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Remote Sensing
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Synergy of GIS and Remote Sensing in Civil Engineering
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Synergy of GIS and Remote Sensing in Civil Engineering

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: closed (15 August 2024) | Viewed by 4966

Special Issue Editors

Dr. Susana Del Pozo

E-Mail Website
Guest Editor
Department of Cartographic and Land Engineering, Higher Polytechnic School of Avila, University of Salamanca, Hornos Caleros, 50, 05003 Ávila, Spain
Interests: GIS; webGIS; remote sensing; multi-source data analysis; geographical standards; architectural and built heritage standards
Special Issues, Collections and Topics in MDPI journals
Dr. Laura Piedelobo Martin

E-Mail Website
Guest Editor
Department of Science, Technology and Society, University School of Advanced Studies IUSS Pavia, Palazzo del Broletto, Piazza della Vittoria 15, 27100 Pavia, Italy
Interests: multisource remote sensing; biophysical parameters; essential climate variables; nature-based solutions; regulating ecosystem services; climate change adaptation; disaster risk reduction

Special Issue Information

Dear Colleagues,

The incessant growth of cities, the degradation of natural capital, the loss of ecosystem services, climate change, and the greater occurrence of natural disasters emerge among nowadays’ focal threats. It has been identified that the increase in urban growth is associated with the concentration of the population in an area that drives the change in the land cover pattern. The analysis of the urban growth pattern, especially that of civil constructions, is a continuous process that involves scientists, resource managers, and planners. In this sense, the mapping and monitoring of the spatial and temporal dynamics of civil constructions and the change in land use using remote sensing techniques and GIS are key. In this way, remote sensing technologies together with GIS can contribute significantly to paving the way towards better knowledge-based, cost-effective, accurate, and efficient decision-making in civil engineering that benefits climate change adaptation and mitigation.

These are the key vectors that motivate this Special Issue, which welcomes state-of-the-art research articles and review articles dealing with the synergies of GIS and remote sensing applied to civil engineering studies. Topics of interest include, but are not limited to:

  • Remote sensing and GIS in civil engineering using hyperspectral satellite and/or airborne data, such as PRISMA or AVIRIS-NG.
  • Synergies of active and passive remote sensing to support planning, design, and operational monitoring and management of infrastructures in civil engineering.
  • Remote sensing and GIS support early warning systems, such as for floods or droughts.
  • Remote sensing and GIS synergies and advancements in monitoring sustainable solutions, such as nature-based solutions, and green or blue infrastructure.
  • Remote sensing and GIS potential for the mapping and assessment of ecosystems and their services, with a special interest in metrics to assess the ecosystem status.
  • Multisource remote sensing metrics of essential climate variables.
  • Remote sensing and GIS in the development of pre-operational and/or operational downstream services.
  • Supporting decision-making processes with spatial information in construction and planning.

Advancements and further developments are needed within space and Earth Observation programs and geo-information systems and services in civil engineering.  

Dr. Susana Del Pozo
Dr. Laura Piedelobo Martín
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • remote sensing
  • earth observation
  • nondestructive techniques
  • GIS processing and modeling
  • geospatial analysis
  • civil engineering
  • building construction
  • sustainable development
  • optical sensing
  • thermal sensing
  • image processing and analysis
  • spatial planning
  • surveying monitoring
  • climate change
  • nature-based solutions

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Published Papers (2 papers)

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Research

17 pages, 10306 KiB  
Article
BIM Data Model Based on Multi-Scale Grids in Civil Engineering Buildings
by Huangchuang Zhang, Ge Li and Meilin Pu
Remote Sens. 2024, 16(4), 690; https://doi.org/10.3390/rs16040690 - 15 Feb 2024
Viewed by 2071
Abstract
The construction of digital twin cities is a current research hotspot; GIS technology and BIM technology are widely used in the field of digital twin cities. However, BIM is still subject to major limitations in its applications, mainly due to huge amounts of [...] Read more.
The construction of digital twin cities is a current research hotspot; GIS technology and BIM technology are widely used in the field of digital twin cities. However, BIM is still subject to major limitations in its applications, mainly due to huge amounts of model data, low query efficiency and accuracy, non-uniform marking systems, etc. The reason is that the BIM model itself focuses more on the expression of visual effects and lacks spatial calculation ability and the utilization of spatial location information. Secondly, the current lightweight processing methods for BIM models are mostly based on geometric transformation and rendering optimization, focusing more on the data compression and visual quality of the model, which essentially does not change the data structure of the BIM model, and it is difficult to establish the mapping relationship between spatial location and spatial data, information, and resources. In addition, current coding methods proposed for BIM models are mostly based on the line classification method, which realizes the identification of components based on the classification of their attributes, and the location information is stored according to the attributes or natural language descriptions, which need to be parsed and translated when they are used, and this procedure ignores the importance of spatial location in daily management and emergency management. The importance of spatial location in daily management and emergency management is also ignored. Based on this kind of identification code, it is impossible to directly analyze and apply spatial location data. Therefore, this paper takes the combination of GIS technology and BIM technology as the starting point and proposes a BIM data modeling method based on the BeiDou grid code, based on the efficiency of its underlying data organization and the accuracy of its real geographic location expression on the one hand and the completeness of the information expression by BIM and fine three-dimensional visualization on the other hand. Finally, a series of experiments are carried out based on the method. Through visualization modeling and efficiency experiments, different feature models are meshed to verify the feasibility and efficiency of the model. Through coding and information query experiments, the model′s data organization capability, data dynamic carrying capability, and efficient spatial computation capability and practical application capability are verified. Full article
(This article belongs to the Special Issue Synergy of GIS and Remote Sensing in Civil Engineering)
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15 pages, 6785 KiB  
Article
A Digital Grid Model for Complex Time-Varying Environments in Civil Engineering Buildings
by Huangchuang Zhang and Ge Li
Remote Sens. 2023, 15(16), 4037; https://doi.org/10.3390/rs15164037 - 15 Aug 2023
Viewed by 1482
Abstract
The indoor environment is typically a complex time-varying environment. At present, the problem of indoor modeling is still a hot research topic for scholars at home and abroad. This paper primarily studies indoor time-varying space. On the basis of the Beidou grid framework [...] Read more.
The indoor environment is typically a complex time-varying environment. At present, the problem of indoor modeling is still a hot research topic for scholars at home and abroad. This paper primarily studies indoor time-varying space. On the basis of the Beidou grid framework and time coding model, in the first scenario, a local space subdivision framework based on Beidou is proposed. The necessity of local space subdivision framework is analyzed. In the second scenario, based on the time coding model needle, a local temporal subdivision model, more suitable for a short time domain, is proposed. Then, for the spatial modeling of an indoor time-varying environment, an indoor time-varying mesh frame based on global subdivision, local space subdivision, and local time subdivision is proposed. Using this framework, the indoor environment is represented by the space–time grid, and the basic storage data structure is designed. Finally, the experiment of local subdivision coding in the indoor space–time grid, indoor space–time grid modeling, and an organization experiment is carried out using real data and simulation data. The experimental results verify the feasibility and correctness of the encoding and decoding algorithm of local subdivision encoding in space–time encoding and the calculation algorithm of the space–time relationship. The experimental results also verify the multi-space organization and the management ability of the indoor space–time grid model. Full article
(This article belongs to the Special Issue Synergy of GIS and Remote Sensing in Civil Engineering)
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