Building Extraction Based on Openstreetmap Tags and Very High Spatial Resolution Image in Urban Area

Kang, Lu; Wang, Q.; Yan, Heng

doi:10.5194/isprs-archives-xlii-3-715-2018

Cited by 8 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These data have been widely used over the last decade as a supplementary source of information for land-use mapping, and have been especially valuable in classifying artificial surfaces [29]. The most common use is combining OSM and satellite images to extract information related to the urban environment [30][31][32][33]. For example, useful and good-quality land use/land cover (LULC) information was extracted using OSM and GlobeLand30 in Kathmandu and Dar es Salaam with good results Fonte et al [34].…”

Section: Introductionmentioning

confidence: 99%

Automatic Detection of Spatiotemporal Urban Expansion Patterns by Fusing OSM and Landsat Data in Kathmandu

et al. 2019

View full text Add to dashboard Cite

During the last few decades, a large number of people have migrated to Kathmandu city from all parts of Nepal, resulting in rapid expansion of the city. The unplanned and accelerated growth is causing many environmental and population management issues. To manage urban growth efficiently, the city authorities need a means to be able to monitor urban expansion regularly. In this study, we introduced a novel approach to automatically detect urban expansion by leveraging state-of-the-art cloud computing technologies using the Google Earth Engine (GEE) platform. We proposed a new index named Normalized Difference and Distance Built-up Index (NDDBI) for identifying built-up areas by combining the LandSat-derived vegetation index with distances from the nearest roads and buildings analysed from OpenStreetMap (OSM). We also focused on logical consistencies of land-cover change to remove unreasonable transitions supported by the repeat photography. Our analysis of the historical urban growth patterns between 2000 and 2018 shows that the settlement areas were increased from 63.68 sq km in 2000 to 148.53 sq km in 2018. The overall accuracy of mapping the newly-built areas of urban expansion was 94.33%. We have demonstrated that the methodology and data generated in the study can be replicated to easily map built-up areas and support quicker and more efficient land management and land-use planning in rapidly growing cities worldwide.

show abstract

Section: Introductionmentioning

confidence: 99%

Automatic Detection of Spatiotemporal Urban Expansion Patterns by Fusing OSM and Landsat Data in Kathmandu

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Kang,Q. Wang, H. W. Yan has studied under title "Building extraction based on OpenStreetMap tags and very high spatial resolution image in urban area" and compair building extration from OSM and Very high resolution data and they found that the OSM data is rich enough to directly extract almost all the buildings in 2018 [12].…”

Section: Survey Of Literaturementioning

confidence: 99%

Extensive Rooftop Expression Identification and Spatial Analysis

Sangle¹,

Deshmukh²

2023

Advances in Intelligent Systems Research

View full text Add to dashboard Cite

This Research is going to explore innovative ways for Site Evaluation and Potential Assessment to utilize sunlight hitting rooftop extent for green energy potential and agriculture practices. It may intend to green energy, green roofs and water harvesting as per extent area. In this scenario, it is essential to estimate the existing open flat roof surface with full sun on it, hitting light but absolutely no utilization of the surface. The investigation of the urban rooftop extent based on geospatial technology an extensive roof top for solar potential assessment and as to establishing a benchmark for a multifunctional system within one surface area at household level. Those are green energy potential, water harvesting and agriculture practices. A new term Agrivoltaics practice at household level an Agrivoltaics is the process of farming crops under shade of the solar system. In this scenario an Agrivoltaics is an approach for the cultivation of vegetables or portable agriculture system installation at urban rooftop. In this research a major focus on evaluation of site estimation, quantification and potential measure analysis similarly to interpret the role of technology in this scenario. This will be ensure the utilization of existing resources smartly as under stressed resources due to urbanization, population, industrialization and pollution. A specific convinced technology can boost green energy, vegetable food generation, saving water, healthy environment and major effectiveness for the solar energy potential assessment and generation truthfulness can be extended.

show abstract

“…We adopt the widely used segmented channel model [19], [25], [29], which has different propagation parameters to distinguish LoS/NLoS propagation scenarios. The 1 One publicly accessible way to extract building structure information is to use an open source geographic database OpenStreeMap, where the contour and height of a building are given by its raw data tagged with geometry and height, respectively [28].…”

Section: A Channel Modelmentioning

confidence: 99%

“…The convergence depends on the optimality of the Lagrangian problem (15) solved by the innerloop iterations. If Lagrangian problem ( 15) can obtain globally optimal solution for given Lagrangian multipliers {λ i }, then the gradient method by using the updating formula ( 27) and the step size (28) can guarantee the convergence of the dual problem [33], [41]. However, Lagrangian problem ( 15) is non-convex and may not always converge to the globally optimal solution.…”

Section: B Convergence Analysis 1) Inner-loop Convergencementioning

confidence: 99%

Joint 3-D Positioning and Power Allocation for UAV Relay Aided by Geographic Information

Yi¹,

Li²,

Zhu³

et al. 2021

Preprint

View full text Add to dashboard Cite

<div>In this paper, we study to employ geographic information to address the blockage problem of air-to-ground links between UAV and terrestrial nodes. In particular, a UAV relay is deployed to establish communication links from a ground base station to multiple ground users. To improve communication capacity, we fifirst model the blockage effect caused by buildings according to the three-dimensional (3-D) geographic information. Then, an optimization problem is formulated to maximize the minimum capacity among users by jointly optimizing the 3-D position and power allocation of the UAV relay, under the constraints of link capacity, maximum transmit power, and blockage. To solve this complex non-convex problem, a two-loop optimization framework is developed based on Lagrangian relaxation. The outer-loop aims to obtain proper Lagrangian multipliers to ensure the solution of the Lagrangian problem converge to the tightest upper bound on the original problem. The inner-loop solves the Lagrangian problem by applying the block coordinate descent (BCD) and successive convex approximation (SCA) techniques, where UAV 3-D positioning and power allocation are alternately optimized in each iteration. Simulation results confifirm that the proposed solution signifificantly outperforms two benchmark schemes and achieves a performance close to the upper bound on the UAV relay system.</div>

show abstract

Building Extraction Based on Openstreetmap Tags and Very High Spatial Resolution Image in Urban Area

Cited by 8 publications

References 13 publications

Automatic Detection of Spatiotemporal Urban Expansion Patterns by Fusing OSM and Landsat Data in Kathmandu

Automatic Detection of Spatiotemporal Urban Expansion Patterns by Fusing OSM and Landsat Data in Kathmandu

Extensive Rooftop Expression Identification and Spatial Analysis

Joint 3-D Positioning and Power Allocation for UAV Relay Aided by Geographic Information

Contact Info

Product

Resources

About