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  • 1.
    Archer, Jenny
    et al.
    KTH, School of Electrical Engineering (EES), Space and Plasma Physics.
    Dahlgren, Hanna
    KTH, School of Electrical Engineering (EES), Space and Plasma Physics.
    Ivchenko, Nickolay
    KTH, School of Electrical Engineering (EES), Space and Plasma Physics.
    Lanchester, Betty
    School of Physics and Astronomy, University of Southampton, UK.
    Marklund, Göran
    KTH, School of Electrical Engineering (EES), Space and Plasma Physics.
    Dynamics and characteristics of black aurora as observed by high resolution ground-based imagers and radar2011In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 32, no 11, p. 2973-2985Article in journal (Refereed)
    Abstract [en]

    High-resolution, multi-spectral data from the ground-based low-light auroral imager ASK (Auroral Structure and Kinetics) are used to characterize the fine structure of black aurora. Sixteen events comprising sheared and unsheared black arcs, as well as black patches and rings, constitute the analysed dataset. Simultaneous measurements of emissions caused by high- and low-energy precipitation make it possible to relate the characteristics of different black structures to the energy of the precipitating electrons. The reductions of high-energy particles versus low-energy particles in the black regions compared to the diffuse background are investigated for the different forms of black aurora. Two separate mechanisms have been suggested to cause black aurora. The larger reduction of high-energy precipitation within the fine-scale black structures discussed here favours a magnetospheric mechanism that blocks high-energy electrons from being scattered into the loss cone. European Incoherent SCATter radar (EISCAT) electron density profiles are available for one of the nights, and are compared to the optical measurements.

  • 2.
    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.

  • 3.
    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).

  • 4.
    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)
  • 5.
    McCarthy, Jenny
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Land and Water Resources Engineering, Environmental Management and Assessment.
    Gumbricht, Thomas
    KTH, School of Architecture and the Built Environment (ABE), Land and Water Resources Engineering.
    McCarthy, T S
    Ecoregion classification in the Okavango Delta, Botswana from multitemporal remote sensing2005In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 26, no 19, p. 4339-4357Article in journal (Refereed)
    Abstract [en]

    The Okavango inland Delta in Botswana is characterized by a high spatial and temporal variation in vegetation patches and flooding. Predicting the effects of escalating development projects in this pristine wildlife area is hampered by a lack of accurate maps. Efforts using traditional statistical methods have been futile. The processes forming this highly dynamic environment, however, give rise to a well-documented consistency in the land cover pattern at scales ranging from single island architecture to an overall gradient in wetland, flood plain and island occurrence. We conducted a classification in a two-step process starting with statistical methods, and then refining using indices and flooding data. The indices and flooding data were created and selected to make possible the inferring of knowledge about the patterns at different scales through declarative IF ... THEN ... statements. The initial statistical classification achieved a best result of 46% accuracy for 10 classes, whereas the rule-based classification achieved an accuracy of 63%. Application of the derived classification for mapping islands and topography shows a surprisingly high accuracy.

  • 6.
    Niu, Xin
    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.
    Multi-temporal RADARSAT-2 polarimetric SAR data for urban land-cover classification using an object-based support vector machine and a rule-based approach2013In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 34, no 1, p. 1-26Article in journal (Refereed)
    Abstract [en]

    We have investigated multi-temporal polarimetric synthetic aperture radar (SAR) data for urban land-cover classification using an object-based support vector machine (SVM) in combinations of rules. Six-date RADARSAT-2 high-resolution polarimetric SAR data in both ascending and descending passes were acquired in the rural-urban fringe of the Greater Toronto Area during the summer of 2008. The major land-use/land-cover classes include high-density residential areas, low-density residential areas, industrial and commercial areas, construction sites, parks, golf courses, forests, pasture, water, and two types of agricultural crops. Various polarimetric SAR parameters were evaluated for urban land-cover mapping and they include the parameters from Pauli, Freeman and Cloude-Pottier decompositions, the coherency matrix, intensities of each polarization, and their logarithm forms. The multi-temporal SAR polarimetric features were classified first using an SVM classifier. Then specific rules were developed to improve the SVM classification results by extracting major roads and streets using shape features and contextual information. For the comparison of the polarimetric SAR parameters, the best classification performance was achieved using the compressed logarithmic filtered Pauli parameters. For the evaluation of the multi-temporal SAR data set, the best classification result was achieved using all six-date data (kappa = 0.91), while very good classification results (kappa = 0.86) were achieved using only three-date polarimetric SAR data. The results indicate that the combination of both the ascending and the descending polarimetric SAR data with an appropriate temporal span is suitable for urban land-cover mapping.

  • 7.
    Niu, Xin
    et al.
    Natl Univ Def Technol, Peoples R China.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Dou, Yong
    RADARSAT-2 fine-beam polarimetric and ultra-fine-beam SAR data for urban mapping: comparison and synergy2016In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 37, no 12, p. 2810-2830Article in journal (Refereed)
    Abstract [en]

    The aim of this article is to investigate the capabilities of multitemporal RADARSAT-2 fine-beam polarimetric synthetic aperture radar (SAR) data and RADARSAT-2 ultra-fine-beam C-band single-polarization HH SAR (C-HH SAR) data for detailed urban land-cover mapping using a contextual approach. With an adaptive Markov random field and a spatially variant finite mixture model, contextual information was effectively explored to improve the mapping accuracy. A texture enhancement in FMM was further proposed to improve the classification accuracy. Moreover, a rule-based approach exploring object features and spatial relationships was employed to extract road, street, and park. Three-date RADARSAT-2 fine-beam polarimetric SAR (PolSAR) and three-date RADARSAT-2 ultra-fine-beam C-HH SAR data over the Greater Toronto area were used for the evaluation. For 10 major classes, the overall accuracy (OA) is 51% for C-HH SAR data and 79% for PolSAR data. Compared with C-HH SAR, PolSAR data produced better results for identifying various urban patterns. Although with multi-date, the C-HH SAR data showed low capability to distinguish high-density residential area and industry commercial area (Ind.). Considerable low-density residential area (LD) was misclassified as forest. Identification of the construction site (Cons.) and golf course were poor. Nevertheless, the efficiency of the multitemporal C-HH SAR textures for distinguishing the built-up areas was observed. By texture enhancement with the synergy of the PolSAR and C-HH SAR data, the mapping results could be significantly improved, especially for LD, forest, and crops. The OA is improved by 2.7% for PolSAR data, and 11.1% for C-HH SAR data. Road, street, and park could be extracted by the rule-based approach with OA about 77% for 13 classes.

  • 8.
    Qin, Yuchu
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Niu, Z.
    Chen, F.
    Li, B.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Object-based land cover change detection for cross-sensor images2013In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 34, no 19, p. 6723-6737Article in journal (Refereed)
    Abstract [en]

    Accurate and timely land cover change detection at regional and global scales is necessary for both natural resource management and global environmental change studies. Satellite remote sensing has been widely used in land cover change detection over the past three decades. The variety of satellites which have been launched for Earth Observation (EO) and the large volume of remotely sensed data archives acquired by different sensors provide a unique opportunity for land cover change detection. This article introduces an object-based land cover change detection approach for cross-sensor images. First, two images acquired by different sensors were stacked together and principal component analysis (PCA) was applied to the stacked data. Second, based on the Eigen values of the PCA transformation, six principal bands were selected for further image segmentation. Finally, a land cover change detection classification scheme was designed based on the land cover change patterns in the study area. An image-object classification was implemented to generate a land cover change map. The experiment was carried out using images acquired by Landsat 5 TM and IRS-P6 LISS3 over Daqing, China. The overall accuracy and kappa coefficient of the change map were 83.42% and 0.82, respectively. The results indicate that this is a promising approach to produce land cover change maps using cross-sensor images.

  • 9.
    Vu, Tuong Thuy
    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).
    Context-based mapping of damaged buildings from high-resolution optical satellite images2010In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 31, no 13, p. 3411-3425Article in journal (Refereed)
    Abstract [en]

    In the early stages of post-disaster response, a quick and reliable damage assessment map is essential.As time is a critical factor, automated damage mapping from remotely sensed images is the expected solution to drastically reduce data acquisition and computation time. Recently, high-resolution satellite images, such as QuickBird data, have been in high demand by damage assessment analysts and disaster management practitioners. However, the existing automated mapping approaches hardly accommodate such high-resolution data. This research aims at developing a new context-based automated approach for earthquake damage mapping from high-resolution satellite images. Relevant contextual information (including structure, shape, size, edge texture, spatial relations) describing the damage situation is formulated and up-scaled on a morphological scale-space. Speed optimization is achieved by parallel processing implementation. The developed approach was tested with two QuickBird images acquired on 26 June 2005 and 3 June 2008 over YingXiu town, Sichuan, China, which suffered the devastating 12 May 2008 earthquake. In comparison to the reference, the developed mapping approach could achieve over 80% accuracy for computation of the damage ratio. Future research is planned to test the approach on various disaster cases for both optical and radar images using a grid-computing platform towards a cost-effective damage mapping solution.

  • 10.
    Xiang, Deliang
    KTH, School of Architecture and the Built Environment (ABE). National University of Defense Technology, China.
    The cross-scattering component of polarimetric SAR in urban areasand its application to model-based scattering decompositionIn: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901Article in journal (Refereed)
    Abstract [en]

    After the work of Freeman, Durden, Pottier, and Yamaguchi, manydecomposition techniques have been proposed for urban areas, mainly to resolvethe overestimation problem of volume scattering. Since it has been validated thatthe cross-polarised (HV) scattering is caused not only by forests but also byrotated dihedrals, in this paper, we propose a cross scattering coherency matrix tomodel the HV component from orientated and complex buildings and thendemonstrate its performance on model-based scattering decomposition. Thebuilding orientation angle is considered in this coherency matrix, making itflexible and adaptive in the decomposition. Therefore, the HV components fromforests and orientated urban areas can be modelled respectively. Twodecomposition procedures are applied in this paper. The first one is to validatethe effectiveness of this scattering model. We regard the HV component fromurban areas as cross scattering, which is an independent scattering componentadded to the Yamaguchi four-component decomposition. Another one is theurban area decomposition application using this scattering model. Decompositionis implemented for urban and natural areas respectively and the HV componentfrom urban areas is regarded as their volume scattering. This procedure is similarto many other state-of-the-art methods for urban areas and needs to discriminatethe urban and natural areas before decomposition. Spaceborne Radarsat-2 C band,the Airborne Synthetic Aperture Radar (AIRSAR) L band and UninhabitedAerial Vehicle Synthetic Aperture Radar (UAVSAR) L band full polarimetricSAR data are used to validate the performance of this cross scattering coherencymatrix. The HV component of orientated buildings is generated, leading to abetter decomposition result for urban areas.

  • 11.
    Xiang, Deliang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics. National University of Defense Technology, China.
    Ban, Yifang
    Su, Yi
    The cross-scattering component of polarimetric SAR in urban areas and its application to model-based scattering decomposition2016In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 37, no 16Article in journal (Refereed)
    Abstract [en]

    After the work of Freeman, Durden, Pottier, and Yamaguchi, manydecomposition techniques have been proposed for urban areas, mainly to resolvethe overestimation problem of volume scattering. Since it has been validated thatthe cross-polarised (HV) scattering is caused not only by forests but also byrotated dihedrals, in this paper, we propose a cross scattering coherency matrix tomodel the HV component from orientated and complex buildings and thendemonstrate its performance on model-based scattering decomposition. Thebuilding orientation angle is considered in this coherency matrix, making itflexible and adaptive in the decomposition. Therefore, the HV components fromforests and orientated urban areas can be modelled respectively. Twodecomposition procedures are applied in this paper. The first one is to validatethe effectiveness of this scattering model. We regard the HV component fromurban areas as cross scattering, which is an independent scattering componentadded to the Yamaguchi four-component decomposition. Another one is theurban area decomposition application using this scattering model. Decompositionis implemented for urban and natural areas respectively and the HV componentfrom urban areas is regarded as their volume scattering. This procedure is similarto many other state-of-the-art methods for urban areas and needs to discriminatethe urban and natural areas before decomposition. Spaceborne Radarsat-2 C band,the Airborne Synthetic Aperture Radar (AIRSAR) L band and UninhabitedAerial Vehicle Synthetic Aperture Radar (UAVSAR) L band full polarimetricSAR data are used to validate the performance of this cross scattering coherencymatrix. The HV component of orientated buildings is generated, leading to abetter decomposition result for urban areas.

  • 12.
    Yousif, Osama
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    A novel approach for object-based change image generation using multitemporal high-resolution SAR images2017In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 38, no 7, p. 1765-1787Article in journal (Refereed)
    Abstract [en]

    Object-based change detection offers a unique approach for high-resolution images to capture meaningful detailed change information while suppressing noise in change detection results. In this approach, mean intensities of objects are commonly used as a feature and images comparison is carried out based on simple mathematical operations such as ratioing. The strong intensity variations within an object - a consequence of high spatial resolution - combined with synthetic aperture radar (SAR) image speckle degrade the accuracy of object mean intensity estimate, and consequently, affect the quality of the estimated object-based change image. A change quantification approach that takes into account the characteristics of high-resolution SAR images, that is, SAR speckle and the strong intensity variation, is proposed. By descending to the pixel level, a new representation of change data (i.e. the change signal) is proposed. With this representation, change quantification boils down to measuring the roughness of the change signal. Two techniques to assess the intensity of change at the object-level, based on Fourier and wavelet transforms (WT) of the change signal, are proposed. Their main advantages lie in their ability to capture the dominant change behaviour of the object, while being insusceptible to irrelevant disturbances. The proposed approach is evaluated using two multitemporal data sets of TerraSAR-X images acquired over Beijing and Shanghai. The qualitative and quantitative analyses of the results demonstrate the superior discrimination power of the proposed change variables compared with the object-based modified ratio (MR) and the absolute log ratio (LR) images.

1 - 12 of 12
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