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  • 1.
    Abrehdary, Majid
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Satellite Positioning. Univ Karlstad, Sweden.
    Sjöberg, L. E.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Satellite Positioning.
    Bagherbandi, Mohammad
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Satellite Positioning. Univ Gavle, Sweden.
    Sampietro, D.
    Towards the Moho depth and Moho density contrast along with their uncertainties from seismic and satellite gravity observations2017In: Journal of Applied Geodesy, ISSN 1862-9016, E-ISSN 1862-9024, Vol. 11, no 4, p. 231-247Article in journal (Refereed)
    Abstract [en]

    We present a combined method for estimating a new global Moho model named KTH15C, containing Moho depth and Moho density contrast (or shortly Moho parameters), from a combination of global models of gravity (GOCO05S), topography (DTM2006) and seismic information (CRUST1.0 and MDN07) to a resolution of 1 degrees x 1 degrees based on a solution of Vening Meinesz-Moritz' inverse problem of isostasy. This paper also aims modelling of the observation standard errors propagated from the Vening Meinesz-Moritz and CRUST1.0 models in estimating the uncertainty of the final Moho model. The numerical results yield Moho depths ranging from 6.5 to 70.3 km, and the estimated Moho density contrasts ranging from 21 to 650 kg/m(3), respectively. Moreover, test computations display that in most areas estimated uncertainties in the parameters are less than 3 km and 50 kg/m(3), respectively, but they reach to more significant values under Gulf of Mexico, Chile, Eastern Mediterranean, Timor sea and parts of polar regions. Comparing the Moho depths estimated by KTH15C and those derived by KTH11C, GEMMA2012C, CRUST1.0, KTH14C, CRUST14 and GEMMA1.0 models shows that KTH15C agree fairly well with CRUST1.0 but rather poor with other models. The Moho density contrasts estimated by KTH15C and those of the KTH11C, KTH14C and VMM model agree to 112, 31 and 61 kg/m(3) in RMS. The regional numerical studies show that the RMS differences between KTH15C and Moho depths from seismic information yields fits of 2 to 4 km in South and North America, Africa, Europe, Asia, Australia and Antarctica, respectively.

  • 2.
    Adjei-Darko, Priscilla
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Remote Sensing and Geographic Information Systems for Flood Risk Mapping and Near Real-time Flooding Extent Assessment in the Greater Accra Metropolitan Area2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Disasters, whether natural or man-made have become an issue of mounting concern all over the world. Natural disasters such as floods, earthquakes, landslides, cyclones, tsunamis and volcanic eruptions are yearly phenomena that have devastating effect on infrastructure and property and in most cases, results in the loss of human life. Floods are amongst the most prevalent natural disasters. The frequency with which floods occur, their magnitude, extent and the cost of damage are escalating all around the globe. Accra, the capital city of Ghana experiences the occurrence of flooding events annually with dire consequences. Past studies demonstrated that remote sensing and geographic information system (GIS) are very useful and effective tools in flood risk assessment and management.  This thesis research seeks to demarcate flood risk areas and create a flood risk map for the Greater Accra Metropolitan Area using remote sensing and Geographic information system. Multi Criteria Analysis (MCA) is used to carry out the flood risk assessment and Sentinel-1A SAR images are used to map flood extend and to ascertain whether the resulting map from the MCA process is a close representation of the flood prone areas in the study area.  The results show that the multi-criteria analysis approach could effectively combine several criteria including elevation, slope, rainfall, drainage, land cover and soil geology to produce a flood risk map. The resulting map indicates that over 50 percent of the study area is likely to experience a high level of flood.  For SAR-based flood extent mapping, the results show that SAR data acquired immediately after the flooding event could better map flooding extent than the SAR data acquired 9 days after.  This highlights the importance of near real-time acquisition of SAR data for mapping flooding extent and damages.  All parts under the study area experience some level of flooding. The urban land cover experiences very high, and high levels of flooding and the MCA process produces a risk map that is a close depiction of flooding in the study area.  Real time flood disaster monitoring, early warning and rapid damage appraisal have greatly improved due to ameliorations in the remote sensing technology and the Geographic Information Systems.

  • 3.
    Alvarez, Manuela
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Mapping forest habitats in protected areas by integrating LiDAR and SPOT Multispectral Data2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    KNAS (Continuous Habitat Mapping of Protected Areas) is a Metria AB project that produces vegetation and habitat mapping in protected areas in Sweden. Vegetation and habitat mapping is challenging due to its heterogeneity, spatial variability and complex vertical and horizontal structure. Traditionally, multispectral data is used due to its ability to give information about horizontal structure of vegetation. LiDAR data contains information about vertical structure of vegetation, and therefore contributes to improve classification accuracy when used together with spectral data. The objectives of this study are to integrate LiDAR and multispectral data for KNAS and to determine the contribution of LiDAR data to the classification accuracy. To achieve these goals, two object-based classification schemes are proposed and compared: a spectral classification scheme and a spectral-LiDAR classification scheme. Spectral data consists of four SPOT-5 bands acquired in 2005 and 2006. Spectral-LiDAR includes the same four spectral bands from SPOT-5 and nine LiDAR-derived layers produced from NH point cloud data from airborne laser scanning acquired in 2011 and 2012 from The Swedish Mapping, Cadastral and Land Registration Authority. Processing of point cloud data includes: filtering, buffer and tiles creation, height normalization and rasterization. Due to the complexity of KNAS production, classification schemes are based on a simplified KNAS workflow and a selection of KNAS forest classes. Classification schemes include: segmentation, database creation, training and validation areas collection, SVM classification and accuracy assessment. Spectral-LiDAR data fusion is performed during segmentation in eCognition. Results from segmentation are used to build a database with segmented objects, and mean values of spectral or spectral-LiDAR data. Databases are used in Matlab to perform SVM classification with cross validation. Cross validation accuracy, overall accuracy, kappa coefficient, producer’s and user’s accuracy are computed. Training and validation areas are common to both classification schemes. Results show an improvement in overall classification accuracy for spectral-LiDAR classification scheme, compared to spectral classification scheme. Improvements of 21.9 %, 11.0 % and 21.1 % are obtained for the study areas of Linköping, Örnsköldsvik and Vilhelmina respectively. 

  • 4.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatik och Geodesi.
    Assessing the Impact of Landscape Dynamics on the Terrestrial Biodiversity Using Multisensor Renmote Sensing Project #: DNR 151/05 & DNR 151/05:2: A Project Report Submitted to the Swedish National Space Board2010Report (Other academic)
  • 5.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatik och Geodesi.
    ENVISAT ASAR Dual-Polarization Temporal Backscatter Profiles of Urban Land Covers2005In: The 9th International Symposium on Physical Measurements and Signatures in Remote Sensing (ISPMSRS) , 2005Conference paper (Other academic)
  • 6.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    ENVISAT ASAR for Land Cover Mapping and Change Detection: A Report Submitted to the Swedish National Space Board2006Report (Other academic)
  • 7.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Fusion of Spaceborne SAR and Optical Data for Urbanization Monitoring Project #: DNR 144-08: A Project Report Submitted to the Swedish National Space Board2010Report (Other academic)
  • 8.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Multitemporal ERS-1 SAR and Landsat TM data for agricultural crop classification: comparison and synergy2003In: Canadian journal of remote sensing, ISSN 0703-8992, E-ISSN 1712-7971, Vol. 29, no 4, p. 518-526Article in journal (Refereed)
    Abstract [en]

    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.

  • 9.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Spaceborne SAR for Analysis of Urban Environment and Detection of Human Settlements Project #: DNR 125-0: A Project Report Submitted to the Swedish National Space Board2010Report (Other academic)
  • 10.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Ahmed, Kazi Ishtiak
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    ENVISAT ASAR for Land Cover Mapping and Change Detection in the Rural-Urban Fringe of the Greater Toronto Area2007In: Proceedings, 5th International Symposium on Retrieval of Bio- and Geophysical Parameters from SAR Data for Land Applications, 2007Conference paper (Other academic)
  • 11.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    et, al.
    ViSuCity: A Visual Sustainable City Planning Tool2010Report (Other academic)
  • 12.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Gamba, P.
    EO4Urban: First-year results on Sentinel-1A SAR and Sentinel-2A MSI data for global urban services2016In: European Space Agency, (Special Publication) ESA SP, 2016Conference paper (Refereed)
    Abstract [en]

    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%.

  • 13.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Gamba, Paolo
    University of Pavia.
    Gong, Peng
    Du, Peijun
    Satellite Monitoring of Urbanization in China for Sustainable Development: Preliminary Results2010In: Proceedings of ESA Living Planet Symposium, 2010Conference paper (Other academic)
  • 14.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Gamba, Paolo
    Gong, Peng
    Du, Peijun
    Satellite Monitoring of Urbanization in China for Sustainable Development: The Dragon 'Urbanization' Project2011In: IEEE EarthzineArticle in journal (Other (popular science, discussion, etc.))
  • 15.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Gamba, Paolo
    Jacob, Alexander
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Salentining, A.
    Multitemporal, multi-rsolution SAR data for urbanization mapping and monitoring: midterm results2014In: Proceedings of the Dragon 3 mid-term results Symposium, ESA , 2014Conference paper (Other academic)
  • 16.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Gong, P.
    Gamba, P.
    Du, P.
    Satellite monitoring of urbanization in China for sustainable development: Final results2013In: European Space Agency, (Special Publication) ESA SP, Volume 704 SP, 2013, European Space Agency, 2013Conference paper (Refereed)
    Abstract [en]

    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.

  • 17.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Howarth, P. J.
    Multitemporal ERS-1 SAR data for crop classification: a sequential-masking approach1999In: Canadian journal of remote sensing, ISSN 0703-8992, E-ISSN 1712-7971, Vol. 1999, no 25, p. 438-447, article id 5Article in journal (Refereed)
    Abstract [en]

    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.

  • 18.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Howarth, P. J.
    Orbital effects on ERS-1 SAR temporal backscatter profiles of agricultural crops1997In: ESA SP, 1997, p. 179-183Conference paper (Other academic)
  • 19.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Howarth, P. J.
    Orbital effects on ERS-1 SAR temporal backscatter profiles of agricultural crops1998In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 19, no 17, p. 3465-3470Article in journal (Refereed)
    Abstract [en]

    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.

  • 20.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Hu, Hongtao
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    RADARSAT Fine-Beam SAR Data for Land-Cover Mapping and Change Detection in the Rural-Urban Fringe of the Greater Toronto Area2007In: Proceedings, Urban Remote Sensing Joint Event, 2007, 2007Conference paper (Other academic)
    Abstract [en]

    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. 

  • 21.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Hu, Hongtao
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Rangel, Irene
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Fusion of RADARSAT fine-beam SAR and QuickBird data for land-cover mapping and change detection2007In: Geoinformatics 2007Proceedings of SPIE - The International Society for Optical Engineering: Remotely Sensed Data And Information, Pts 1 And 2 / [ed] Ju, W; Zhao, S, 2007, Vol. 6752, p. H7522-H7522Conference paper (Refereed)
    Abstract [en]

    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.

  • 22.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Hu, Hongtao
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Rangel, Irene M.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Fusion of Quickbird MS and RADARSAT SAR data for urban land-cover mapping: object-based and knowledge-based approach2010In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 31, no 6, p. 1391-1410Article in journal (Refereed)
    Abstract [en]

    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).

  • 23.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Jian, L.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Kazi, I.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Ihse, M.
    Stockholm University.
    Synergy of ENVISAT ASAR and MERIS Data for Landuse/Land-Cover Mapping: Earsel symposium, Warsaw, Poland2006Other (Other academic)
  • 24.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Marullo, Salvatore
    Eklundh, Lars
    European Remote Sensing: progress, challenges, and opportunities2017In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 38, no 7, p. 1759-1764Article in journal (Refereed)
  • 25.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Niu, Xin
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    RADARSAT-2 Polarimetric SAR Data for Urban Land Cover Classification: A Multitemporal Dual-Orbit Approach2011In: / [ed] Lena Halounová, 2011, p. 450-456Conference paper (Refereed)
    Abstract [en]

    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.

  • 26.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Wallin, Johan
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Fusion of ALOS PALSAR and SPOT HRG Data for Urban Land-Cover Mapping in Stockholm:  2009Conference paper (Other academic)
  • 27.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Webber, Luke
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Gamba, P.
    Paganini, M.
    EO4Urban: Sentinel-1A SAR and Sentinel-2A MSI data for global urban services2017In: 2017 Joint Urban Remote Sensing Event, JURSE 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 7924550Conference paper (Refereed)
    Abstract [en]

    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%.

  • 28.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Wu, Qiaojun
    RADARSAT SAR data for landuse/land-cover classification in the rural-urban fringe of the greater Toronto area2005In: Proceedings 2005: The 8th AGILE International Conference on Geographic Information Science, AGILE 2005, 2005Conference paper (Refereed)
    Abstract [en]

    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.

  • 29.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Yousif, Osama A.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Multitemporal Spaceborne SAR Data for Urban Change Detection in China2012In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, ISSN 1939-1404, E-ISSN 2151-1535, Vol. 5, no 4, p. 1087-1094Article in journal (Refereed)
    Abstract [en]

    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.

  • 30.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Yousif, Osama A
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Multitemporal Spaceborne SAR data for urbanization monitoring in China: Preliminary Result2010In: Proceedings, ESA/MOST Dragon 2 Program Midterm Symposium, 2010Conference paper (Other academic)
    Abstract [en]

    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.

  • 31.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Yousif, Osama A
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Unsupervised Change Detection Using Multitemporal Spaceborne SAR Data: A Case Study in Beijing2011In: 2011 Joint Urban Remote Sensing Event, JURSE 2011 - Proceedings, IEEE , 2011, p. 161-164Conference paper (Refereed)
    Abstract [en]

    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.

  • 32.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Yousif, Osama
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Hu, Hongtao
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Fusion of SAR and Optical Data for Urban Land Cover Mapping and Change Detection2014In: Global Urban Monitoring and Assessment through Earth Observation / [ed] Qihao Weng, CRC Press, 2014Chapter in book (Refereed)
  • 33.
    Blänning, Erik
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatik och Geodesi.
    Ivarsson, Caroline
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatik och Geodesi.
    Assessment of Placing of Field Hospitals After the 2010 Haiti EarthquakeUsing Geospatial Data2012Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    When natural disasters such as earthquakes happen, there is a need for an efficient method to support humanitarian aid organizations in the decision making process. One such decision is placement of Foreign Field Hospitals to assist with medical help.To support such a decision lots of different information and data needs to be gathered and combined. The main objectives of this thesis are to collect existing data published shortly after the earthquake in Haiti 2010 as well as data published up to two months after the earthquake. The data is then to be evaluated according to adequacy for analysis and the result of the analysis to be compared to the actual placements of the field hospitals after the 2010 earthquake.The method used in this analysis is Multi Criteria Evaluation (MCE). Data regarding population, elevation, roads, land use, damage, climate, water, health facility locations and airport location are collected and weighted relative with the Analytic Hierarchy Process (AHP) with weights retrieved from a questionnaire sent out to Non-Governmental Organizations (NGOs) and countries involved in the disaster relief. The result obtained from the MCE is a final suitability map depicting areas that are suitable according to the different factors.The data availability for the thesis project is an issue, due to lack of data published shortly after the earthquake. Some of the data used in the analysis do not have the sufficient detail level. Still, an analysis can be performed where suitable areas are obtained.The suitable locations found in the analysis agree well in most cases with where the actual FFHs are placed, however a few locations are not in proximity to where the suitable areas lie. A few of the locations were located in areas exposed to frequently floods. Even though the data availability and quality leaves things to desire, the analysis method shows promising results for future research. The approach could help aggregating information from different sources and provide support in pre-dispatch organization, already having a set of suitable locations to arrive to.

  • 34.
    Bobrinskaya, Maria
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Remote Sensing for Analysis of Relationships between Land Cover and Land Surface Temperature in Ten Megacities2012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Urbanization is one of the most significant phenomena of the anthropogenic influence on the Earth’s environment. One of the principal results of the urbanization is the creation of megacities, with their local climate and high impact on the surrounding area. The design and evolution of an urban area leads to higher absorption of solar radiation and heat storage in which is the foundation of the urban heat island phenomenon. Remote sensing data is a valuable source of information for urban climatology studies. The main objective of this thesis research is to examine the relationship between land use and land cover types and corresponding land surface temperature, as well as the urban heat island effect and changes in these factors over a 10 year period. 10 megacities around the world where included in this study namely Beijing (China), Delhi (India), Dhaka (Bangladesh), Los Angeles (USA), London (UK), Mexico City (Mexico), Moscow (Russia), New York City (USA), Sao Paulo (Brazil) and Tokyo (Japan).

    Landsat satellite data were used to extract land use/land cover information and their changes for the abovementioned cities. Land surface temperature was retrieved from Landsat thermal images. The relationship between land surface temperature and landuse/land-cover classes, as well as the normalized vegetation index (NDVI) was analyzed.

    The results indicate that land surface temperature can be related to land use/land cover classes in most cases. Vegetated and undisturbed natural areas enjoy lower surface temperature, than developed urban areas with little vegetation. However, the cities show different trends, both in terms of the size and spatial distribution of urban heat island. Also, megacities from developed countries tend to grow at a slower pace and thus face less urban heat island effects than megacities in developing countries.

  • 35.
    Boström, Henrik
    Stockholms universitet, Institutionen för data- och systemvetenskap.
    Forests of probability estimation trees2012In: International journal of pattern recognition and artificial intelligence, ISSN 0218-0014, Vol. 26, no 2, article id 1251001Article in journal (Refereed)
    Abstract [en]

    Probability estimation trees (PETs) generalize classification trees in that they assign class probability distributions instead of class labels to examples that are to be classified. This property has been demonstrated to allow PETs to outperform classification trees with respect to ranking performance, as measured by the area under the ROC curve (AUC). It has further been shown that the use of probability correction improves the performance of PETs. This has lead to the use of probability correction also in forests of PETs. However, it was recently observed that probability correction may in fact deteriorate performance of forests of PETs. A more detailed study of the phenomenon is presented and the reasons behind this observation are analyzed. An empirical investigation is presented, comparing forests of classification trees to forests of both corrected and uncorrected PETS on 34 data sets from the UCI repository. The experiment shows that a small forest (10 trees) of probability corrected PETs gives a higher AUC than a similar-sized forest of classification trees, hence providing evidence in favor of using forests of probability corrected PETs. However, the picture changes when increasing the forest size, as the AUC is no longer improved by probability correction. For accuracy and squared error of predicted class probabilities (Brier score), probability correction even leads to a negative effect. An analysis of the mean squared error of the trees in the forests and their variance, shows that although probability correction results in trees that are more correct on average, the variance is reduced at the same time, leading to an overall loss of performance for larger forests. The main conclusions are that probability correction should only be employed in small forests of PETs, and that for larger forests, classification trees and PETs are equally good alternatives.

  • 36. Daras, I.
    et al.
    Fan, Huaan
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Geodesy (closed 20110301).
    Papazissi, K.
    Fairhead, J. D.
    Determination of a Gravimetric Geoid Model of Greece Using the Method of KTH2010In: Gravity, Geoid And Earth Observation, Springer Berlin/Heidelberg, 2010, p. 407-413Conference paper (Refereed)
    Abstract [en]

    The main purpose of this study is to compute a gravimetric geoid model of Greece using the least squares modification method developed at KTH. In regional gravimetric geoid determination, the modified Stokes' formula that combines local terrestrial data with a global geopotential model is often used nowadays. In this study, the optimum modification of Stokes' formula, introduced by Sjöberg (2003), is employed so that the expected mean square error (MSE) of the combined geoid height is minimized. According to this stochastic method, the geoid height is first computed from modified Stokes' formula using surface gravity data and a global geopotential model (GGM). The precise geoid height is then obtained by adding the topographic, downward continuation, atmospheric and ellipsoidal corrections to the approximate geoid height. In this study the downward continuation correction was not considered for the precise geoid height computations due to a limited DEM. The dataset used for the computations, consisted of terrestrial gravimetric measurements, a DEM model and GPS/Levelling data for the Greek region. Three global geopotential models (EGM96, EIGEN-GRACE02S, EIGEN-GL04C) were tested for choosing the best GGM to be combined into the final solution. Regarding the evaluation and refinement of the terrestrial gravity measurements, the cross-validation technique has been used for detection of outliers. The new Greek gravimetric geoid model was evaluated with 18 GPS/Levelling points of the Greek geodetic network. After using a 7-parameter model to fit the geoid model to the GPS/Levelling data, the agreement between the absolute geoid heights derived from the gravimetric method and the GPS/Levelling data, was estimated to 27 cm while the agreement for the relative geoid heights after the fitting, to 0.9 ppm. In an optimal case study, considering the accuracies of the ellipsoidal and orthometric heights as σh≈±10 cm and σH≈±20 cm respectively, the RMS fit of the model with the GPS/Levelling data was estimated to σN≈±15 cm. The geoid model computed in this study was also compared with some previous Greek geoid models, yielding better external accuracy than them.

  • 37.
    Duc, Khanhngo
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment.
    Vu, T.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Ushahidi and Sahana Eden Open-Source Platforms to Assist Disaster Relief: Geospatial Components and Capabilities2014In: Geoinformation for Informed Decisions, Springer, 2014, Vol. 199679, p. 163-174Conference paper (Refereed)
    Abstract [en]

    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.

  • 38.
    Earon, Robert
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Land and Water Resources Engineering.
    Dehkordi, Seyed Emad
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Land and Water Resources Engineering.
    Olofsson, Bo
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Land and Water Resources Engineering.
    Groundwater Resources Potential in Hard Rock Terrain: A Multivariate Approach2014In: Ground Water, ISSN 0017-467X, E-ISSN 1745-6584Article in journal (Refereed)
    Abstract [en]

    Groundwater resources are limited and difficult to predict in crystalline bedrock due to heterogeneity and anisotropy in rock fracture systems. Municipal-level governments often lack the resources for traditional hydrogeological tests when planning for sustainable use of water resources. A new methodology for assessing groundwater resources potential (GRP) based on geological and topographical factors using principal component analysis (PCA) and analysis of variance (ANOVA) was developed and tested. ANOVA results demonstrated statistically significant differences in classed variable groups as well as in classed GRP scores with regard to hydrogeological indicators, such as specific capacity (SC) and transmissivity. Results of PCA were used to govern the weight of the variables used in the prediction maps. GRP scores were able to identify 79% of wells in a verification dataset, which had SC values less than the total dataset median. GRP values showed statistically significant correlations using both parametric (using transformed datasets) and non-parametric methods. The method shows promise for municipal or regional level planning in crystalline terrains with high levels of heterogeneity and anisotropy as a hydrogeologically and statistically based tool to assist in assessing groundwater resources. The methodology is executed in a geographic information systems environment, and uses often readily available data, such as geological maps, feature maps and topography, and thus does not require expensive and time-consuming aquifer tests.

  • 39.
    Eshagh, Mehdi
    et al.
    Univ West, Dept Engn Sci, Trollhattan, Sweden..
    Johansson, Filippa
    Univ West, Dept Engn Sci, Trollhattan, Sweden..
    Karlsson, Lenita
    Univ West, Dept Engn Sci, Trollhattan, Sweden..
    Horemuz, Milan
    KTH, School of Architecture and the Built Environment (ABE), Real Estate and Construction Management, Geodesy and Satellite Positioning.
    A case study on displacement analysis of Vasa warship2018In: Journal of Geodetic Science, ISSN 2081-9919, E-ISSN 2081-9943, Vol. 8, no 1, p. 43-54Article in journal (Refereed)
    Abstract [en]

    Monitoring deformation of man-made structures is very important to prevent them from a risk of collapse and save lives. Such a process is also used for monitoring change in historical objects, which are deforming continuously with time. An example of this is the Vasa warship, which was under water for about 300 years. The ship was raised from the bottom of the sea and is kept in the Vasa museum in Stockholm. A geodetic network with points on the museum building and the ship's body has been established and measured for 12 years for monitoring the ship's deformation. The coordinate time series of each point on the ship and their uncertainties have been estimated epoch-wisely. In this paper, our goal is to statistically analyse the ship's hull movements. By fitting a quadratic polynomial to the coordinate time series of each point of the hull, its acceleration and velocity are estimated. In addition, their significance is tested by comparing them with their respective estimated errors after the fitting. Our numerical investigations show that the backside of the ship, having highest elevation and slope, has moved vertically faster than the other places by a velocity and an acceleration of about 2 mm/year and 0.1 mm/year(2), respectively and this part of the ship is the weakest with a higher risk of collapse. The central parts of the ship are more stable as the ship hull is almost vertical and closer to the floor. Generally, the hull is moving towards its port and downwards.

  • 40.
    Furberg, Dorothy
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Satellite Monitoring and Impact Assessment of Urban Growth in Stockholm, Sweden between 1986 and 20062010In: Imagin[e,g] Europe: Proceedings of the 29th Symposium of the European Association of Remote Sensing Laboratories, Chania, Greece / [ed] Ioannis Manakos, Chariton Kalaitzidis, IOS Press, 2010, p. 131-142Conference paper (Refereed)
    Abstract [en]

    The objective of this research is to investigate the extent of land-cover change in and around Stockholm from 1986 to 2006 and the nature of the resulting landscape fragmentation with a particular focus on the possible environmental impact. Four scenes of SPOT imagery over the Stockholm area were acquired for this study: two on 13 June 1986, one on 5 August 2006 and one on 4 June 2008. Various image processing and classification algorithms were tested and compared. The best classification results were obtained using an object-based and rule-based approach with texture measures as well as spectral data as inputs. The image pairs from the two decades were classified into seven land cover categories for Stockholm Municipality, i.e., low-density built-up, high-density built-up, industrial areas, open land, forest, mixed forest and open land, and water. The overall accuracies were 93% (kappa: 0.91) for 1986 and 97% (kappa: 0.96) for 2006. Landscape fragmentation and change was evaluated using spatial metrics. The spatial metric results reveal that urban areas increased at the expense of non-built up areas by around 2% both on the municipal and regional levels. The 2006/2008 classification gives evidence of being a more fragmented landscape than that of 1986. While urban areas have become denser within Stockholm municipality, which is in line with the region's development policy, more natural land cover types have at the same time been eroded; a development not in line with the regional goal of maintaining the area's green spaces. The classification technique used on the municipality will be expanded to the region as a whole, and regional trends and consequent recommendations will be the focus of future research

  • 41.
    Furberg, Dorothy
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Satellite Monitoring of Urban Land Cover Change in Stockholm Between 1986 and 2006 and Indicator-Based Environmental Assessment2013In: Earth Observation of Global Changes (EOGC), Springer Berlin/Heidelberg, 2013, p. 205-222Chapter in book (Refereed)
    Abstract [en]

    Over the past few decades, there has been substantial urban growth in Stockholm, Sweden, now the largest city in Scandinavia. This research investigates and evaluates the evolution of land cover/use change in Stockholm between 1986 and 2006 with a particular focus on what impact urban growth has had on the environment using indicators derived from remote sensing and environmental data. Four scenes of SPOT imagery over the Stockholm County area were acquired for this study including two on 13 June 1986, one on 5 August 2006 and one on 4 June 2008. These images are classified into seven land cover categories using an object-based and rule-based approach with spectral data and texture measures as inputs. The classification is then used to generate spatial metrics and environmental indicators for evaluation of fragmentation and land cover/land use change. Based on the environmental indicators, an environmental impact index is constructed for both 1986 and 2006 and then compared. The environmental impact index is based on the proportion and condition of green areas important for ecosystem services, proximity of these areas to intense urban land use, proportion of urban areas in their immediate vicinity, and how impacted they are by noise. The analysis units are then ranked according to their indicator values and an average of the indicator rankings gives an overall index score. Results include a ranking of the landscape in terms of environmental impact in 1986 and 2006, as well as an analysis of which units have improved the least or the most and why. The highest ranked units are located most often to the north and east of the central Stockholm area, while the lowest tend to be located closer to the center itself. Yet units near the center also tended to improve the most in ranking over the two decades, which would suggest a convergence towards modest urban expansion and limited environmental impact.

  • 42.
    Furberg, Dorothy
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Satellite Monitoring of Urban Sprawl and Assessing the Impact of Land-Cover Changes in the Greater Toronto Area2008In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008Conference paper (Other academic)
  • 43.
    Furberg, Dorothy
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Satellite Monitoring of Urban Sprawl and Assessment of its Potential Environmental Impact in the Greater Toronto Area Between 1985 and 20052012In: Environmental Management, ISSN 0364-152X, E-ISSN 1432-1009, Vol. 50, no 6, p. 1068-1088Article in journal (Refereed)
    Abstract [en]

    This research investigates urban sprawl in the Greater Toronto Area (GTA) between 1985 and 2005 and the nature of the resulting landscape fragmentation, particularly with regard to the Oak Ridges Moraine (ORM), an ecologically important area for the region. Six scenes of Landsat TM imagery were acquired in summer of 1985, 1995, and 2005. These images and their texture measures were classified into eight land cover classes with very satisfactory final overall accuracies (93-95 %). Analysis of the classifications indicated that urban areas grew by 20 % between 1985 and 1995 and by 15 % between 1995 and 2005. Landscape fragmentation due to spatio-temporal land cover changes was evaluated using urban compactness indicators and landscape metrics, and results from the latter were used to draw conclusions about probable environmental impact. The indicator results showed that urban proportions increased in nearly all areas outside of the metropolitan center, including on portions of the ORM. The landscape metrics reveal that low density urban areas increased significantly in the GTA between 1985 and 2005, mainly at the expense of agricultural land. The metric results indicate increased vulnerability and exposure to adverse effects for natural and semi-natural land cover through greater contrast and lowered connectivity. The degree of urban perimeter increased around most environmentally significant areas in the region. Changes like these negatively impact species and the regional water supply in the GTA. Further investigation into specific environmental impacts of urban expansion in the region and which areas on the ORM are most at risk is recommended.

  • 44.
    Gao, Liang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Investigations of SAR Polarimetric Features on Land-Cover Classification2008In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008Conference paper (Other academic)
  • 45.
    Gao, Liang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Multitemporal RADARSAT-2 Polarimetric SAR Data for Urban Land-Cover Mapping2010In: Proceedings of SPIE - The International Society for Optical Engineering, Bellingham: SPIE-INT SOC OPTICAL ENGINEERING , 2010, Vol. 7841Conference paper (Refereed)
    Abstract [en]

    The objective of this research is to evaluate the performance of multitemporal RADARSAT-2 polarimetric SAR data for urban land use/land-cover classification. Three dates of RADARSAT-2 polarimetric SAR data were acquired during the summer of 2008 over the rural-urban fringe of the Greater Toronto Area. The major land-cover types are residential areas, industry areas, bare land, golf courses, forest, and agricultural crops. The methodology used in this study follow the manner that first extracting the features and then carrying out the supervised classification taking the different feature combinations as an input. Support vectors machine is selected to be the classifier. SAR features including amplitude, intensity, long-term coherence, Freeman-Durden decomposition are extracted and compared by evaluating the classification abilities. Long-term coherence plays an important role in building discrimination in this study. The best classification results achieved by using the three dates HH, VH, HV amplitude layers and the coherence map. The overall accuracy is 82.3%. The results indicate that RADARSAT-2 polarimetric data has a potential to urban land-cover classification with the proper feature combinations.

  • 46.
    Gao, Liang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
    Zeng, Q.
    Beijing University.
    Terrain Deformation Monitoring in Three Gorges Area Using Permanent Scatterers SAR Interferometry2007In: Proceedings, ScanGIS’2007, 2007, p. 261-267Conference paper (Other academic)
    Abstract [en]

    As a new technique of SAR interferometry (InSAR), permanent scatterersSAR interferometry (PS InSAR) has been successfully applied on some urban areas tomeasure the terrain deformation.[1][2][5] But it is not easy to use it in the mountainousand humid areas due to the uncorrelated and atmospheric errors. Wanzhou is such aplace where landslides frequently take place. It locates in the Three Gorges region,China. In this paper, we present our PS InSAR application on Wanzhou. Investigationsare also made on PS processing flow.

  • 47. Giovanidis, A.
    et al.
    Haustein, T.
    Jorswieck, Eduard
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Kim, D.
    Maximization of the single user rate in OFDMA assuming equal power on allocated subcarriers2007In: 2007 IEEE 65th Vehicular Technology Conference, IEEE , 2007, p. 2751-2755Conference paper (Refereed)
    Abstract [en]

    The problem of optimal power allocation for a single user in an OFDMA system is considered for uplink, under the assumption that the total power is divided equally to a selected subset of subcarriers. This scenario suggests reduced feedback information for power control from base station to the user since only the information over modulation on each subcarrier is necessary. Assuming knowledge of the instantaneous users' channel gains, the rate optimization problem reduces to a subcarrier allocation problem, discribed by a discrete function with the set of possible allocated subcarriers as domain and the set of achievable sum rates as range. A continuous equivalent of the function is used to derive properties that also hold in the discrete case. The function is in general not concave and concavity holds only for high CNR regions - over a specified bound. In all cases however it is proved that the maximum is unique and a simple and efficient algorithm is proposed for subcarrier allocation which always provides the optimal solution concerning the subcarriers to be loaded. The cost in achievable capacity from the use of equal-power compared to actual waterfilling is calculated, which is shown to be small while the gain in frequency resources and feedback reduction is important.

  • 48. Gutiérrez, I.
    et al.
    Bader, F.
    Pijoan, J.
    Ben Slimane, Slimane
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture (Closed 20120101), Communication Systems, CoS (closed 2012-01-01).
    Adaptive resource management for a MC-CDMA system with mixed QoS classes using a cross layer strategy2007In: 2007 IEEE 65th Vehicular Technology Conference, IEEE , 2007, p. 3036-3040Conference paper (Refereed)
    Abstract [en]

    Wireless communications are experiencing a great increasing demand, both user and bandwidth capacity. The efficiency in the resource management and usage will be a dramatically important issue since spectrum and power is a scarce resource, even more in the wireless environment. Under these circumstances, adaptive resource management will lead to high spectral efficiency rates and power saving algorithms. Previous works have focused on increasing the system capacity by means of complex power and rate adaptation techniques at the expense of unfair systems. The present proposal proposes a low complexity algorithm for adaptive resource allocation considering different quality of service classes in a Multicarrier-Code Division Multiple Access (MC-CDMA) system, which is considered according to several researches, as a promising air interface scheme for the Beyond 3G systems.

  • 49. Haas, J.
    et al.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Sentinel-1A SAR and sentinel-2A MSI data fusion for urban ecosystem service mapping2017In: Remote Sensing Applications: Society and Environment, ISSN 2352-9385, Vol. 8, p. 41-53Article in journal (Refereed)
    Abstract [en]

    The two main objectives of this study are to evaluate the potential use and synergetic effects of ESA Sentinel-1A C-band SAR and Sentinel-2A MSI data for classification and mapping of ecologically important urban and peri-urban space and to introduce spatial characteristics into ecosystem service analyses based on remotely sensed data. Image resolutions between 5 m and 20 m provided by the Sentinel satellites introduce a new relevant spatial scale in-between high and medium resolution data at which not only urban areas but also their important hinterlands can be effectively and efficiently mapped. Sentinel-1/2 data fusion facilitates both the capture of ecologically relevant details while at the same time also enabling large-scale urban analyses that draw surrounding regions into consideration. The combined use of Sentinel-1A SAR in Interferometric Wide Swath mode and simulated Sentinel-2A MSI (APEX) data is being evaluated in a classification of the Zürich metropolitan area, Switzerland. The SAR image was terrain-corrected, speckle-filtered and co-registered to the simulated Sentinel-2 image. After radiometric and spatial resampling, the fused image stack was segmented and classified by SVM. After post-classification, landscape elements were investigated in terms of spatial characteristics and topological relations that are believed to influence ecosystem service supply and demand, i.e. area, contiguity, perimeter-to-area ratio and distance. Based on the classification results, ecosystem service supplies and demands accounting for spatial and topological patch characteristics were attributed to 14 land cover classes. The quantification of supply and demand values resulted in a positive ecosystem service budget for Zürich. The spatially adjusted service budgets and the original budgets are similar from a landscape perspective but deviate up to 50% on the patch level. The introduction of spatial and topological patch characteristics gives a more accurate impression of ecosystem service supply and demands and their distributions, thus enabling more detailed analyses in complex urban surroundings. The method and underlying data are considered suitable for urban land cover and ecosystem service mapping and the introduction of spatial aspects into relative ecosystem service valuation concepts is believed to add another important aspect in currently existing approaches.

  • 50.
    Haas, Jan
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Kontinuerlig urbanisering påverkar ekosystemtjänster i Kina2012In: Kart & Bildteknik, ISSN 1651-8705, no 3, p. 26-28Article in journal (Other academic)
123 1 - 50 of 142
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