Remote sensing for urban planning and management: The use of window-independent context segmentation to extract urban features in Stockholm

Nielsen, Michael Meinild

doi:10.1016/j.compenvurbsys.2015.02.002

Cited by 47 publications

(24 citation statements)

References 27 publications

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“…Remote sensing, in particular satellite-based Earth observation (EO), is a key enabler to encompass the physical dimension of urban green by area-wide mapping and monitoring in multiple nested scales, including the strategic scale(s) of urban planning and management (Nielsen, 2015). Urban green mapping based on EO remote sensing image analysis has become an operational task in city planning, urban land management, and quality of life assessments (Keul & Prinz, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…a group of trees, a lawn between buildings, etc.). Considering their functional and more purpose-related dimension, urban features such as a park, a green belt, green infrastructure, and so on, can be mapped to represent the telic (intentional) dimension (Nielsen, 2015) of city planning. Additionally, specific urban green features may subjectively be conceived differently by citizens with respect to their impression or recreational effects (Keul & Prinz, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…This contains the distribution of the variables that establish the functioning of the region as a system. In addition, the delineation of regions bears constitutive (composition), telic (function and purpose related), and agentive (process-related) components (Nielsen, 2015). In regional geography, the region is conceptualized as an integral part of a larger whole (Tomanev, 2009), that is “unbound [yet] multiscalar” (p. 149), thus having no pre-given status, at least in the post-structural view.…”

Section: Introductionmentioning

confidence: 99%

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Urban green valuation integrating biophysical and qualitative aspects

Lang

2017

European Journal of Remote Sensing

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Urban green mapping has become an operational task in city planning, urban land management, and quality of life assessments. As a multi-dimensional, integrative concept, urban green comprising several ecological, socio-economic, and policy-related aspects. In this paper, the author advances the representation of urban green by deriving scale-adapted, policy-relevant units. These so-called geons represent areas of uniform green valuation under certain size and homogeneity constraints in a spatially explicit representation. The study accompanies a regular monitoring scheme carried out by the urban municipality of the city of Salzburg, Austria, using optical satellite data. It was conducted in two stages, namely SBG_QB (10.2 km², QuickBird data from 2005) and SBG_WV (140 km², WorldView-2 data from 2010), within the functional urban area of Salzburg. The geon delineation was validated by several quantitative measures and spatial analysis techniques, as well as ground documentation, including panorama photographs and visual interpretation. The spatial association pattern was assessed by calculating Global Moran’s I with incremental search distances. The final geonscape, consisting of 1083 units with an average size of 13.5 ha, was analyzed by spatial metrics. Finally, categories were derived for different types of functional geons. Future research paths and improvements to the described strategy are outlined.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Urban green valuation integrating biophysical and qualitative aspects

Lang

2017

European Journal of Remote Sensing

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“…Remote sensing images have wide applications such as object detection [1], environmental monitoring [2], and urban planning [3], etc. With the rapid development of sensor technology, high spatial resolution images are more easily acquired.…”

Section: Introductionmentioning

confidence: 99%

Remote sensing image compression based on binary tree and optimized truncation

Huang

Ren

et al. 2017

Digital Signal Processing

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The remote sensing image data is so vast that it requires compression by low-complexity algorithm on space-borne equipment. Binary tree coding with adaptive scanning order (BTCA) is an effective algorithm for the mission. However, for large-scale remote sensing images, BTCA requires a lot of memory, and does not provide random access property. In this paper, we propose a new coding method based on BTCA and optimize truncation. The wavelet image is first divided into several blocks which are encoded individually by BTCA. According the property of BTCA, we select the valid truncation points for each block carefully to optimize the ratio of rate-distortion, so that a higher compression ratio, lower memory requirement and random access property are attained. Without any entropy coding, the proposed method is simple and fast, which is very suitable for space-borne equipment. Experiments are conducted on three remote sensing image sets, and the results show that it can significantly improve PSNR, SSIM and VIF, as well as subjective visual experience.

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“…This could be achieved by utilizing satellite remote sensing data, since these data were efficiently used to map urban areas as well urban sprawl of the last decades [11,12]. As Nielsen [13] argues, remote sensing has the potential to collect information over large areas repeatedly, and monitoring urban land cover and land use changes [14,15]. Therefore, remote sensing is suitable for investigating and evaluating models and hypotheses and for constructing new theories to help policy-makers and professionals.…”

Section: Introductionmentioning

confidence: 99%

Digital mapping of corrosion risk in coastal urban areas using remote sensing and structural condition assessment: case study in cyprus

et al. 2016

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Atmospheric corrosion is one of the main factors leading to performance deterioration of reinforced concrete buildings; and, hence, periodic structural condition monitoring is required to assess and repair the adverse effects of corrosion. However, this can become a cumbersome and expensive task to undertake for large populations of buildings, scattered in large urban areas. To optimize the use of available resources, appropriate tools are required for the assessment of corrosion risk of reinforced concrete construction. This paper proposes a framework for the production of digital corrosion risk maps for urban areas; Cyprus was used as a case study. This framework explored multi-temporal satellite remote sensing data from the Landsat sensors as well as corrosion risk factors derived from the results of a recently completed research project, entitled "STEELCOR". This framework was used to develop two corrosion risk scenarios within Geographical Information Systems, and to produce corrosion risk maps for three coastal cities of Cyprus. The thematic maps indicated that, for slight corrosion damage, the distance of reinforced concrete buildings from the coast was more influential than the building age. While, for significant corrosion damage, the maps indicated that the age of RC buildings was more influential than the distance from the coast.

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Remote sensing for urban planning and management: The use of window-independent context segmentation to extract urban features in Stockholm

Cited by 47 publications

References 27 publications

Urban green valuation integrating biophysical and qualitative aspects

Urban green valuation integrating biophysical and qualitative aspects

Remote sensing image compression based on binary tree and optimized truncation

Digital mapping of corrosion risk in coastal urban areas using remote sensing and structural condition assessment: case study in cyprus

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