR imagery yielded very poor result due to speckles. The best result was achieved for combined Mean, Standard Deviation and Correlation texture images using artificial neural networks (ANN) (overall accuracy: 89.7% and Kappa: 0.886). These high accuracies indicated that RADARSAT fine-beam SAR has the potential for operational landuse/land-cover mapping in urban environments.
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| 30. |
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| 31. |
- Ban, Yifang, et al.
(författare)
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Satellite monitoring of urbanization in China for sustainable development : Final results
- 2013
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Ingår i: European Space Agency, (Special Publication) ESA SP, Volume 704 SP, 2013. - : European Space Agency.
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Konferensbidrag (refereegranskat)abstract
- The overall objectives of this research are to investigate spaceborne SAR data, optical data and fusion of SAR and optical data for urbanization monitoring in China, and to assess the impact of urbanization on the environment for sustainable development. Effective segmentation and classification methods for urban extent extraction and land cover mapping were developed. Several change detection algorithms and approaches using SAR and optical data were evaluated. Further, synergistic effects of multisensor SAR data as well as ASAR and HJ-1B data are examined. The results show that the developed methods were effective for urban extent extraction, land cover mapping and change detection. The fusion of multisensor spaceborne SAR as well as fusion of ASAR and HJ-1 data were beneficial for urban land cover mapping. The spatiotemporal patterns of urbanization in China were analyzed. The results show that rapid urbanization in Yangtze River Delta, Jingjinji and Pearl River Delta has a significant impact on the environment in terms of landscape fragmentation and ecosystem services.
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| 32. |
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| 33. |
- 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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| 34. |
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| 35. |
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| 36. |
- Ban, Yifang, et al.
(författare)
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Unsupervised Change Detection Using Multitemporal Spaceborne SAR Data : A Case Study in Beijing
- 2011
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Ingår i: 2011 Joint Urban Remote Sensing Event, JURSE 2011 - Proceedings. - : IEEE. - 9781424486571 ; , s. 161-164
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Konferensbidrag (refereegranskat)abstract
- The objective of this research is to examine unsupervised change detection methods using multitemporal spaceborne SAR data for urbanization monitoring in Beijing. One scene of ENVISAT ASAR C-VV image was acquired in July, 2008 and one scene of ERS-2 SAR C-VV image was acquired in July, 1998. To compare the two SAR images, a modified ratio operator that takes into account both positive and negative changes was developed to derive a change image. A generalized version of Kittler-Illingworth minimum-error thresholding algorithm was then tested to automatically classify the change image into two classes, change and no-change. Various probability density functions such as Log normal, Generalized Gaussian, Nakagami ratio, and Weibull ratio were investigated to model the distribution of the change and no-change classes. The preliminary results showed that Kittler-Illingworth algorithm applied to the modified ratio image is very effective in detecting temporal changes in urban areas using SAR images. Log normal and Nakagami density models achieved the best results. The Kappa coefficients of the these solutions were of 0.82 while the false alarm rates were 2.7%. The initial findings indicated that the accuracy of the change result obtained using Kittler-Illingworth algorithm varies depending on how the assumed conditional class density function fits the histograms of change and no-change classes.
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| 37. |
- Ban, Yifang, et al.
(författare)
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Visualization in ViSuCity : a tool for sustainable city planning
- 2011
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Ingår i: SIGRAD2011. ; , s. 105-109
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Konferensbidrag (refereegranskat)abstract
- This paper gives an overview of several aspects of visualization for city planning as they were used in the projectViSuCity. The overall objective of ViSuCity is to develop an effective web-based, interactive visualization demonstrator,ViSuCity, to support sustainable city planning in terms of information sharing, analysis, development,presentation and communication of ideas and proposals throughout the city planning processes. In this paper, wediscuss and show some results regarding LOD, scalability, streaming, and examples of visualization of roads, etcthat are important for city planning.
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| 38. |
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| 39. |
- 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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| 40. |
- 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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| 41. |
- Chen, Jun, et al.
(författare)
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Collaborative validation of GlobeLand30 : Methodology and practices
- 2021
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Ingår i: Geo-spatial Information Science. - : TAYLOR & FRANCIS LTD. - 1009-5020 .- 1993-5153. ; 24:1, s. 134-144
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Tidskriftsartikel (refereegranskat)abstract
- 30-m Global Land Cover (GLC) data products permit the detection of land cover changes at the scale of most human land activities, and are therefore used as fundamental information for sustainable development, environmental change studies, and many other societal benefit areas. In the past few years, increasing efforts have been devoted to the accuracy assessment of GlobeLand30 and other finer-resolution GLC data products. However, most of them were conducted either within a limited percentage of map sheets selected from a global scale or in some individual countries (areas), and there are still many areas where the uncertainty of 30-m resolution GLC data products remains to be validated and documented. In order to promote a comprehensive and collaborative validation of 30-m GLC data products, the GEO Global Land Cover Community Activity had organized a project from 2015 to 2017, to examine and explore its major problems, including the lack of international agreed validation guidelines and on-line tools for facilitating collaborative validation activities. With the joint effort of experts and users from 30 GEO member countries or participating organizations, a technical specification for 30-m GLC validation was developed based on the findings and experiences. An on-line validation tool, GLCVal, was developed by integrating land cover validation procedures with the service computing technologies. About 20 countries (regions) have completed the accuracy assessment of GlobeLand30 for their territories with the guidance of the technical specification and the support of GLCVal.
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| 42. |
- Claesson, A., et al.
(författare)
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Unmanned aerial vehicles (drones) in out-of-hospital-cardiac-arrest
- 2016
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Ingår i: Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine. - : BioMed Central (BMC). - 1757-7241. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: The use of an automated external defibrillator (AED) prior to EMS arrival can increase 30-day survival in out-of-hospital cardiac arrest (OHCA) significantly. Drones or unmanned aerial vehicles (UAV) can fly with high velocity and potentially transport devices such as AEDs to the site of OHCAs. The aim of this explorative study was to investigate the feasibility of a drone system in decreasing response time and delivering an AED. Methods: Data of Global Positioning System (GPS) coordinates from historical OHCA in Stockholm County was used in a model using a Geographic Information System (GIS) to find suitable placements and visualize response times for the use of an AED equipped drone. Two different geographical models, urban and rural, were calculated using a multi-criteria evaluation (MCE) model. Test-flights with an AED were performed on these locations in rural areas. Results: In total, based on 3,165 retrospective OHCAs in Stockholm County between 2006-2013, twenty locations were identified for the potential placement of a drone. In a GIS-simulated model of urban OHCA, the drone arrived before EMS in 32 % of cases, and the mean amount of time saved was 1.5 min. In rural OHCA the drone arrived before EMS in 93 % of cases with a mean amount of time saved of 19 min. In these rural locations during (n = 13) test flights, latch-release of the AED from low altitude (3-4 m) or landing the drone on flat ground were the safest ways to deliver an AED to the bystander and were superior to parachute release. Discussion: The difference in response time for EMS between urban and rural areas is substantial, as is the possible amount of time saved using this UAV-system. However, yet another technical device needs to fit into the chain of survival. We know nothing of how productive or even counterproductive this system might be in clinical reality. Conclusions: To use drones in rural areas to deliver an AED in OHCA may be safe and feasible. Suitable placement of drone systems can be designed by using GIS models. The use of an AED equipped drone may have the potential to reduce time to defibrillation in OHCA.
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| 43. |
- Cumbane, Silvino Pedro
(författare)
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Population Displacement Estimation During Disasters Using Mobile Phone Data
- 2022
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Natural disasters result in devastating losses in human life, environmental assets, and personal-, regional-, and national economies. The availability of different big data such as satellite images, Global Positioning System (GPS)traces, mobile Call Detail Records (CDR), social media posts, etc., in conjunction with advances in data analytic techniques (e.g., data mining and big data processing, machine learning and deep learning) can facilitate the extraction of geospatial information that is critical for rapid and effective disaster response. However, disaster response system development usually requires the integration of data from different sources (streaming data sources and data sources at rest) with different characteristics and types, which consequently have different processing needs. Deciding which processing framework to use for specific big data to perform a given task is usually a challenge for researchers from the disaster management field. While many things can be accomplished with population and movement data, for disaster management key, and arguably most important task is to analyze the displacement of the population during and after a disaster. Therefore, in this Licentiate, the knowledge and framework resulting from a literature review were used to select tools, and processing strategies to perform population displacement analysis after a disaster. This is a use case of the framework as well as an illustration of the value and challenges (e.g., gaps in data due to power outages) of using CDR data analysis to support disaster management.Using CDR data, the displaced population was inferred by analyzing the variation of home cell-tower for each anonymized mobile phone subscriber before and after a disaster. The effectiveness of the proposed method is evaluated using remote sensing-based building damage assessment data and Displacement Tracking Matrix (DTM) from individuals’ survey responses at shelters after a severe cyclone in Beira city, central Mozambique, in March 2019.The results show an encouraging correlation coefficient (over 70%) between the number of arrivals in each neighborhood estimated using CDR data and from DTM. In addition to this, CDR-based analysis derives the spatial distribution of displaced populations with high coverage of people, i.e., including not only people in shelters but everyone who used a mobile phone before and after a disaster. Moreover, results suggest that if CDR data are available after a disaster, population displacement can be estimated and this information can be used for response activities and for example to contribute to reducing waterborne diseases (e.g., diarrheal disease) and diseases associated with crowding (e.g., acute respiratory infections) in shelters and host communities.
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| 44. |
- Deng, Juan, et al.
(författare)
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Hierarchical Segmentation of Multitemporal RADARSAT-2 SAR Data Using Stationary Wavelet Transform and Algebraic Multigrid Method
- 2014
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Ingår i: IEEE Transactions on Geoscience and Remote Sensing. - 0196-2892 .- 1558-0644. ; 52:7, s. 4353-4363
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this paper is to develop a new effective method for hierarchical segmentation of multitemporal ultrafine-beam synthetic aperture radar (SAR) data in urban areas. Multitemporal RADARSAT-2 ultrafine-beam high-resolution horizontal transmit and horizontal receive-Synthetic Aperture Radar (HH-SAR) images acquired in the rural-urban fringe of the Greater Toronto Area during the summer of 2008 are selected for this research. Stationary wavelet transform (SWT) and algebraic multigrid (AMG) method are proposed for segmentation of SAR data. SWT is applied for decomposition of multitemporal SAR images in image preprocessing. The hierarchical and matrix-based AMG method is applied for segmentation. A pyramid of fine-to-coarse grids is constructed by iteration of selecting representative pixels and calculating the interpolation matrix between a fine-level grid and a coarse-level grid. When the pyramid is completed, segments are determined by a top-down scanning based on the interpolation matrices. The AMG techniques provide a complete hierarchical segmentation of SAR data. The experimental results show that our method produces higher accuracy than eCognition.
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| 45. |
- Dúc, Khánh Ngô, et al.
(författare)
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Ushahidi and Sahana Eden Open-Source Platforms to Assist Disaster Relief : Geospatial Components and Capabilities
- 2014
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Ingår i: Geoinformation for Informed Decisions. - Cham : Springer. ; , s. 163-174
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Konferensbidrag (refereegranskat)abstract
- In responses to recent large-scale disaster events, huge amount of ground information have been collected in addition to the synoptic views from satellite images. Different platforms have been in place to facilitate the collection and management of such critical location-based information from the crowd. This study investigated the current implementation of geospatial components and their capabilities in open-source platforms, particularly Ushahidi and Sahana Eden. Using the 2011 Christchurch earthquake data and following the four main functions of a geo-info system: Data input, Geospatial analysis, Data management, and Visualization, the performance of geospatial-components were evaluated by a group of users. The result showed that with rich visualization on interactive map both Sahana Eden and Ushahidi enable emergency managers to track the needs of disaster-affected people. While Ushahidi can only filter incidents records by time or category, geospatial data management of Sahana Eden is proven to be more powerful, allowing emergency managers input different geospatial data such as incidents, organizations, human resource, warehouses, hospitals, shelters, assets, and projects and visualizing all of these features on a map. It also helps to simplify the coordination among aids agencies. However, geospatial analysis is the limitation of both platforms. The findings recommended that data input with more variety of formats and more geospatial analysis functions should be added. Further research will expand to more case studies taking into account the requirements of disaster management practitioners and emergency responders.
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| 46. |
- Eklundh, Lars, et al.
(författare)
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Timesat for processing time-series data from satellite sensors for land surface monitoring
- 2016
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Ingår i: Remote Sensing and Digital Image Processing. - Cham : Springer International Publishing. - 1567-3200 .- 2215-1842. - 9783319470375 - 9783319470351 ; 20, s. 177-194
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Bokkapitel (refereegranskat)abstract
- The TIMESAT software package has been developed to enable monitoring of dynamic land surface processes using remotely sensed data. The monitoring capability is based on processing of time-series for each image pixel using either of three smoothing methods included in TIMESAT: asymmetric Gaussian fits, doublelogistic fits, and Savitzky-Golay filtering. The methods have different properties and are suitable for a wide range of data with different character and noise properties. The fitting methods can be upper-envelope weighted and can take quality data into account. Based on the fitted functions, growing season parameters are then extracted (beginning, end, amplitude, slope, integral, etc.), and can be merged into images. TIMESAT has been used in a number of application fields: mapping of phenology and phenological variations; ecological disturbances; vegetation classification and characterization; agriculture applications; climate applications; and for improving remote sensing signal quality. Future developments of TIMESAT will include new methods to better handle long gaps in time-series, handling of irregular time sampling, improved smoothing methods, and incorporation of the spatial domain. These modifications will enable use of TIMESAT also for high-resolution data, e.g. data from the planned ESA Sentinel-2 satellite.
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| 47. |
- Fredman, D., et al.
(författare)
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Expanding the first link in the chain of survival – Experiences from dispatcher referral of callers to AED locations
- 2016
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Ingår i: Resuscitation. - : Elsevier. - 0300-9572 .- 1873-1570. ; 107, s. 129-134
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Early use of automated external defibrillators (AED) increases survival in cases of out-of-hospital cardiac arrest (OHCA). Dispatchers play important roles in identifying OHCA, dispatching ambulances and providing callers with telephone-assisted cardiopulmonary resuscitation. Guidelines recommend that AED registries be linked to dispatch centres as tools to refer callers to nearby AED. Aim The aim of this study was to investigate to what extent dispatchers, when provided with a tool to display AED locations and accessibility, referred callers to nearby AED. Methods An application providing real-time visualization of AED locations and accessibility was implemented at four dispatch centres in Sweden. Dispatchers were instructed to refer callers to nearby AED when OHCA was suspected. Such cases were prospectively collected, and geographic information systems were used to identify those located ≤100 m from an AED. Audio recordings of emergency calls were assessed to evaluate the AED referral rate. Results Between February and August 2014, 3009 suspected OHCA calls were received. In 6.6% of those calls (200/3009), an AED was ≤100 m from the suspected OHCA. The AED was accessible and the caller was not alone on scene in 24% (47/200) of these cases. In two of those 47 cases (4.3%), the dispatcher referred the caller to the AED. Conclusion Despite a tool for dispatchers to refer callers to a nearby AED, referral was rare. Only a minority of the suspected OHCA cases occurred ≤100 m from an AED. We identified AED accessibility and callers being alone on scene as obstacles for AED referral.
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| 48. |
- Fredman, David, et al.
(författare)
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Objective classification and comparison of OHCA and AED locations using geographic information systems
- 2015
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Ingår i: Resuscitation. - : Elsevier BV. - 0300-9572 .- 1873-1570. ; 96, s. 21-21
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Tidskriftsartikel (refereegranskat)abstract
- The Utstein registry template stress recording of out-of-hospital cardiac arrest (OHCA) location and suggest eight data options with additional subcategories. The subjectivity in categorization of OHCA locations by emergency medical services (EMS) makes objective regional and international comparisons hard.
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| 49. |
- Fredman, David, et al.
(författare)
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Use of a geographic information system to identify differences in automated external defibrillator installation in urban areas with similar incidence of public out-of-hospital cardiac arrest : A retrospective registry-based study
- 2017
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Ingår i: BMJ Open. - : BMJ Publishing Group Ltd. - 2044-6055. ; 7:5
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Tidskriftsartikel (refereegranskat)abstract
- Objectives Early defibrillation in out-of-hospital cardiac arrest (OHCA) is of importance to improve survival. In many countries the number of automated external defibrillators (AEDs) is increasing, but the use is low. Guidelines suggest that AEDs should be installed in densely populated areas and in locations with many visitors. Attempts have been made to identify optimal AED locations based on the incidence of OHCA using geographical information systems (GIS), but often on small datasets and the studies are seldom reproduced. The aim of this paper is to investigate if the distribution of public AEDs follows the incident locations of public OHCAs in urban areas of Stockholm County, Sweden. Method OHCA data were obtained from the Swedish Register for Cardiopulmonary Resuscitation and AED data were obtained from the Swedish AED Register. Urban areas in Stockholm County were objectively classified according to the pan-European digital mapping tool, Urban Atlas (UA). Furthermore, we reclassified and divided the UA land cover data into three classes (residential, non-residential and other areas). GIS software was used to spatially join and relate public AED and OHCA data and perform computations on relations and distance. Results Between 1 January 2012 and 31 December 2014 a total of 804 OHCAs occurred in public locations in Stockholm County and by December 2013 there were 1828 AEDs available. The incidence of public OHCAs was similar in residential (47.3%) and non-residential areas (43.4%). Fewer AEDs were present in residential areas than in non-residential areas (29.4% vs 68.8%). In residential areas the median distance between OHCAs and AEDs was significantly greater than in non-residential areas (288 m vs 188 m, p<0.001). Conclusion The majority of public OHCAs occurred in areas classified in UA as 'residential areas' with limited AED accessibility. These areas need to be targeted for AED installation and international guidelines need to take geographical location into account when suggesting locations for AED installation.
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| 50. |
- Furberg, Dorothy, et al.
(författare)
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Monitoring of Urbanization and Analysis of Environmental Impact in Stockholm with Sentinel-2A and SPOT-5 Multispectral Data
- 2019
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Ingår i: Remote Sensing. - : MDPI. - 2072-4292. ; 11:20
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Tidskriftsartikel (refereegranskat)abstract
- There has been substantial urban growth in Stockholm, Sweden, the fastest-growingcapital in Europe. The intensifying urbanization poses challenges for environmental managementand sustainable development. Using Sentinel-2 and SPOT-5 imagery, this research investigatesthe evolution of land-cover change in Stockholm County between 2005 and 2015, and evaluatesurban growth impact on protected green areas, green infrastructure and urban ecosystem serviceprovision. One scene of 2015 Sentinel-2A multispectral instrument (MSI) and 10 scenes of 2005SPOT-5 high-resolution instruments (HRI) imagery over Stockholm County are classified into 10land-cover categories using object-based image analysis and a support vector machine algorithmwith spectral, textural and geometric features. Reaching accuracies of approximately 90%, theclassifications are then analyzed to determine impact of urban growth in Stockholm between 2005and 2015, including land-cover change statistics, landscape-level urban ecosystem service provisionbundle changes and evaluation of regional and local impact on legislatively protected areas as well asecologically significant green infrastructure networks. The results indicate that urban areas increasedby 15%, while non-urban land cover decreased by 4%. In terms of ecosystem services, changes inproximity of forest and low-density built-up areas were the main cause of lowered provision oftemperature regulation, air purification and noise reduction. There was a decadal ecosystem serviceloss of 4.6 million USD (2015 exchange rate). Urban areas within a 200 m buer zone around theSwedish environmental protection agency’s nature reserves increased 16%, with examples of urbanareas constructed along nature reserve boundaries. Urban expansion overlapped the deciduousecological corridor network and green wedge/core areas to a small but increasing degree, often inclose proximity to weak but important green links in the landscape. Given these findings, increasedconservation/restoration focus on the region’s green weak links is recommended.
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