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  • 1.
    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.

  • 2.
    Ahlberg, Jörgen
    Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Estimating atmosphere parameters in hyperspectral data2010In: Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI / [ed] Sylvia S. Shen, Paul E. Lewis, SPIE - International Society for Optical Engineering, 2010, Art.nr. 7695-82- p.Conference paper (Refereed)
    Abstract [en]

    We address the problem of estimating atmosphere parameters (temperature, water vapour content) from data captured by an airborne thermal hyperspectral imager, and propose a method based on direct optimization. The method also involves the estimation of object parameters (temperature and emissivity) under the restriction that the emissivity is constant for all wavelengths. Certain sensor parameters can be estimated as well in the same process. The method is analyzed with respect to sensitivity to noise and number of spectral bands. Simulations with synthetic signatures are performed to validate the analysis, showing that estimation can be performed with as few as 10-20 spectral bands at moderate noise levels. More than 20 bands does not improvethe estimates. The proposedmethod is alsoextended to incorporateadditionalknowledge,for examplemeasurements ofatmospheric parameters and sensor noise.

  • 3.
    Ahlberg, Jörgen
    et al.
    Department of IR Systems, Division of Sensor Technology, Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Renhorn, Ingmar
    Department of IR Systems, Division of Sensor Technology, Swedish Defence Research Agency (FOI), Linköping, Sweden.
    An information-theoretic approach to band selection2005In: Proc. SPIE 5811, Targets and Backgrounds XI: Characterization and Representation / [ed] Wendell R. Watkins; Dieter Clement; William R. Reynolds, SPIE - International Society for Optical Engineering, 2005, 15-23 p.Conference paper (Refereed)
    Abstract [en]

    When we digitize data from a hyperspectral imager, we do so in three dimensions; the radiometric dimension, the spectral dimension, and the spatial dimension(s). The output can be regarded as a random variable taking values from a discrete alphabet, thus allowing simple estimation of the variable’s entropy, i.e., its information content. By modeling the target/background state as a binary random variable and the corresponding measured spectra as a function thereof, wecan compute theinformation capacity ofa certainsensoror sensor configuration. This can be used as a measure of the separability of the two classes, and also gives a bound on the sensor’s performance. Changing the parameters of the digitizing process, bascially how many bits and bands to spend, will affect the information capacity, and we can thus try to find parameters where as few bits/bands as possible gives us as good class separability as possible. The parameters to be optimized in this way (and with respect to the chosen target and background) are spatial, radiometric and spectral resolution, i.e., which spectral bands to use and how to quantize them. In this paper, we focus on the band selection problem, describe an initial approach, and show early results of target/background separation.

  • 4.
    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. 

  • 5.
    Andersson, Marcus
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
    Estimating Phosphorus in rivers of Central Sweden using Landsat TM data2012Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Phosphorus flowing via rivers into the Baltic Sea is a major source of nutrients, and in some cases the limiting factor for the growth of algae which causes the phenomenon known as eutrophication. Remote sensing of phosphorus, here using Landsat TM-data, can help to give a better understanding of the process of eutrophication. Since Landsat TM-data is used, this could form a basis for further spatio-temporal analysis in the Baltic Sea region. A method originally described and previously applied for a Chinese river is here transferred and applied to three different rivers flowing into the Baltic Sea. The results show that by measuring the proxy variables of Secchi Depth and Chloryphyll-a the remote sensing model is able to explain 41% of the variance in total- phosphorus for the rivers Dalälven, Norrström and Gavleån without any consideration taken to CDOM, turbidity or other local features.

  • 6.
    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, Vol. 29, no 4, 518-526 p.Article 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.

  • 7.
    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)
  • 8.
    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)
  • 9.
    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)
  • 10.
    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)
  • 11.
    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)
  • 12.
    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)
  • 13.
    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)
  • 14.
    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%.

  • 15.
    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.))
  • 16.
    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)
  • 17.
    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)
  • 18.
    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.

  • 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 crops1997In: ESA SP, 1997, 179-183 p.Conference paper (Other academic)
  • 20.
    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, Vol. 1999, no 25, 438-447 p., 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.

  • 21.
    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, 3465-3470 p.Article 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.

  • 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).
    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. 

  • 23.
    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, H7522-H7522 p.Conference 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.

  • 24.
    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, 1391-1410 p.Article 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).

  • 25.
    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)
  • 26.
    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, 450-456 p.Conference 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.

  • 27.
    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)
  • 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, Vol. 5, no 4, 1087-1094 p.Article 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, 161-164 p.Conference 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.
    Bekele, Yared
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management.
    GIS Based Factor Identification for the Change in Occurrence of Genista pilosa: a Case Study in Southern Sweden2012Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This study has the objective of identifying the possible environmental constraints that has role for the continuous loss of heathland plant Genista pilosa. The study has assessed different environmental settings where the plant occurs by way of overlaying analysis based on multiple spatial data sets. Thereafter empirical change detection analyses on the land use of the study area have been performed on the GIS environment by combining temporal based remotely sensed spatial data. The result was then analyzed using land use dynamicity model and the rates of change on each land use type are identified. Expansion of human activity, especially the spreading of agricultural land and urbanization, is found to be the most determinant factor for the dramatic loss of the plant. Finally serious attention for the protection of the plant is recommended by mentioning the possible problem that would occur due to a loss of biodiversity.

  • 34.
    Berg, Amanda
    et al.
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology. Termisk Systemteknik AB, Linköping, Sweden.
    Ahlberg, Jörgen
    Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, The Institute of Technology. Termisk Systemteknik AB, Linköping, Sweden.
    Classification and temporal analysis of district heating leakages in thermal images2014In: Proceedings of The 14th International Symposium on District Heating and Cooling, 2014Conference paper (Other academic)
    Abstract [en]

    District heating pipes are known to degenerate with time and in some cities the pipes have been used for several decades. Due to bad insulation or cracks, energy or media leakages might appear. This paper presents a complete system for large-scale monitoring of district heating networks, including methods for detection, classification and temporal characterization of (potential) leakages. The system analyses thermal infrared images acquired by an aircraft-mounted camera, detecting the areas for which the pixel intensity is higher than normal. Unfortunately, the system also finds many false detections, i.e., warm areas that are not caused by media or energy leakages. Thus, in order to reduce the number of false detections we describe a machine learning method to classify the detections. The results, based on data from three district heating networks show that we can remove more than half of the false detections. Moreover, we also propose a method to characterize leakages over time, that is, repeating the image acquisition one or a few years later and indicate areas that suffer from an increased energy loss.

  • 35.
    Berg, Amanda
    et al.
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology. Termisk Systemteknik AB, Linköping, Sweden.
    Ahlberg, Jörgen
    Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, The Institute of Technology. Termisk Systemteknik AB, Linköping, Sweden.
    Classification of leakage detections acquired by airborne thermography of district heating networks2014In: 2014 8th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS), IEEE , 2014, 1-4 p.Conference paper (Refereed)
    Abstract [en]

    We address the problem of reducing the number offalse alarms among automatically detected leakages in districtheating networks. The leakages are detected in images capturedby an airborne thermal camera, and each detection correspondsto an image region with abnormally high temperature. Thisapproach yields a significant number of false positives, and wepropose to reduce this number in two steps. First, we use abuilding segmentation scheme in order to remove detectionson buildings. Second, we extract features from the detectionsand use a Random forest classifier on the remaining detections.We provide extensive experimental analysis on real-world data,showing that this post-processing step significantly improves theusefulness of the system.

  • 36.
    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.

  • 37.
    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.

  • 38.
    Boström, Henrik
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Forests of probability estimation trees2012In: International journal of pattern recognition and artificial intelligence, ISSN 0218-0014, Vol. 26, no 2, 1251001- p.Article 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.

  • 39.
    Brandt, S. Anders
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Lim, Nancy J.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Visualising DEM-related flood-map uncertainties using a disparity-distance equation algorithm2016In: The spatial dimensions of water management: Redistribution of benefits and risks / [ed] A. H. Schumann, G. Blöschl, A. Castellarin, J. Dietrich, S. Grimaldi, U. Haberlandt, A. Montanari, D. Rosbjerg, A. Viglione, and S. Vorogushyn, Göttingen: Copernicus Publications on behalf of International Association of Hydrological Sciences (IAHS) , 2016, 153-159 p.Conference paper (Refereed)
    Abstract [en]

    The apparent absoluteness of information presented by crisp-delineated flood boundaries can lead tomisconceptions among planners about the inherent uncertainties associated in generated flood maps. Even mapsbased on hydraulic modelling using the highest-resolution digital elevation models (DEMs), and calibrated withthe most optimal Manning’s roughness (n) coefficients, are susceptible to errors when compared to actual floodboundaries, specifically in flat areas. Therefore, the inaccuracies in inundation extents, brought about by thecharacteristics of the slope perpendicular to the flow direction of the river, have to be accounted for. Instead ofusing the typical Monte Carlo simulation and probabilistic methods for uncertainty quantification, an empiricalbaseddisparity-distance equation that considers the effects of both the DEM resolution and slope was used tocreate prediction-uncertainty zones around the resulting inundation extents of a one-dimensional (1-D) hydraulicmodel. The equation was originally derived for the Eskilstuna River where flood maps, based on DEM dataof different resolutions, were evaluated for the slope-disparity relationship. To assess whether the equation isapplicable to another river with different characteristics, modelled inundation extents from the Testebo Riverwere utilised and tested with the equation. By using the cross-sectional locations, water surface elevations, andDEM, uncertainty zones around the original inundation boundary line can be produced for different confidences.The results show that (1) the proposed method is useful both for estimating and directly visualising modelinaccuracies caused by the combined effects of slope and DEM resolution, and (2) the DEM-related uncertaintiesalone do not account for the total inaccuracy of the derived flood map. Decision-makers can apply it to alreadyexisting flood maps, thereby recapitulating and re-analysing the inundation boundaries and the areas that areuncertain. Hence, more comprehensive flood information can be provided when determining locations whereextra precautions are needed. Yet, when applied, users must also be aware that there are other factors that caninfluence the extent of the delineated flood boundary.

  • 40.
    Brandt, S. Anders
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management.
    Lim, Nancy Joy
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management.
    Importance of river bank and floodplain slopes on the accuracy of flood inundation mapping2012In: River Flow 2012: Volume 2 / [ed] Rafael Murillo Muñoz, Leiden, The Netherlands: CRC Press / Balkema (Taylor & Francis) , 2012, 1015-1020 p.Conference paper (Refereed)
    Abstract [en]

    Effective flood assessment and management depend on accurate models of flood events, which in turn are strongly affected by the quality of digital elevation models (DEMs). In this study, HEC-RAS was used to route one specificwater discharge through the main channel of the Eskilstuna River, Sweden. DEMs with various resolutions and accuracies were used to model the inundation. The results showed a strong positive relationship between the quality of theDEMand the extent of the inundation. However, evenDEMswith the highest resolution produced inaccuracies. In another case study, the Testebo River, the model settings could be calibrated, thanks to a surveyed old inundation event. However, even with the calibration efforts, the resulting inundation extents showed varying degrees of deviation from the surveyed flood boundaries. Therefore, it becomes clear that not only does the resolution of the DEM impact the quality of the results; also, the floodplain slope perpendicular to the river flow will impact the modelling accuracy. Flatter areas exhibited the greatest predictive uncertainties regardless of the DEM’s resolution. For perfectly flat areas, uncertainty becomes infinite.

  • 41.
    Bäckström Bäckman, Rebecca
    Kristianstad University, School of Education and Environment.
    Havsstrandängar i Blekinge län: Förlust och bevarande av habitatet vid en förändrad havsnivå2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    Globala klimatförändringar med en ökad havsnivå leder till att flacka landområden översvämmas, vilket drabbar värdefulla livsmiljöer och ekosystem längs med kusten. Den här undersökningens syfte är att genom en fjärranalys i ett geografiskt informationssystem kartlägga omfattningen av havsstrandängar i Blekinge län som hotas att försvinna till följd av en stigande havsnivå på 0,5 m respektive 1 m. För att vidare identifiera spridningsmöjligheter och en möjlig framtida utbredning för habitatet inåt land vid en förändrad havsnivå. Slutligen kommer fjärranalysens tillförlitlighet i avseendet att hitta spridningsmöjligheter utvärderas efter fältstudier i två utvalda referensområden. Resultatet visar att 98 % av Blekinges befintliga havsstrandängar hotas att försvinna till följd av en ökad havsnivå – men att det finns spridningsmöjligheter inåt land. Undersökningen har lokaliserat spridningsmöjligheter på mark med naturliga förutsättningar för att bli havsstrandäng, vilket anses vara en tillförlitlig tolkningsmetod som pekar på att habitatets utbredningsområde i länet kommer att minska. Det är därför viktigt att Länsstyrelsen i Blekinge arbetar för att så tidigt som möjligt skyddar och hävdar tänkbar utvecklingsmark tillsammans med dagens befintliga havsstrandängar för att underlätta arternas spridning i landskapet och bevara ett biologiskt värdefullt habitat till kommande generationer. 

  • 42. 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, 407-413 p.Conference 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.

  • 43. Duc, K. N.
    et al.
    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 / [ed] Alias Abdul Rahman, Pawel Boguslawski, François Anton, Mohamad Nor Said, Kamaludin Mohd Omar, Springer, 2014, 163-174 p.Chapter in book (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.

  • 44.
    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.

  • 45. Fornieles-Callejon, J.
    et al.
    Salinas, A.
    Toledo-Redondo, Sergio
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Swedish Institute of Space Physics, Uppsala Division.
    Porti, J.
    Mendez, A.
    Navarro, E. A.
    Morente-Molinera, J. A.
    Soto-Aranaz, C.
    Ortega-Cayuela, J. S.
    Extremely low frequency band station for natural electromagnetic noise measurement2015In: Radio Science, ISSN 0048-6604, E-ISSN 1944-799X, Vol. 50, no 3, 191-201 p.Article in journal (Refereed)
    Abstract [en]

    A new permanent ELF measurement station has been deployed in Sierra Nevada, Spain. It is composed of two magnetometers, oriented NS and EW, respectively. At 10 Hz, their sensitivity is 19 V/pT and the signal-to-noise ratio (SNR) is 28 dB for a time-varying signal of 1 pT, the expected field amplitude in Sierra Nevada. The station operates for frequencies below 24 Hz. The magnetometers, together with their corresponding electronics, have been specifically designed to achieve such an SNR for small signals. They are based on high-resolution search coils with ferromagnetic core and 10(6) turns, operating in limited geometry configuration. Different system noise sources are considered, and a study of the SNR is also included. Finally, some initial Schumann resonance measurements are presented in order to validate the performance of the measurement station, including 1 h length spectra, daily variations of resonance amplitudes and frequencies for the different seasons, and a 3 day spectrogram.

  • 46.
    Francisco, Francisco
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.
    Sundberg, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.
    Sonar for Environmental Monitoring. Initial Setup of an Active Acoustic Platform2015Conference paper (Refereed)
  • 47.
    Fransson, Thomas
    Linnaeus University, Faculty of Technology, Department of Forestry and Wood Technology.
    Användning av drönare vid skogsvårdsplanering2014Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    En relativt ny metod i skogsbruket är att samla in data med hjälp av små obemannade flygplan s.k. drönare. Målet med denna studie var erhålla svar på om det är möjligt att använda drönare vid skogsvårdsplanering. Det som undersöktes var vilka parametrar som kunde identifieras i bilder tagna ifrån drönare vid inventering av återväxt, röjningsbehov och röjningsuppföljning. Även hur olika väderlekar, tider på dygnet och omgivande vegetation påverkade bilderna undersöktes. Försöket genomfördes genom ett experiment i fält med provytor som både fotograferades från luften och inventerades i fält. Bilderna blev i de flesta fall av god kvalitet. Antalet plantor underskattades något vid återväxtinventeringen. Skillnaderna mellan bildtolkning och fältinventering var mindre för röjningsbestånd. Utifrån resultaten bedöms det möjligt att använda drönare vid skogsvårdsplanering. 

  • 48.
    Friman, Ola
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Swedish Defence Research Agency, Linköping, Sweden.
    Follo, Peter
    Swedish Defence Research Agency, Linköping, Sweden.
    Ahlberg, Jörgen
    Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, The Institute of Technology. Termisk Systemteknik AB, Linköping, Sweden.
    Sjökvist, Stefan
    Termisk Systemteknik AB, Linköping, Sweden.
    Methods for Large-Scale Monitoring of District Heating Systems Using Airborne Thermography2014In: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, E-ISSN 1558-0644, Vol. 52, no 8, 5175-5182 p.Article in journal (Refereed)
    Abstract [en]

    District heating is a common way of providing heat to buildings in urban areas. The heat is carried by hot water or steam and distributed in a network of pipes from a central powerplant. It is of great interest to minimize energy losses due to bad pipe insulation or leakages in such district heating networks. As the pipes generally are placed underground, it may be difficult to establish the presence and location of losses and leakages. Toward this end, this work presents methods for large-scale monitoring and detection of leakages by means of remote sensing using thermal cameras, so-called airborne thermography. The methods rely on the fact that underground losses in district heating systems lead to increased surface temperatures. The main contribution of this work is methods for automatic analysis of aerial thermal images to localize leaking district heating pipes. Results and experiences from large-scale leakage detection in several cities in Sweden and Norway are presented.

  • 49.
    Friman, Ola
    et al.
    Swedish Defence Research Agency, Linköping, Sweden.
    Tolt, Gustav
    Swedish Defence Research Agency, Linköping, Sweden.
    Ahlberg, Jörgen
    Termisk Systemteknik, Linköping, Sweden.
    Illumination and shadow compensation of hyperspectral images using a digital surface model and non-linear least squares estimation2011In: Proc. SPIE 8180, Image and Signal Processing for Remote Sensing XVII / [ed] Lorenzo Bruzzone, SPIE - International Society for Optical Engineering, 2011, Art.nr 8180-26- p.Conference paper (Refereed)
    Abstract [en]

    Object detection and material classification are two central tasks in electro-optical remote sensing and hyperspectral imaging applications. These are challenging problems as the measured spectra in hyperspectral images from satellite or airborne platforms vary significantly depending on the light conditions at the imaged surface, e.g., shadow versus non-shadow. In this work, a Digital Surface Model (DSM) is used to estimate different components of the incident light. These light components are subsequently used to predict what a measured spectrum would look like under different light conditions. The derived method is evaluated using an urban hyperspectral data set with 24 bands in the wavelength range 381.9 nm to 1040.4 nm and a DSM created from LIDAR 3D data acquired simultaneously with the hyperspectral data

  • 50.
    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)
1234 1 - 50 of 172
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